RESERVOIR INNOVATIONSVOLUME 5, NO. 1, 2016 A WIRELINE AND PERFORATING TECHNOLOGY JOURNAL

Subsurface Fluid Characterization Using Downhole and Core NMR T1T2 Maps Combined with Pore-Scale Imaging Techniques

See pages 16-28

Optimized Fracture Stage and Perforation Placement in Horizontal Wells Using a New Calibrated Pulsed-Neutron Log Workflow

See pages 42-50

I N T H I S I S S U E

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A Message from David ToppingWelcome to the ninth edition of RESERVOIR INNOVATIONS where we are proud to present a compilation of technical publications in close collaboration with our customers worldwide. While the market dynamics of our industry continue to be challenging, Halliburton is committed to working with our customers to lower their cost per BOE by collaborating and finding innovative ways to enhance reservoir understanding and maximize productivity.

This edition features a wide range of topics spanning across the oilfield life cycle, from gaining better reservoir insight in the exploration and delineation phases, to innovative well intervention and delivering engineered perforating solutions through the production phases. We are honored to highlight the publication titled, “Subsurface Fluid Characterization Using Downhole and Core NMR T1T2 Maps Combined with Pore-Scale Imaging Techniques,” which won the Best Paper award at the SPWLA 2015 Annual Symposium. The authors received the plaque at the recently concluded 2016 event.

We highly value the industry recognition as a testament of our commitment to the technology innovations we bring to our industry, and our alignment with customer objectives in the quest of meeting global energy demands. In this regard, we’re proud to share that our unique CoreVault® fluid and rock sampling system received the Spotlight on New Technology Award at the Offshore Technology Conference – Asia in Kuala Lumpur in March 2016. Furthermore, our Advanced Perforating Flow Laboratory received the Hart’s Meritorious Award for Engineering Innovation at the Offshore Technology Conference in Houston this May. We have included a paper on how this flow lab is enhancing our understanding of perforating system performance in true reservoir conditions.

We are also pleased to announce that Dr. John Quirein, technology fellow at Halliburton, received the Gold Medal for Technical Achievement award at the SPWLA 2016 Annual Symposium for his contributions to the industry. This is the highest honor bestowed to any individual by SPWLA, recognizing outstanding achievements in the science of formation evaluation that result in significant and enduring contributions to the technology. Additionally, Dr. Luis Quintero, global advisor with our Formation & Reservoir Solutions group, will guide SPWLA in its mission to advance the science of petrophysics and formation evaluation as he takes the helm as SPWLA president for 2016-2017.

We highly appreciate your engagement and collaboration in sharing the knowledge of innovative applications of technology, which are paramount as our industry grapples with extreme market conditions unlike any we’ve ever seen. We, at Halliburton are committed to our customers as we work through these challenges to position ourselves for success into the future. As always, we welcome any feedback and hope you find RESERVOIR INNOVATIONS relevant and useful.

We highly appreciate your business.

Thank you,

David ToppingVice PresidentWireline and Perforating

Executive Steering CommitteeEric CarreSenior Vice President, Global Business Lines

Toby DixonSenior Vice President, Drilling & Evaluation

David ToppingVice President, Wireline and Perforating

Greg PowersVice President, Technology

Editorial Advisory CommitteeShankar NarayanAndrew KirkwoodChris Tevis Dan Quinn Jim HillDavid Larimore Freeman Hill Ron Cherry

Managing EditorSoraya Brombacher

EditorElizabeth Naggar

DesignGina Bean

CirculationNancy Kirkland

This magazine is published by Halliburton Wireline and Perforating

For comments and suggestions, contact: Wireline and Perforating@Halliburton.com

On the CoverHalliburton FracInsight® analysis is an unbiased, repeatable interpretation workflow that leverages the best available horizontal well data, including cased-hole pulsed-neutron logs, to optimize perforation

clusters and hydraulic fracturing stage locations. This service provides an easy-to-read production index and fracability index that are combined to optimize stage and cluster placement.

Special thanks to Chris McIlroy, Eric Mullen, and Scott Jerrett.

See Halliburton.com/FracInsight for video and more information.

FPO

© Copyright 2016 Halliburton. All rights reserved.

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Contents

4 Facies Architecture, Channel System and Paleoflow Pattern of a Young Sandstone Reservoir Using Borehole Resistivity ImagesIntegrating Core-Calibrated Images with Openhole Logs to Characterize Formations

16 Subsurface Fluid Characterization Using Downhole and Core NMR T1T2 Maps Combined with Pore-Scale Imaging TechniquesUsing Core and Log Data to Characterize Wettability

29 Statistical Attenuation of High Amplitude Coherent NoiseAn Ensembled-Based Nonlinear Statistical Method to Address Seismic Processing Problem

34 A Statistical Approach to Wireline Formation Testing Provides a Higher Level of Reservoir UnderstandingIntegration of NMR Facies Classification and Formation Testing Saves Rig Time and Reservoir Evaluation Cost

42 Optimized Fracture Stage and Perforation Placement in Horizontal Wells Using a New Calibrated Pulsed-Neutron Log WorkflowLow-Risk, Pumped-Down PNL for Cost-Effective Completions in Lateral Wells

51 Successful Utilization of E-line Tractor in Horizontal, High-Pressure and High-Temperature Gas WellsConveyance Method Aids in Large Rigless Production Enhancement

58 Operator Uses Advanced Perforation Flow Laboratory to Support HMX Perforating by Coiled Tubing in HPHT FieldConifident Charge Selection Through Simulating Real-World Conditions

63 Pulling Subsea Wellhead Plugs Using a Slickline Downhole Electrical Power Generator ToolUpdated Extended-Stroke DPU Offers Dependendability, Power, and Savings

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Facies Architecture, Channel System and Paleoflow Pattern of a Young Sandstone Reservoir Using Borehole Resistivity ImagesKhalid Ahmed, Hasan Ferdous, Pradeep K. Choudhary, Faisal Abbas, and Waleed Al-Khamees, Kuwait Oil Company; Adly Helba, Adham Osman, Wael Ali, Mohsen Abdel Fatah, and Rafael Vasquez, Halliburton This paper was prepared for presentation at the SPE Middle East Oil & Gas Show and Conference held in Manama, Bahrain, 8 -11 March 2015.Copyright 2015, Society of Petroleum Engineers. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

AbstractThe Miocene age shallow unconsolidated sandstone formation in Kuwait contains viscous oil whose distribution is primarily controlled by depositional facies and their diagenetic modifications. This study integrates core-calibrated resistivity images with openhole logs to obtain high-resolution facies logs with continuous array of oriented depositional structures, facies types, and environment-related facies associations with paleocurrents measurements. These are combined in defining reservoir zonation, geometry, spatial distribution, and paleogeographic evolution during its accretion across the field.

The formation is characterized by variable grain sizes, sedimentary structures, and diagenetic cementations. The sandstone succession is punctuated by scouring surfaces and separated by discrete mudstone intervals mixed with scattered bioclasts. The upper section of the formation encompasses two main oil-producing sandstone intervals (S1 and S2 reservoirs), separated by a mudstone unit (Mid Shale) and sealed on top by a marine Cap Shale unit. Each sandstone interval consists of lower sheet-forming stacked horizontal- and cross-stratified sandstone units (S1B and S2B) and upper lenticular sand-prone bodies (S1A and S2A) that laterally truncate or intermingle with units of sandy mudstone and argillaceous sandstone (S1 Shale and S2 Shale).

The observed physical and biological features, paleocurrents data, and vertical hierarchy of recognized sandstone and mudstone facies suggest the oil-bearing sequence formed as fluvial to upper delta-plain deposits that were accreted by repeated lateral shifting and an overlapping of fluvial channels, distributary/abandoned channels, crevasse splays, and interdistributaries lakes or bays of estuarine origin. The active fluvial and distributary channels were generally flowing from SW to NE, and locally due E and SE, and largely discharged from S. The morphological parameters reveal that the fluvial channels migrated laterally and bifurcated downstream, and fluctuated across a low sinuous channel belt. With continuous base level rise, the area was drained entirely by transgressive brackish-water lacustrine or bay events depositing the widely distributed Mid Shale and Cap Shale units.

IntroductionThe Mid-Miocene sandstone formation in Kuwait is among the shallowest viscous oil-bearing reservoirs. Since its discovery, different studies have been carried out to evaluate the various attributes of the reservoir rocks and its fluids, and to find out the suitable technologies that can enhance its recovery to the optimal production (e.g., Alimi et al. 2006; Sanyal 2009; Al Owihan 2009; Sultan et al. 2010; Madan Jha et al. 2011; and Ferdous et al. 2012).

This oil-bearing formation consists essentially of stacked units of weakly consolidated sandstone being separated by erosional surfaces and thin intervals of mudstone. Laterally persistent shale unit capping two major pay zones that are separated by another marker mudstone unit seals the formation. The pay-forming sandstone has, in most intervals, good porosity (25 to 35%) and permeability (0.3 to 6D); low temperature (82° to 100°F) and pressure (50 to 250 psi); and hosts viscous oil (10° to 18° API) with 30 to 80% oil saturation. (Sultan el al. 2010 and Ferdous et al. 2012). The oil trapping in these reservoirs is primarily of stratigraphic nature with hydrodynamic control of formation water movement (Sultan et al. 2010). Therefore, detailed

INTEGRATING CORE-CALIBRATED IMAGES WITH OPENHOLE LOGS TO CHARACTERIZE FORMATIONS

sedimentological and reservoir architectural analysis is crucial for exploration and production of these young reservoirs. Although intensive drilling with coring of this formation has been done, few and concise literatures dealt with its depositional setting and spatial geometry are published (e.g., Madan Jha et al. 2011 and Ferdous et al. 2012).

This paper integrated resistivity images with core data and openhole logs from 34 vertical wells in order to discriminate with high resolution the different facies types, facies hierarchy, and facies assemblages building up the pay-hosting intervals of the formation. It interpreted the depositional setting and dispersal pattern of the identified facies assemblages, and constructed the architecture of the main depositional elements and its paleogeography in the study block (Fig. 1).

RATQA AABDALI

IRAQ

KUWAIT

SAUDI ARABIA

MINAGISH

GREATER

BURGAN

ABDULIAH

ARABIANGULF

FAILAKA ISLAND

KUBBER ISLAND

QAROH ISLAND

JIM AL-MARADEM ISLANDAL-KHIRAN

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UMM GUDAIR

MEDINA

WAFRA

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NORTHERN SECTOR NYZ-054X

YZ-055X

YZ-056X

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YZ-022X

YZ-062X YZ-007X

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YZ-064XYZ-062X YZ-067X

YZ-0660YZ-008XYZ-064X

YZ-064XYZ-0692

YZ-066X

YZ-072XYZ-067X

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YZ-069X

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YZ-100XYZ-058X YZ-100X

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Fig. 1. Maps showing the location of Kuwait oil fields A) and the location of the study wells in the northern sector B) and southern sector C) of the study block.

Paper 1

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Database and WorkflowThe large dataset used for this study includes resistivity-image log data along with other openhole logs from 34 wells with 12 slabbed cores and core photos in ordinary and ultraviolet lights. The structural dip of the reservoir layers was determined from resistivity images in each well. The lithofacies types were identified based on lithologies, sedimentary structures, and texture/fabric picked from slabbed cores, resistivity images, and from openhole logs after correcting the image-core depth shift. The recognized lithofacies types (LFT) were interpreted in terms of depositional processes and conditions and then grouped into sets of facies associations representing depositional environments and subenvironments.

The paleoflow trends were assigned from the picked dip azimuths of cross stratifications after structural dip removal. Stratigraphic correlation panels in dip and strike directions were constructed using “Linux-Strat” software to demonstrate the vertical and lateral distribution of the recognized facies. All results were integrated in providing a depositional model and tentative paleogeographic maps with estimated paleomorphological parameters of the main depositional elements of each reservoir unit in the study block.

Geological and Stratigraphical SettingThe “Ratqa deep” area in north Kuwait (Figs. 2A and B) is considered as the main depocenter of the Dibdibba Basin where over 4.750-m thick of post-Jurassic-Neogene sediments have accumulated (Carman 1996). The Dibdibba Basin in turn belongs to the mega structure “Mesopotamian foreland deep basin” (Fig. 2A) that resulted from the collision between Arabian Plate and Eurasian Plate since Oligo-Miocene time (Al Sulaimi et al. 2000). The Tertiary sedimentary succession filling Raqba-Dibdibba Basin comprises two main groups: Hasa Carbonate Group (Paleocene-Eocene) and Kuwait Clastic Group (Miocene-Pliocene) separated by Oligocene karst unconformity (Fig. 3A). The Kuwait Group includes three formations: Ghar sandstone (Paleocene-Early Miocene), Fars sandstone (Middle Miocene), and the Upper Miocene-Pliocene Dibdibba gravelly sandstone (HGG 1981). The Neogene structures affected on Kuwait Group were almost related to the uplifting, tilting, and faulting associated with the Arabian Plate motion during Neogene. Its main effect was a tilting of the pre-Neogene sedimentary cover and development of the well-known NW-striking monoclines of Arabia (Fig. 2A). This structural pattern continued in Kuwait

whereby the major lithostratigraphic contacts strike NW-SE and dip very gently NE (Fig. 2C) forming a mature continental slope with regulating continental drainage system that transported and deposited the Neogene clastics into the northeast depression of Dibdibba-Raqba Basin (Al Sulaimi and Al Ruwaih 2004).

The Mid-Miocene sandstone formation rests below Dibdibba Formation and above Ghar Sandstone (Fig. 3A), but its base is not reached in the studied wells. The formation is about 700 to 900-ft thick composed simply of thick to very thick, four reservoir-forming sandstone-dominating members separated by three mudstone-dominating units, and terminated with a marker sealing shale unit (Fig. 3B). These reservoir and nonreservoir units extend all over the study block without a pronounced tectonic deformation. They are nearly horizontal or dip very gently due N with average structural dip magnitude measures 1° to 3° in directions swinging from NW (N 292°) to NE (N 28°) through N (Figs. 3C and D).

Lithofacies and Facies AssociationsThe facies analysis and depositional interpretation of the Mid-Miocene clastic deposits were documented in 34 wells using resistivity images integrated

with openhole logs and calibrated with cores. Twelve principal lithofacies types building the pay-forming sandstone members and the encompassing mudstone units were identified and grouped into five main genetically related facies associations (FA). The individual lithofacies types (LFT), their diagnostic parameters, and mode of formation are summarized in Table 1. The five facies associations are defined relying on a stacking pattern of the constituent facies, nature of vertical facies transition, and lateral geometry with paleoflow trends.

FA-1: Fluvial In-Channel AssociationDescriptionThis association constitutes the backbone and the pay zone of S1B member and the upper 55 to 90-ft thickness of S2B member. It builds also the middle and, in a few wells, the lower intervals of S1A member, but has a restricted occurrence in S2A member. The association consists essentially of LFTs 1 to 4 with subordinate interbeds of LFTs 5 and 6 (Fig. 4A, Table 1). These facies stack vertically into two or three erosively based fining upward sandstone bodies or cycles (10 to 25-ft thick). Each body begins with sharp erosive sole with or without suprajacent gravelly sandstone (Fig. 4B), and consists of interbedded high- andlow-angle cross-laminated sandstone, horizontal-

Fig. 2. A) A tectonic map of the Arabian Plate shows the mega structural elements enclosing Kuwait. B) Simplified structural map of Kuwait showing the location of Ratqa Deep-Dibdibba Basin. C) NE-SW simplified cross section displays NE-ward deepening and thickening of Kuwait Group.

QuaternaryDibdibba FormationFars-Ghar FormationDammam FormationRus FormationUmm er Radhuma FormationTayarat Formation

400

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A’North-east

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laminated sandstone, and massive bedded sandstone, and gradationally terminates either by faint-laminated to bioturbated argillaceous sandstone or being truncated by a scouring surface (Fig. 4A). It is generally barren from body fossils, except for a vague bioturbation recorded in some upper intervals. The sandstone rock is earthy brown to dark brownish gray, friable to weakly consolidated, and almost porous, except in few discrete intervals being partially to extensively cemented by carbonates. It is good to moderately sorted with grain size ranging commonly from medium to very fine sand mixed in some intervals with coarse sands and scattered locally reworked rock fragments. The latter are invariably composed of mudstone and muddy sandstone without exotic grains. They are angular to rounded, poorly sorted with a size reaching to boulders and cobbles (Fig. 4C). The high-angle cross strata are of planar, tangential, and trough types with a set thickness ranging from 0.5 ft up to 4 ft and foresets occasionally aligned with mud drapes. They occur either in solitary sets or in cosets separated by reactivation surfaces (Figs. 4D and E). The trough and tangential cross sets predominate in the lower part of the cycle, commonly have erosive base, and cross cut each other (Fig. 4F). Their foresets show mostly mono- and occasionally bidirectional dip trends with dip magnitude ranging from 10° up to 30° in directions swinging commonly from NW to

ENE through N, and less commonly due SE and SW (Figs. 4H and I). The low-angle cross strata exists as solitary thin to thick sets with foresets dipping 5° to 10°, almost due E or W and N directions (Fig. 4G). The E- and W-ward trends are approximately normal to the main northward dip trend derived from most high-angle cross strata.

InterpretationThe overall clean sand composition, the erosive base, the predominance of high-energy stratifications, and the general fining upward facies stacking pattern verify the deposition within active channels as a channel fill or in-channel bar (Miall 1985 and 1996). The nearly absence of any proper marine body and echno-fossils substantiates fluvial or distributary channel’s origin. The predominant horizontal-laminated sandstone facies indicate upper flow regime traction deposition as flash floods, whereas the high-angle cross-stratified sandstones develop through a migration of subaqueous 2D and 3D dunes in the bottom and middle portions of channels (Harms et al. 1975). On the other hand, the low-angle cross strata suggest a lateral accretion on point bars or on the sides of transverse and longitudinal bars or via a rapid flow in the upper channel portion. Cross sets with mud drapes are interpreted as toe sets of larger tidally influenced fluvial dunes migrating in the channel. This envisaged that the

fluvial channels were located relatively close to the paleo-shoreline similar to a braidplain (Martinius et al. 2012). The frequent scouring surfaces indicate repeated episodes of channels migration, incision, and infill (Bridge et al. 2000 and Bjorklund 2005). The monomictic composition of the rock fragments aligning scouring and reactivation surfaces with its poor sorting, angularity, and boulder to cobble gravelly size indicates a derivation and local transportation from nearby sources as collapsed short-lived banks, and represents lag deposits related to the migration of the channel thalweg and dunes (Kleinhans et al. 2002). The thin bioturbated argillaceous sandstone facies terminating each body represents deposits under waning flow conditions and during abandonment stage of the channels. The sands of this association were transported and accumulated by high-velocity currents that were swinging from NW to NE and less commonly by SW- and SE-ward backflowing currents accompanying scouring and fill processes. The morphological parameters and styles of this channel association are assigned and discussed below.

FA-2: Abandoned Channel AssociationDescriptionThis association shares in building the rock successions of S1A and S2A members. It interfingers with the active channel association (FA1) and the crevasse splay associations (FA-3) in such that whenever exists, it substitutes one of them and rests below the other (Figs. 5A and B). It invariably truncates top channel and calcrete facies assemblage (FA4) occasionally with reworked mudstone and calcrete gravels in its base. The association consists essentially of massive to bioturbated argillaceous sandstone (Fig. 5C), faint-laminated and bioturbated sandy/silty mudstone (Fig. 5D), and rippled- to flaser-laminated argillaceous sandstone/sandy mudstone (Figs. 5E and F) with or without subordinate interbeds of horizontal- and cross-laminated sandstone. These facies types almost organize in fining upward array (Figs. 5A and B). Bioturbation is ubiquitous with some intervals yielding delicate bivalves and dwarfed gastropods (Figs. 5C and 5G). The sandstone facies have characteristic patchy or mottled coloration and moderate to poor sorting with a wide spectrum of grain size ranging from very fine to medium sand in most intervals to very coarse sand in few intervals. They are mostly argillaceous with poor reservoir quality, except the subordinate horizontal- and cross-laminated sandstone facies. The mudstone facies are creamy

Fig. 3. A) General stratigraphic subdivisions of Tertiary succession in Kuwait, B) Informal stratigraphic zonation of sandstone formation in the study block, C and D) Dip azimuths of sandstone formation in the northern and southern sectors of the study block, respectively.

INTEGRATING CORE-CALIBRATED IMAGES WITH OPENHOLE LOGS TO CHARACTERIZE FORMATIONS

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Table 1 – Summary of the Principal Lithofacies; Its Key Attributes and Causative Depositional Processes and Conditions

Lithofacies Type(LFT)

Color and Lithology Physical Structures Grain Size and Sorting Body and Ichnofossils

Distribution Formation Mode Symbols

Earthy brown to dark brownish gray sand and sandstone: partially cemented by carbonates in few intervals

Thick-to-very-thick horizontal stratifications with internal planar lamination, and occasional vague bioturbation

Medium-to-fine-sand grained, occasionally coarse grained with discrete mud balls and chips, almost well to moderate sorted, porous, and reservoir forming

Nonfossiliferous

Very common in the middle and upper portions of the S1A, S1B, and S2B members

Bed-load sedimentation under high-energy upper-flow regime plane bed condition as flash floods

Brownish gray sandstone being in some intervals partially to extensively strengthened by carbonate cement

Thin-to-very-thick beds with internal planar, tangential, and trough-cross stratifications either in solitary sets or in cosets with foresets dipping>10˚. The trough-cross sets commonly have scouring soles and truncate each other

Well sorted with medium lower-to-medium upper and fine-sand grain size with an overall good porosity

Nonfossiliferous

Very common in the lower and middle portions of S1B and S2B members, commonly alternates with LFT1

Bed-load sedimentation via migration of subaqueous 2D and 3D dunes under high- energy flow conditions

LFT 1: Horizontal- laminated sandstone

LFT 2 : Cross-stratified sandstone/argillaceous sandstone

LFT 3: Low-angle cross-laminated sandstone/ argillaceous sandstone

LFT 4: Massive to bioturbated sandstone/argillaceous sandstone

LFT 5: Faint-laminated and bioturbated bioclastic argillaceous sandstone/sandy mudstone

LFT 6: Massive argillaceous gravelly sandstone

LFT 7: Ripple- and flaser-laminated argillaceous sandstone/sandy mudstone

LFT 8: Faint-laminated and bioturbated bioclastic mudstone

LFT 9: Planar-laminated mudstone

LFT 10: Planar-laminated calcareous mudstone

LFT 11: Nodular-bedded calcareous sandy mudstone/argillaceous sandstone

LFT 12: Cross-laminated sandy-to-silty mudstone

Light-to-dark brown sandstone and argillaceous sandstone

Patchy- or mottled- colored sandstone and argillaceous sandstone varying from grayish brown to whitish gray

Creamy green argillaceous sandstone/sandy mudstone, partially calcareous

Light-to-dark brown gravelly/argillaceous sandstone

Patchy-colored (grayish white to grayish brown) argillaceous sandstone grading in some intervals to sand/silty mudstone

Light-to-dark olive green, occasionally reddish brown clayey to silty mudstone, partly calcareous

Light olive or grayish green, mostly clayey, partly silty, and slightly calcareous mudstone

Light olive or grayish green clayey-to-silty calcareous mudstone

Patchy-colored sandy mudstone and argillaceous sandstone being extensively replaced by calcareous cement

Grayish brown sandy-to-silty mudstone or sandy heterolithics

Thin-to-thick sets of low-angle inclined foresets (5° to10°)

Apparently massive with badly preserved horizontal-to-low-angle dipping laminations

Faint planar-to-wavy lamination and bioturbation

Massive, ocassional faint cross stratification, sharp scouring sole, and gradational top

Ripple-, flaser- and lenticular- stratification being obliterated in many intervals by vague bioturbidation and calcareous cementation

Apparently massive, occasionally nodular, and almost homogenized by intensive bioturbation with burrow moldic cavities

Finely laminated, and in parts, bioturbated

Finely laminated, and in parts, bioturbated

Nodular bedded and brecciated with ghosts of horizontal- and low-angle cross lamination and bioturbation

Low-angle dippng (<10°) and occasionally high-angle cross lamination with foresets being invariable aligned with clay drapes

Fine-to-very-fine sand-grained, argillaceous, moderately to well sorted and relatively porous

Moderately to poorly sorted, with a wide spectrum of grain size ranging from very-fine-to- medium sand in most intervals to coarse and very coarse sand in few intervals

Fine-to-very-fine sand and silt-grained, moderate-to- poorly sorted and poorly porous

Poorly sorted rock consisting of granules and boulders of monomictic rock clasts and balls set in muddy-to-very-coarse sandy-grained matrix

Medium-to-very-fine sandy and silty grained with moderate-to-poor sorting and porosity

Clayey and silty grained occaisionally with very fine sand grains

Clayey and silty-grained facies

Clayey and silty-grained facies

Moderately to poorly sorted, with a wide spectrum of grain size ranging from very-fine-to-medium sand mixed with silty- and clayey grains

Silty grains with very fine sand grains

Nonfossiliferous, occasionally with vague burrowing

Thoroughly biotrbated, occasionally with ghosts of gastropods and bivalves mold

Delicate bivalve and gastropod shells

Nonfossilferous

Nonfossilferous, occasionally with vague burrows

Whole and disarticulated delicate bivalves and dwarfed gastropod shells

Ghosts of biogenic molds

Ghosts of biogenic molds

Nonfossilferous with vague burrows

Nonfossilferous with vague burrows

Common, often coexists with the LFTs 1 and 2 in the lower and middle intervals of units S1B and S2B members

Common in the upper parts of S1A, S1B, S2A, and S2B, as well as in S1 shale and S2 shale members, commonly rests with a gradational boundary above LFTs 1 and 2

Essential in S1 shale and S2 shale units and secondary in S1A and S2A members

Very common in the lower and middle parts of S2B member, forms thin discrete intervals in S1A and S2A members

Fairly recorded in upper portion of S1A, S2A, and Mid Shale members

Fundamental facies of S1 and S2 shale units, and shares in the lower and middle intervals of S2A member

Essential facies in Cap Shale and Mid Shale units as well as in some intervals of S1 shale and S2 shale

Common in Cap Shale and Mid Shale units

Common in S1 shale marks the tops of S1A and S2A members

Limted distribution in S1A , S1B, and S2B members

Bed-load sedimentation via lateral accretion on either point bar or on the sides of transverse/longitudinal bars or under decelerating

Bed-load sedimentation under moderate water energy condition or deceleration strong current flow as in the abandoned stage of active channel

Bed- and suspension-load sedimentation under quiet-to-moderate energy condition in semi-restricted water

Scour and fill or rapid dump from decelerating strong grain flows

Bed- and suspension-load sedimentation under oscillatory currents with a fluctuation in current strength and sand-mud supply

Suspension-load sedimentation in quiet semi-restricted water

Suspension-load sedimentation in quiet semi-restricted water

Suspension-load sedimentation in quiet semi-restricted water

Bed- and suspension-load sedimentation under fluc-tuating current strengths and sand-mud supply and subsequent subaerial exposure with calcrete pedogenesis

Migration of ripple trains under fluctuating current strengths and sand-mud supply in very shallow-water depths

Argillaceous

Sandy mudstone

Sandy mudstone

Silty mudstone

Silty mudstone

Silty mudstone

Sandy mudstone

Argillaceous

Argillaceous

Argillaceous

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Fig. 4. A) High-resolution imaged-based facies log displays the essential lithofacies types and facies associations constituting S1B, Mid Shale, S2A, S2 Shale, and S2B members in one of the study’s 34 wells. The S1B and S2B members are composed chiefly of active channel “sandstone” association (FA1) with subordinate intervals of channel top “sand-mud” association (FA4). B) Scouring channel floor with suprajacent lag gravels of locally reworked mudstone. C) Poorly sorted and monomictic rubbles and gravels of intraformational mudstone and muddy sandstone. D) A large-scale solitary set of trough-cross stratification characterizing the lower and middle intervals of active channel sandstone cycles. E) Cosets of medium-scale cross strata separated by reactivation surfaces. F) Erosively based trough-cross sets cross cut each other with bipolar dip direction. G) Low-angle (10°) cross stratification characterizing some sandstone/argillaceous sandstone intervals in the middle and upper parts of active channel sandstone cycles. H and I) Rose diagrams of the picked high-angle cross strata from S1B member in the northern (H) and southern sector (I) of the study block displaying the common NW to NE-ward paleoflow trends in the active channels. Key for facies symbols is shown in Table 1.

gray to olive green in color, almost silty and clayey with scattered fine to very fine sands, and, in some intervals, calcareous (Fig. 5G). They display faint planar, wavy, and ripple lamination, and rarely cross lamination being commonly disturbed by thorough bioturbation.

InterpretationThe general fining upward hierarchy of this assemblage of facies with erosive base and gradational top indicates its accumulation within channels. The abundance of argillaceous sandstone and sandy-to-silty mudstone facies with frequent bioturbation in the expanse of clean sand facies reflects a low rate of sedimentation from inconsistent bed and suspension loads. The presence

of flaser- and lenticular-lamination with ripple-lamination substantiates fluctuating current strength and sand-mud supply. The rapid upward change in facies from sands occasionally with reworked mudstone clasts to argillaceous sand and/or sand/silty mudstone suggests intermittent short-lived strong flows followed by an abrupt starvation in coarse clastics supply. Such a restriction in water circulation and related stressed ecological condition is evident by low faunal diversity and dwarfed/delicate nature of the preserved bivalves and gastropods. These depositional processes and conditions and related litho- and bio-facies commonly prevail or characterize abandoned fluvial and distributary channels or lacustrine/bay crevasse channels (Miall 1995).

FA-3: Crevasse Splays AssociationDescriptionThis association (10 to 30-ft thick) occurs commonly in S2A member and occasionally in Mid Shale. It is well developed in the southern sector of the study block where it builds most of S2A succession (30-ft thick); while in the northern sector, it intertongues and rests below the active channel assemblage (FA1), except, in some wells, changes to abandoned channel association (FA2). The FA3 has commonly a sharp erosive top and a transitional base into lacustrine or bay mudstone (FA5). It starts with faint-laminated and bioturbated bioclastic sandy to silty mudstone grading up to faint-laminated and bioturbated bioclastic argillaceous sandstone/calcareous sandstone and occasionally with subordinate interbeds of horizontal- and cross-laminated relatively clean sandstone displaying together coarsening upward stacking pattern (Fig. 5H). The facies are mostly light gray to greenish gray and fossiliferous with small-sized bivalves and gastropods. Bioturbation with calcareous cementation is also a common feature, especially in its middle and upper parts.

InterpretationThe silty and sandy mudstone dominating composition with intensive bioturbation characterizing the lower interval of this association indicates a deposition under low-energy shallow- water environment. The scarcity and low diversity of fauna with bioturbation suggests a low rate of sedimentation and restricted water circulation. On the other hand, the gradual upward coarsening in grain size, decrease in mud content, and occurrence of faint-laminated and bioturbated argillaceous sandstone with interbeds of clean sandstone facies in the upper part indicates a deposition from a short-lived high-energy depositional event such as flash floods. Accordingly, this association is considered as prograding crevasse splays in the margin of interdistributaries lake or bay.

FA-4: Channel Top AssociationDescriptionThis association terminates commonly the upper part of S1A and S2A members with a thickness ranging between 2 to 5 ft. It forms also S1 shale and S2 shale members as well as thin units separating between stacked active- or abandoned-sandstone channels (Figs. 4A and 5A). In most wells, it has invariably gradational base, sharp desiccated top, and subtle cleaning/coarsening up gamma-ray log pattern, which is, in fact, related to upward enrichment in carbonate cementation (Figs. 5I and 5J). It consists essentially of

INTEGRATING CORE-CALIBRATED IMAGES WITH OPENHOLE LOGS TO CHARACTERIZE FORMATIONS

9

Fig. 5. A and B) High-resolution imaged-based facies log of S1A and S2A members; their facies successions consist essentially of abandoned channel (FA2) and active channel (FA1) facies associations with subordinate intervals of FA4 (channel top/overbank). C) Core-calibrated image shows the massive to bioturbated bioclastic argillaceous sandstone facies of FA2 and FA3. D) Faint-laminated and bioturbated sandy/silty mudstone of FA2, FA3, and FA5. E and F) Rippled- and flaser-laminated argillaceous sandstone and sandy limestone of FA2 and FA5. G) Faint-laminated and bioclastic calcareous mudstone facies containing delicate bivalves and dwarfed calcitic molds. H) High-resolution imaged-based facies log of S2A member; its succession consists essentially of crevasse splay association (FA3) and active channel association (FA1) with subordinate intervals of FA4 (channel top/overbank) and FA5 (lacustrine mudstone). I and J) Nodular form, desiccation cracks with infiltrated terra rosa and brecciation characterize the sharp carbonate cemented top of S1A member. K) Massive to faint-laminated mudstone and calcareous mudstone dominating in FA5. Key for facies symbols is shown in Table 1.

interbedded argillaceous sandstone (LFTs-4 and 5), sandy-to-silty mudstone (LFT-8), and nodular-bedded calcareous mudstone (LFT-11). The beds are apparently massive to actually faint-laminated and thoroughly bioturbated. Traces of cross lamination are also picked, but uncommon. Due to intensive carbonate cementation, the top part (1 to 3-ft thick) is almost patchy colored from whitish gray to reddish white, nodular-bedded and brecciated into polygonal fitted rubbles with sometimes infiltrated terra-rosa and vague root burrows (Figs. 5I and 5J).

InterpretationThe interbedded argillaceous sand and muddy composition with essential faint planar lamination and through bioturbation indicates a low rate of

sedimentation under fluctuating current strength and alternating sandy bed load and muddy suspension load. The occurrence of this unit with a gradational boundary above channel fill sandstone suggests it accumulated in the abandoned stage of the channels as top channel fill that was subsequently exposed to subaerial conditions and subjected to pedogenesis giving calcrete profile.

FA-5: Lacustrine Fill AssociationDescriptionThis association constitutes the entire succession of Cap Shale (10.7 to 37.2-ft thick) and Mid Shale (1018-ft thick) members, and in some wells, builds also S2 shale unit. It consists mainly of interbedded planar-laminated mudstone, faint-laminated

calcareous mudstone, and bioturbated mudstone (Fig. 5K). In Mid Shale member, subordinate interbeds of ripple- and flaser-laminated sandy mudstone and argillaceous sandstone, cross-laminated argillaceous sandstone, and occasionally horizontal-laminated sandstone occur and form with the encompassing mudstone facies either coarsening or fining upward stacking patterns. The mudstone rock is almost gray to greenish gray, silty to clayey in size, sandy in parts, and bioturbated in some intervals.

InterpretationIn most wells, the overall fine grain size, mud-supported fabric, and prevalence of planar lamination with bioturbation indicate suspension-load sedimentation in low-energy shallow-water environment. The nearly absence of fauna suggests a restricted water circulation and probably stressed ecological conditions. On the other hand, the occurrence of rippled-, flaser-, and cross-laminated argillaceous sandstone and sandy-to-silty mudstone with horizontal-laminated sandstone interbeds reflect deposition from alternating traction- and suspension-load via short-lived strong currents or flash floods. All of these processes and products fit many of the depositional attributes denoting interdistributaries shallow lakes or bay in which the overall quiet sedimentation of the principal muddy facies was sporadically interrupted by incision of localized crevasse channels building crevasse splays and/or abandoned crevasse channels.

Channel Architecture and PaleogeographyThe above sedimentological analysis demonstrated that the Mid-Miocene clastics were accreted across a fluvial-lacustrine plain–mainly in active and abandoned channels, proximal overbanks, and lacustrine flood plains. Controlled by the Mid-Miocene relative changes in nearby sea (base) level and in sediment supply, the lateral shifting and vertical overlapping of these environments developed two nearly identical depositional cycles representing S1 and S2 rock units (Fig. 3). Each cycle began with erosional surface (sequence boundary) and terminated by lacustrine mudstone unit; Cap Shale and Mid Shale, respectively (Fig. 3). These mudstone units are widely distributed and represent the sedimentation products during the maximum landward shifting of aforementioned fluvial-lacustrine facies belts. Each of S1 and S2 cycles comprises two distinct reservoir-forming sandstone intervals (S1A, S1B and S2A, S2B) that were developed by different channel systems with different stories and styles. Discriminating the style and channel dimensions;

10

Fig. 6. A) Resistivity image shows the three facies associations (FA1, FA2, and FA4) and its facies components building S1A member. B-D) Examples of the common variation in both of thickness and facies types of the three associations. The key of facies symbols is shown in Table 1.

Fig. 7. N-S stratigraphic correlation panel leveled on top S1A member shows the general S-ward thickening of S1A member and the distinct lenticular geometry of active and abandoned channels in two superimposed channel belts. Notice the limited occurrence and restricted extension of active channels (yellow) in the lower belt, and the longhorn steer-like geometry of the active channels in the upper belt.

YZ-062X YZ-062X YZ-064X YZ-072X YZ-007X YZ-100XN S

Fluvial/distributary channel sandstone

Lake or bay mudstone

Abandoned channels

Top channel/overbank

Caliche

20 ft

0.0

Horizontal distances between wells are not to scale

0.0 1.0 Km

especially width (Cw), depth (Cd), and channel-belt width (Cbw), in addition to paleoflow trends, are crucial for correct correlation of fluvial sand bodies and reconstruct its paleogeography and spatial distribution.

Several techniques and empirical equations were employed to discriminate fluvial channel pattern and determine their dimensions (e.g., Schumm 1972; Ethridge and Schumm 1978; Miall 1976; Galloway and Hobday 1983; Bridge and Tye 2000; and Khan and Tewari 2011). The following is a perception of the channel system; its dimensions and paleoflow trends, and a tentative reconstruction of the paleogeographic setting of the study field area during the deposition of each individual of Fars reservoir members. The channels’ widths and depths are estimated according to the methods applied by Bridge and Tye (2000) and Khan and Tewari (2011), which was based on the calculated means of medium-scale cross-set thicknesses. The cross-set thickness and paleoflow trends are precisely determined from the azimuthally oriented resistivity images. However, the dimensions of S2A sand bodies could not be estimated where there were too little cross sets available to be applied.

S1A Channel SystemS1A is the topmost reservoir-hosting member in the study block. It extends with a thickness ranging from 19.6 to 44.2 ft with a gradual decrease due NW. Its facies sequence comprises three facies associations

including: lower abandoned sand-mud channel, middle active sandstone channel, and upper overbank/channel top sand-mud with calcrete (Fig. 6A). From well to another, these associations pinch and swell laterally in the expanse of each other giving a distinct lenticular geometry (Figs. 6 and 7). The variation in thickness is in part due to a truncation of the basal association (FA2) by the overlying active channel association (FA1), and in other parts related to fractional abandonment of the middle active channels. The three associations suffer also a lateral change in facies, especially the lower one, which in most wells has poor reservoir quality facies, except in the central part of the study northern

sector where it attains its maximum thickness (up to 10 ft), and changed to active channel association with good reservoir quality (Figs. 6B, 6C, and 7). The middle active channel association that forms the main reservoir body of S1A member extends with a thickness ranging between 25 ft (in the middle part of the sector) and 10 ft (in the northwestern corner). It either occurs as a single very thick sandstone body or splits into two small fining-upward bodies separated by thin intervals of argillaceous sandstone and/or mudstone. However, in some wells, its lower body is changed from clean sand facies to poor-quality reservoir argillaceous sandstone due to abandonment (Fig. 6D).

INTEGRATING CORE-CALIBRATED IMAGES WITH OPENHOLE LOGS TO CHARACTERIZE FORMATIONS

11

Table 2 – Estimated S1A Channel Depths and Widths Based on the Empirical Equations of Miall (1976) and Allen (1968 and 1970). B) Estimated S1A Channel-Belt Widths Using Bridge and Tye (2000) Equations

123456789101112131415161718

0.60.41.51.60.71

0.90.70.30.70.80.40.41.20.40.40.30.4

0.180.120.460.490.210.300.270.210.090.210.240.120.120.370.120.120.090.12

TOTALAVERAGEMAXIMUMMINIMUM

3.840.210.490.09

2.445.691.05

2.936.831.26

184.60430.1679.38

SetNumber

(RB1)

SetThickness

{H}_(ft)

SetThickness

{H}_(m)

Depth ofChannel

Dc

Depth ofBankfull

Dbf

Bankfull WidthWbf

Data measured from XRMI images

Channel depth based on equations

of Miall (1976)

Channel widths based on equations of Allen

(1968 and 1970)

Dept

h of

Cha

nnel

= (H

eigh

t of d

une)

/ 0.

086

Dep

th B

ankf

ull D

bf =

CC1 *

D c

Wid

th o

f Cha

nnel

Wc=D

bf*

1.5*

42

hm

= 6

* (s

/1.8

)

d =

hm

*6

d =

hm*1

0

Cbw

= 5

9.9

d1.8 (m

in)

Cbw

= 1

92 d

1.37

(max

)

Channel-belt dimensions based on equations of equation of Bridge and Tye (2000)

Dune mean height (hm)

Channel Flow Depth (d) Channel-belt Width (Cbw)Set

Thickness (s) in

metersMinimum MinimumMaximum Maximum

0.180.120.460.490.210.300.270.210.090.210.240.120.120.370.120.120.090.12

0.70 4.20 7.00 740.00 2761.00 3.84

BA

The well-to-well correlation of S1A member revealed that its facies associations represent the depositional products of two superimposed channel belts (Figs. 7 and 8). The lower belt comprises mainly abandoned channels with a limited occurrence of active channels in the central part of the study block (Fig. 8A), while the upper belt was occupied mainly by active channels with minor abandoned ones (Fig. 8B). In both belts, the common lenticular geometry of active and abandoned channel associations, frequent internal scouring, and limited preservation of overbank/flood plain facies reflect the continuous lateral shifting of the active channels almost via branching and/or abandonment, which was more frequent in the lower belt (Fig. 8A). The general small thickness (5 to 10 ft) of the bankfull in-channel sandstone facies, except in

the central portion reaching up to 25-ft thick, indicates that these channels were in most places shallow with the deepest ones occupied the central area. This is confirmed by the estimated depths of these channels (Table 2A and B), which amounts bankfull depths ranging between 1.3 and 6.8 m (using Miall’s equation 1976) and from 4 to 7 m (applying Bridge and Tye’s equation 2000). The calculated bankfull widths of those channels ranges between 79 and 430 m, and the entire channel belt width swings between 740 and 2760 m in maximum width (Table 2). All of aforementioned qualitative and quantitative attributes fit well with low sinuous distributary or steer head channel system described by Kjemperud et. al (2007). The paleocurrents directions derived from cross strata indicate principal NW to NE paleoflows in those distributary channels

(Fig. 7) with subordinate SE to SW trends related to backflow currents that accompanied scouring and fill processes.

S1B and S2B Channel SystemsThe S1B (30 to 50-ft thick) and the upper portion (55 to 90-ft thick) of S2B members are among the principal oil-bearing reservoir intervals of the study Mid-Miocene succession (Fig. 3). They have nearly similar depositional stories, and comprise almost identical facies types and facies organization. The architecture of their alike depositional elements seems to be duplicated with time, and therefore treated here together. Each reservoir unit is delimited by two marker shale intervals with invariably upper gradational contact and lower truncating boundary. Their facies succession consists ultimately of active channel facies assemblage with subordinate intervals of overbank or channel top association (Fig. 9). Lacustrine mud-dominating assemblage shares occasionally in the succession of S2B, but has a very limited lateral distribution. The chief active channel association forms in most wells two or three (as in S2B) erosively based and fining upward sandstone bodies of 5-ft up to 25-ft thick being commonly separated by scouring surfaces with or without lag gravels or by thin intervals (up to 5-ft thick) of channel top association (Figs. 9A-C). The latter is laterally discontinuous with pinch and swell geometry being related to its scouring by the overlying active channel (Fig. 10). In contrary, the in-channel sandstone bodies are laterally consistent, and extend in sheets without a drastic change in thickness or facies, except in few wells in S2B member where the middle sandstone body is missed and substituted by lacustrine mudstone (Figs. 9D and 10). The sandstone sheets are dominated with stacked sets and cosets of high-angle cross stratifications with frequent internal scouring and reactivation surfaces, as well as intervals possessing horizontal- and low-angle crossbeds. The high-angle cross strata have mostly dip magnitudes ranging from 10° up to 30° in directions swinging commonly from NW to NE through N, and less commonly due W, SE, and SW (Fig. 11).

The well-to-well correlation of the prevailing active channel and the uncommon overbank associations demonstrated that, in upper S2B member, they represent the depositional products of three superimposed fluvial-braided channel belts while in S1B, they were produced in two similar overlapped braided belts (Figs. 9 and 10). The braided style of those five belts is evident from the common sheet-like lateral geometry of the sandstone bodies, abundant internal scouring and reactivation surfaces, and the discontinuity of the thinly preserved overbank/channel top association. These attributes reflect that

Fig. 8. A and B) Tentative paleogeography of the study block displaying the geometry and paleoflow trends of the active and abandoned channels in the lower channel belt (8A) and upper channel belt (8B) during the deposition of S1A member.

Paleoflow

Active distributary channel

Abandoned channels

Lascustrine/bay fill

Abandoned channel fill

No drilling data

Paleoflow

Active distributary channel

Abandoned channel

Lascustrine fill

In-channel fill/bars

No drilling data

12

Fig. 9. A and B) High-resolution imaged-based facies logs of S1B member consisting ultimately of active channel sandstone assemblage (FA1) forming two erosively based thick bodies separated by scouring surface (as in A) or by thin interval of channel top association (as in B). C) Facies sequence of S2B member consisting mainly of active channel sandstone association forming three erosively based bodies separated by thin interval of channel top association (FA4). D) An example of the few wells in which the middle active channel association of S2B member is missed and replaced by lacustrine mudstone assemblage (FA5). The key of facies symbols is shown in Table 1.

Fig. 10. NW-SE stratigraphic correlation panel leveled on top S1A member shows the sheet-like geometry of the active channel sandstone associations separated by discontinuous lenticels of channel top facies assemblage, and form together two superimposed braided channel belts in S1B member, and three overlapped belts in S2B member.

NW SE

YZ-054X YZ-056X YZ-057X YZ-062X YZ-057X YZ-070XYZ-064X YZ-066X YZ-069X YZ-100X

Fluvial/distributary channel sandstone

Lake mudstone

Lake or bay splay

Top channel/overbank

Abandoned channel

20 ft

0.0

Horizontal distances between wells are not to scale

0.0 1.0Km

the individual channels in those belts were truncating each other and eroding their short-lived banks via continuous lateral shifting and/or branching around in-channel sand bars under short-term fluctuations of discharge. They left behind a continuous sand sheet of laterally amalgamated in-channel bars and channel fills delimited from top and bottom in some wells by discontinuous lenticular remnants of channel top/overbank and in other wells by scouring surfaces. The lateral lap-outs or terminations of the sandstone sheets are almost ill-defined except in the middle channel belt of S2B member, where in few wells the sand sheet is missed and replaced by a comparable thickness

of lacustrine mudstone, which suggests that in this belt, the channels were relatively narrower and more sinuous or of distributary nature bifurcating around interchannels lakes.

The set thickness of cross strata measured from S1B and upper S2B members ranges from 12 up to 60 cm with an average of 26 cm. Based on these values, the estimated bankfull depths of their channels, in which the dunes forming those crossbeds were migrated, varied between 1.7 m and 8.5 m (using Miall’s equation 1976) and from 5.2 to 8.7 m (applying Bridge and Tye’s equation 2000), and their bankfull

widths extended from 107 to 536 m while the entire channel belt widths were between 1164.8 m and 3719 m (Table 3). The paleocurrents directions derived from cross strata indicate that those channels were running generally from S to NW and NE through N with local backflows due SE and SW (Fig. 11).

S2A Channel SystemS2A member measures a thickness ranging between 16 to 32 ft, and shows clear lateral change in facies types and facies hierarchy. Its facies sequence comprises four main facies associations: active channel (FA1), crevasse splay (FA2), abandoned channel

INTEGRATING CORE-CALIBRATED IMAGES WITH OPENHOLE LOGS TO CHARACTERIZE FORMATIONS

Uppe

r bod

yLo

wer

bod

y

13

Table 3 – Estimated Dimensions of Active Fluvial Channels and Channel Belt of S1B and S1B

Data measured from XRMI images

Channel depth based on

equations of Miall (1976)

Channel depth based on equations of Allen

(1968 and 1970)

Channel-belt dimensions based on equations of Bridge and Tye (2000)

Total

Average

Maximum

Minimum

Set Thickness

{H}_(m)

5.64

0.26

0.61

0.12

Depth of Channel Dc

2.98

7.09

1.42

Depth of Bankfull

Dbf

3.58

8.51

1.70

Bankfull Width

Wbf

225.31

535.88

107.18

Channel Flow Depth (d)

Minimum

5.2 m

Maximum

8.7 m

Minimum

1165 m

Maximum

3719 m

Channel-belt Width (Cbw)

(FA3), and channel top association (Fig. 5B and H). However, these assemblages never stack together in one sequence, but in most wells only two or three coexist in the expanse of the others. The active channel association forms the main reservoir interval of this member. It has erosive sole, gradational top, and extends laterally as a lenticular body that swells and pinches on the expanse of the underlying associations (FA2 or FA3). It is best developed (up to 20-ft thick) in the middle part of the northern sector while being

missed in the southern sector, and whenever exists, it commonly occupies the upper half section, and in few wells, the upper and middle intervals or even the entire section of the member (Fig. 12A). The obvious lateral pinching and dying out of this association, and its general smaller thickness (5 and 10-ft thick) relative to those of S1B and S2B, suggest that the S2A channels were narrower, shallower, and more branched. The crevasse splay and abandoned channel assemblages extend also as lenticular bodies with a noticeable

thickness variation being intimately related to its truncation by the overlying active channel sandstone (Figs. 10 and 12B). They commonly substitute each other in occupying the lower half section of the member, except in very few wells where being missed and replaced by active channel associations (Fig. 12A).

The well-to-well correlation of S2A member revealed that its four facies associations represent the depositional products of two superimposed fluvio-dominated upper delta plains (Figs. 10 and 13). The lower plain comprises mainly abandoned distributary channels and lacustrine or bay splays with a limited occurrence of active distributary or crevasse channels in the central part of the study block, while the upper belt was occupied mainly by active distributary channels with minor abandoned ones and crevasse splays. In both belts, the common lenticular geometry of active and abandoned channel associations with good preservation of lacustrine fill/splay facies reflect a frequent bifurcation of the main active distributary channels into smaller and shallower crevasse channels that either were debouching its loads into adjacent lakes or bays forming crevasse deltas or were suffering abandonment, which was more common in the lower belt. As mentioned before, the dimensions of S2A sand bodies could not be estimated where there were too little cross sets available to be applied.

ConclusionsThe shallow Mid-Miocene clastics in the study field area host viscous oil; its trapping and distribution were ultimately controlled by vertical and spatial dispersal pattern of specific facies assemblage and its diagenetic alterations. These clastics were accreted across a fluvial-lacustrine plain–mainly in active and abandoned channels, proximal overbanks,

Fig. 11. Tentative paleogeography of the study block displaying the geometry and paleoflows of the active braided channels during the deposition of S1B and S2B members, respectively.

Paleoflow trend

Active fluvial channel

Proximal overbank/ lacustrine fill facies

In-channel fill/bars

No available data

S1B member S2B member

Paleoflow trend

Active fluvial channel

Proximal overbank/ lacustrine fill facies

In-channel fill/bars

No available data

Fig. 13. Tentative paleogeography of the study block displaying the geometry and paleoflows of the active distributary channels during the deposition of S2A members.

Paleoflow trend

Active distributary channel

Abandoned distributary

In-channel fill

Lacustrine or bay-fill

No available data

Fig. 12. A) High-resolution imaged-based facies log of S2A member consisting ultimately of active channel sandstone assemblage (FA1) with thin interval of channel top association. B) Facies sequence of S2A member consisting in its lower half of crevasse splay, and in its upper half of active distributary channel assemblage with channel top association.

Mid Shale

S2 Shale

S2 Shale

Mid Shale

S2A

14

Khalid Ahmed currently works for KOC as a TPL specialist petrophysicist in the Heavy Oil Group. A career petrophysicist with over three decades of experience, Khalid joined KOC in 2002, after successfully serving ONGC

for 21 years. He started his career as a field engineer and then moved into the role of petrophysicist, working both onshore and offshore with clastics and carbonates. Khalid has worked with the KOC Heavy Oil Group since its inception in 2007. He is the author of many technical publications and papers, and is on the technical editor team of SPE’s Peer Review Committee for various technical journals. Khalid has cochaired many SPE events and delivered a keynote address at an SPE-ATW. He holds an MSc degree in physics and is an active member of SPE, SPWLA, and AAPG.

Hasan Ferdous has worked for the past five years as a heavy oil development geologist in the Heavy Oil Group for Kuwait Oil Company (KOC). Hasan has been involved in various heavy oil development projects in

Canada for the past 20 years, looking into various attributes of reservoir characterization, geomodeling, and reservoir management. Concurrently, he also worked as a consultant in developing unconventional and heavy oil fields globally. Hasan has a BS degree with honors in geology, an MS degree in petroleum geology, and a PhD in Bakken reservoir characterization and reservoir management from the University of Saskatchewan, Canada. He is a member of AAPG, CSPG, CHOA, and SPE. Hasan has authored several technical papers.

Pradeep K. Choudhary is a senior geologist for Kuwait Oil Company. He holds a BSc degree in geology and received his MTech (applied geology) from IIT, Roorkee, India in 1982. Pradeep began his geologist career

in 1983 for ONGC, where he served for approximately 24 years in several managerial positions. Since 2008, Pradeep has worked with the KOC Heavy Oil Group, where he has specialized in reservoir characterization and sedimentological/geological aspects for heavy oil development of unconsolidated sand reservoirs. His present responsibilities include the development geology aspects of a major shallow unconventional oil reservoir in Kuwait. Pradeep has published more than 12 research papers globally.

Faisal Abbas started his career as a field geologist for Kuwait Oil Company in 2002. Since then, Faisal has been supervising drilling and operational activities in the heavy oil field located in the northern part of Kuwait. During

this time, he has been an integral team member in drilling and completing very shallow depth horizontal wells in an unconsolidated heavy-oil sandstone reservoir. Faisal has also been heavily involved in integrated reservoir studies involving sequence stratigraphy, reservoir characterization, and assisting in static model building of this reservoir, as well as heavy oil field risk assessment and uncertainty management. He holds a BS degree in geology from Kuwait University in 2001. Faisal has been a member of SPE since 2008.

Waleed Al-Khamees is an experienced reservoir engineer who is currently the team leader of the Heavy Oil Field Development Team (North Kuwait) for Kuwait Oil Company. He leads a multidisciplinary team of 30

professionals charged with the strategic development of several heavy oil fields in the North Kuwait asset. From 2010 to 2012, Waleed served as the chairman of the SPE Kuwait Section. He holds a BS degree in petroleum engineering and an MS degree in oil reservoir management from Kuwait University. Waleed is an SPE certified petroleum professional, General Management Program (GMP) certified from Harvard University, and attended Cornell’s Project Executive Program.

Adly Helba is a geoscience advisor for Halliburton focusing on geological interpretation of resistivity images in both single- and multiwell projects in Saudi Arabia. Prior to joining Halliburton, Adly served as an

assistant professor in the Geology department at Cairo University. He has also worked as a consultant for several Egyptian oil and service companies. Adly received his BSc degree in geology from Cairo University in 1981, his MSc degree in Cretaceous carbonate sedimentology in 1987, and his PhD degree in Paleozoic clastics sedimentology in 1991 from Cairo University.

Adham Osman has been a Formation and Reservoir Solutions (FRS) consultant II for Halliburton Saudi Arabia since 2014. In this role, Adham works as a geologist and imaging specialist performing imaging

processing, structures, and sedimentological image interpretation. Prior to joining Halliburton Saudi Arabia, he worked as a technical professional/well log analyst and

FRS consultant to Egypt. He has also held some academic roles at Cairo University in the Geology department and worked as a teaching assistant at the American University in Cairo. Adham holds a BSc degree in geology, as well as an MSc and PhD degrees in structural and engineering geology from Cairo University.

Wael Ali is a consultant II in Halliburton’s Formation and Reservoir Solution (FRS) group where he currently serves as a team leader of the Reservoir Description Center. Wael has almost 14 years

of industry experience. He started his career as a mud logging geologist with Sperry Drilling and continued up to surface data logging (SDL) operations coordinator before joining Halliburton Wireline and Perforating/FRS in 2009. Wael has worked as a geologist and imaging specialist performing imaging QC, processing, structure, and sedimentological interpretation. He is a coauthor of many technical publications and papers. Wael holds a BSc degree in geology and chemistry from Cairo University.

Mohsen Abdel Fatah is a senior FRS advisor for Halliburton Egypt. Mohsen has more than 30 years of academic and industry experience, specializing in sedimentological and sequence stratigraphic studies. His expertise

spans image interpretation; core sedimentology; clastics and carbonates; petrography, mineralogy, and diagenesis; core analysis; reservoir geology; sequence stratigraphy; depositional systems; and stratigraphic techniques. Mohsen holds a BSc and MS in geology from Cairo University, Egypt, and a PhD in geology from the University of Naples, Italy. He is an active member of AAPG, SPE, SPWLA, and IAS, as well as several other societies. Mohsen is a frequent technical paper author and coauthor.

Rafael Vasquez is currently the Halliburton Formation and Reservoir Solutions (FRS) manager for the Northern Gulf, residing in Kuwait. He has 43 years of experience in the wireline and perforating business,

having performed management jobs in technical, operations, marketing, training, and geoscience across four continents. In addition, Rafael holds a US patent on modern pumpout formation testing. He’s a member of SPWLA and SPE, and has coauthored several papers.

Authors

and lacustrine flood plains. Their lateral shifting and vertical overlapping in response to Mid-Miocene relative changes in sea level and sediment supply developed two nearly identical fluvio-lacustrine cycles or sequences (lower S2 and upper S1). Each sequence began with erosional surface and terminated by widely distributed lacustrine or bay mudstone of Mid Shale and Cap Shale members that formed seals and represented the sedimentation products during the maximum rise of nearby sea

level. Each fluvio-lacustrine sequence started its lowstand accretion by two or three superimposed braided channel belts (1164.8 to 3719 m in width and 5 to 8.7 m in depth), in which the best reservoir sand facies were developed as active in-channel sandbars/fill forming laterally amalgamated and almost vertically connected sand sheets of S2B and S1B members. With a rapid rise in nearby relative sea level and onset of transgressive sedimentation, the lowstand braided channel belts were overlapped

INTEGRATING CORE-CALIBRATED IMAGES WITH OPENHOLE LOGS TO CHARACTERIZE FORMATIONS

by other superimposed depositional belts of upper fluvio-dominated delta plains (740 m and 2760 m in width). These deltaic plains were dissected and drained by active and abandoned distributary channels (2 to 7-m deep) with crevasse branches. The filling of the active distributary channels produced the good-quality reservoir sands of S2A and S1A members, but with elusive shoestring or lenticular extensions and lateral change in both thickness and facies.

15

AcknowledgementThe authors would like to thank Kuwait Oil Company and Kuwait Ministry of Oil for permission to publish this paper. Particular gratitude is expressed to all our colleagues in KOC and FRS, Halliburton, Egypt for their encouragement and technical support in every stage of this study.

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16

USING CORE AND LOG DATA TO CHARACTERIZE WETTABILITY

Subsurface Fluid Characterization Using Downhole and Core NMR T1T2 Maps Combined with Pore-Scale Imaging TechniquesMargaret Lessenger, Newfield; Dick Merkel, Denver Petrophysics; Rojelio Medina, Sandeep Ramakrishna, Songhua Chen, Ron Balliet, Halliburton; Harry Xie, Core Laboratories; Pradeep Bhattad, Anna Carnerup, Mark Knackstedt, FEI-Lithicon This paper was prepared for presentation at the SPWLA 56th Annual Logging Symposium held in Long Beach, California, USA, July 18-22, 2015. Copyright 2015, held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors.

AbstractCharacterization of the subsurface fluid types, porosity, saturations, and wettability are critical for understanding the type and volumes of fluids that will be produced during primary completions and secondary waterflood recovery. The oil reserves within the Green River Formation of the Uinta Basin (Utah, USA) in the Greater Monument Butte Unit (GMBU) have variable fluid volumes, saturations, and wettability. Within a potential pay section of over 2000 ft are over 20 defined producing sandstone reservoir intervals within the Green River Formation with variable depositional environments, mineralogy, and rock quality. Traditional core analyses for saturations and wettability are time consuming and expensive because of variable reservoir properties within discontinuous sands and high-paraffinic oil containing asphaltenes and resins. Similarly, the variable wettability complicates standard analyses of NMR data for fluid type and volume estimations.

Newfield has approximately a dozen wells with nuclear magnetic resonance (NMR) T1, T2, and diffusion data in the producing section of Monument Butte Field. We have identified patterns of NMR, dielectric, and standard triple-combo log data that are associated with differences in estimation of clay-bound water volumes from NMR and XRD data. We present results from pore-scale imaging, NMR core-flood experiments, USBM measurements of wettability, and 2.5D inversion of NMR data used to characterize the variable wettability of GMBU sandstone reservoirs.

We found that the sandstone reservoirs are mixed-wet at the micro- and macropore scales, including presence of oil-wet clays. Mixed-wettability complicates estimation of fluid types and volumes from NMR data using standard interpretation techniques. An analysis protocol involving pore-scale imaging, core-flood NMR experiments, and 2.5D NMR processing and analysis permit reduction of interpretation ambiguity of the NMR data.

IntroductionGreater Monument Butte Field (GMBU) is located in the Uinta Basin in Utah, USA (Fig. 1) and produces from highly discontinuous tight lacustrine sandstones within the Green River Formation (Burton et al., 2012; Ramakrishna et al., 2012). Paraffinic Green River oil is semisolid at surface conditions because of the temperature-dependence of its viscosity. This property of the oil complicates core analyses, which must be run at reservoir temperature. Green River reservoir intervals could contain hydrocarbons in the solid, liquid, and gas phases. Reservoir sands pose challenges in interpreting log data to determine hydrocarbons in-place and reservoir-flow characteristics. GMBU sand reservoirs are highly variable in rock quality, mineralogy, clay types and volumes, framework grain composition, authigenic minerals, and wettability (Ramakrishna et al., 2012; Lessenger et al., in press). Advanced logging suites including NMR

Paper 2

and dielectric have been useful in separating solid from liquid phases and estimating oil saturations (Ramakrishna et al., 2012; Lessenger et al., 2013).

Variable wettability has posed a particularly difficult problem in characterizing reservoir-flow properties. Sandstone reservoirs range from water-wet to strongly oil-wet. Variable wettability controls the types and volumes of produced fluids and strongly controls residual oil saturations (Merkel and Lessenger, 2014). GMBU-produced oil has abundant polar hydrocarbon components with 6% or more asphaltenes and 14% or more resins. Carbonate lithic framework grains and authigenic Fe-calcite and Fe-dolomite are abundant, and are known to be oil-wet in reservoirs (Lessenger et al., 2013). The NMR log responses within GMBU are affected by the highly variable wettability, leading to ambiguous interpretations of those data because of changes in surface relaxation. In combination with pore-scale imaging, we designed a series of core-flood NMR experiments to reduce ambiguity and better characterize the effect of wettability. In this paper, we show results of core-flood experiments analyzed with NMR T1, T2, and T1T2 measurements and integrated with log NMR and dielectric data, XRD, pore-scale imaging, and USBM measurements.

GMBU Log and Core Data MismatchSand reservoirs in GMBU vary in quality as determined by porosity, permeability, capillary pressure data, and waterflood response (Lessenger et al., 2015). Variations in clay volumes, types, and pore morphology are associated with rock-quality types as determined by XRD and SEM imaging. Better-quality reservoir sands have more chlorite and very little mixed-layer illite-smectite (I/S). Authigenic chlorite rosettes line large, open macropores (Fig. 2A). In poorer quality reservoir sands, I/S is more abundant than chlorite, and I/S is pore-bridging, reducing original permeability (Fig. 2B).

We developed a multimineral and resistivity-based saturation model in GMBU calibrated to core XRD, routine core analyses, and log NMR and dielectric data. These models are highly consistent with the exception of our estimation of clay-bound water. NMR T1 and T2 data measure clay-bound water volumes in T2 relaxation times less than 2.8 ms (Martin and Dacy, 2004). Based on the cation- exchange content (CEC) of clay minerals, we calculate estimated clay-bound water volumes (VCBW) from XRD (Dick Merkel, personal communication, 2012). Reservoir sands in GMBU typically show a mismatch in these two measurements, even accounting for different measurement volumes.

Fig. 1. Location of the Uinta Basin and the study area, GMBU Field (modified from Burton et al., 2012).

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Fig. 2. SEM of pores in a higher quality reservoir sand A) and a poorer quality reservoir sand B). In (A), authigenic chlorite (CHL) forms rosettes in open macropores. I/S (I/S) is absent or a minor constituent. In (B), I/S is more abundant and bridges pores, reducing the macroporosity and permeability.

Fig. 3. GMBU log and core data in a sand with low VCBW in the reservoir sand. The T1 and T2 signal is high in the adjacent shale, but disappears abruptly in the sand (“T2 ARRAYS” and “T1 ARRAYS” tracks). XRD volume of wet clay (red dots) matches the mineral model (“MINERAL MODEL” track), and dielectric data match the saturation model (“FLUIDS” track). Laterolog resistivity is greater than 100 ohmm (“RESISTIVITY” track). VCBW from XRD (blue dots) and the mineral inversion is much higher than estimated from T1 and T2 data (“VCBW” track).

Fig. 4. GMBU log and core data in a sand with very low VCBW in the reservoir sand and very little measured with NMR. Tracks are described in Fig. 2. Sample 8 is at 4949 ft and marked with the horizontal blue line.

Fig. 5. GMBU log and core data in a sand with VCBW from NMR greater than estimated from XRD. Tracks are described in Fig. 2. Sample 34 is at 5492 ft and marked with the horizontal blue line.

Typically, NMR T1 and T2 data measure abundant VCBW in shales adjacent to sandstone reservoirs. But, this signal disappears abruptly in many sands (Fig. 3). We have a mineral model well calibrated to XRD that matches core volumes of wet clay from XRD as seen in Track 1 in Fig. 3. Even though clays are present in these sands, we often calculate more VCBW from XRD than observed in the NMR data. Laterolog resistivities are in the hundreds of ohmm, and dielectric data indicate measurable water volumes in the flushed zone. In other sands, VCBW from XRD and NMR is very low, but more closely matched (Fig. 4 Track 5). Laterolog resistivities are in the thousands of ohmm, and dielectric data measure very little water in the flushed zone in these sands. The reservoirs shown in Figs. 3 and 4 are associated with better rock quality. Reservoir

sands with poorer rock quality can have NMR VCBW much higher than estimated from XRD (Fig. 5). In these sands, laterolog resistivities range from the tens to hundreds of ohmm, and dielectric data measure water volumes that match the saturation model.

The association of patterns of mismatch between VCBW from NMR T1 and T2 data and log responses, such as estimated volumes of water from dielectric data and deep resistivities, led us to consider variable wettability as a source for these patterns (Figs. 3 to 5). Beginning in 2013, we started a series of log and core analyses to unravel these patterns and better understand and characterize wettability in the sand reservoirs.

Analysis ProtocolNMR Log Data

First, we analyzed the available NMR data in reservoir sands to identify recurring patterns of observed log responses. The NMR response depends on the volumes, types, and locations of reservoir fluids in the pore system. The NMR tool activation settings used in GMBU logging permit inversion for NMR T1, T2apparent, and T2intrinsic

18

data (Equations 1-3; Coates, et al., 1999). The contribution of each fluid to the NMR response depends on bulk, surface, and molecular diffusion properties:

1/T1 = 1/T1bulk + 1/T1surface (1)

1/T2apparent = 1/T2bulk + 1/T2surface + 1/T2diffusion (2)

1/T2intrinsic = 1/T2bulk + 1/T2surface (3)

where T1 is the measured longitudinal relaxation time of the pore fluid, T1bulk is the T1 relaxation time of the pore fluid as it would be measured with negligible surface effects, T1surface is the T1 relaxation time of the pore fluid resulting from surface relaxation, T2apparent is the transverse relaxation time of the pore fluid, T2bulk is the T2 relaxation time of the pore fluid as it would be measured with negligible surface effects, T2surface is the T2 relaxation time of the pore fluid resulting from surface relaxation, and T2 diffusion is the relaxation time of the pore fluid as induced by diffusion in the magnetic field gradient. T2intrinsic is the T2apparent relaxation time with T2diffusion removed. The bulk T1 and T2 relaxation times depend on the fluid type, temperature, and pressure. The surface T1 and T2 relaxation responses require that the fluid is in contact with a pore wall, and depend on the fluid and pore surface properties. Diffusion-induced T2 relaxation depends on the molecular diffusion coefficient, D, the magnetic field gradient G of the logging tool, and the tool activation settings (Coates et al., 1999).

Using simultaneous inversion of T1 and T2 data, T1T2 maps show the relationship between T1 and T2 attributes and have been used to identify fluid types and volumes in different pore sizes (Droeven et al., 2009). Wettability variations shift T1T2 map responses from interpreted water-wet standards (Freedman and Heaton, 2004; Flaum et al., 2005). Wettability modifies the intrinsic T2 relaxation times through surface effects because by definition a fluid that wets a pore surface is in contact with that surface. In a water-wet pore, the intrinsic T2 of water is reduced from the bulk T2 of water, and the intrinsic T2 of oil will be closer to the bulk oil response. Similarly, in oil-wet pores, the intrinsic T2 of oil is reduced from the bulk T2 of oil, and the intrinsic T2 of water will be closer to the bulk T2 of water.

Molecular diffusivity, D, depends on the fluid type, temperature, and pressure. For a given subsurface depth, gas has a higher diffusivity relative to water and oil. Except for very light oil, the diffusivity for oil is less than water and decreases with increasing oil viscosity (Mardon et al., 1996). Inversion for the

diffusion coefficient can result in significantly lower values if pores are very small and molecular diffusion is restricted (Coates et al., 1999). Measurements of diffusivity along with relaxation time by NMR are well-established methods to investigate fluid molecular motions (Mutina and Hurlimann, 2008). The combined presentation of T2 and diffusivity, often called a T2 -D map, provides additional means for hydrocarbon typing.

Modern NMR logging tools can acquire a large number of echo trains with a variation of the data acquisition parameters. In principle, a global inversion method (Sun and Dunn, 2005) or similar approaches can be used to invert all echo-train data together, and the result can be plotted in three dimensions to show the correlations between key NMR attributes: T1, T2, and D. In the most general form of NMR 3D inversion, the echo-decay functions are expressed by

(4)

where

i∙tEj is the time of the ith echo in an echo train

acquired with the jth interecho time tEj and

tWk is the kth wait time, and the echo signals are contributed from the lth sensitive volume in which the field gradient strength the spins experience is Gl. The solution E0,mnp can be obtained by solving the linear equation sets in the form of Equation 4. Often the nonnegative constraint of

EO,mnp ≥ 0 (5)

is imposed.

Directly solving the nonnegative E0,mnp is time consuming, and the large number of unknowns (M × N × P) may exceed the number of echoes, causing the underdetermined problem. In general, increasing the matrix size by a factor of 10 increases the computation time by a factor of 100. For a case of a large number of unknowns and a large number of data, the matrix can be very large, thus becoming expensive in computation time, especially because such inversion has to be performed at each depth interval, in the order of 4 to 8 samples/ft.

In order to improve the efficiency, a common practice is to apply a valid physical constraint based on the intrinsic T2 and T1 relationship of fluids in

porous media. In general, bulk T1 and intrinsic T2 of liquid water and light or medium viscous oils and hydrocarbon gases are substantially close to unity. When affected by the pore surface, the ratio of T1/T2 may increase somewhat, and generally, is in the range of 1 to 5. Heavy oil and tar, on the other hand, is also expected to have a higher T1/T2 ratio. For the range observable by NMR logging instruments, it is generally true that

(6)

When this constraint is applied, Equation 4 is rewritten as a modified 3D model, which is often called a 2.5D model,

(7)

where M’ is often a much smaller number than M, which significantly reduces the matrix size. The solution of the inversion of Equation 7 with the nonnegative constraint (Equation 5) is M’ number of T2-D maps; each with a distinctive R. Often, a single combined T2-D map is computed by co-adding, pixel-by-pixel, the intensity of the individual T2-D maps:

(8)

In the present study, the 2.5D inversion used M’= 3, and the R values are 1, 3, and 5, respectively.

Aside from the benefit of computational efficiency of using 2.5D, the comparison among the fluid distributions in the maps associated with different R (T1/T2 ratio) provides additional insight for helping to interpret fluid types and their wetting characteristics. We compare the correlations between molecular diffusion, D, and T2intrinsic for T1/T2 ratios of 1, 3, and 5.

Pore-scale Imaging

Concurrent with our analysis of NMR data, in2013 we initiated a study using pore-scale imaging to better characterize reservoir quality and wettability. Representative 3-mm subplugs from sands with different reservoir quality were imaged using micro-CT scanning in as-received, cleaned, and brine-saturated states. In the as-received state, hydrocarbon phases were doped with iodine to image the residual oil phase (Dodd

USING CORE AND LOG DATA TO CHARACTERIZE WETTABILITY

19

et al., 2014). After cleaning and drying, the plugs were imaged in a dry state to show available pore space. The plugs were then saturated with X-ray attenuating brine to map the connected porosity. 3D image registration and calculated differences in these successive images permit 3D measurement of as-received residual oil and connected porosity (Sok et al., 2010). Back-scattered SEM (BSEM) images and EDX mineralogy were registered onto the micro-CT images to associate the pore morphology, residual oil, and connected porosity to mineral phases and for comparison with micro-CT images of fluid phases (Golab et al., 2010; Knackstedt et al., 2011). SEM imaging of asphaltene deposition on mineral surfaces combined with EDX spot analysis was used to determine the wettability of specific minerals at the pore scale (Marathe et al., 2012).

NMR Core-flood Experiments

After identifying recurring patterns of NMR log data, we then designed a series of core-flood experiments combined with core NMR measurements to determine the fluid types and volumes represented by the identified patterns on log T1T2 map data. All experiments were conducted at a reservoir temperature of 150°F because of the high-paraffin content of Green River oil and measured bulk T2 variations with temperature.

• Measure T1, T2, and T1T2 of the core plug as received (native state).

• Flood the core plug with produced oil until reaching irreducible water saturation.

• Measure T1, T2, and T1T2 of the oil-flooded core plug.

• Flood the core plug with synthetic brine until reaching residual oil saturation.

• Measure T1, T2, and T1T2 of the brine-flooded core.

The native state NMR results simulate residual oil. The oil-flooded NMR results simulate NMR responses in a fully-charged reservoir. The brine-flooded NMR results simulate NMR responses measured in the flushed zone and are most comparable to downhole NMR log data.

NMR data of core samples were acquired using a 2MHz MARAN instrument (Resonance Instruments, Oxford, UK), with a reservoir condition Temco core holder (CoreLab Instruments, Tulsa, OK). The interecho spacing (TE) of the standard CPMG pulse sequence for T2 measurements is 0.3 ms. The Inversion Recovery pulse sequence with 31

incremental time-spacing steps was used for T1 measurements. The T1T2 map data were acquired using the combination of the above T1 and T2 measurement settings.

USBM measurement of wettability (Anderson, 1987) was done concurrently with the core floods. In addition, we ran XRD and routine porosity and permeability on the experimental core plugs. We measured the bulk T2 response of the produced oil at 150°F. Four sample plugs were carefully selected to match identified log patterns.

End-member Samples

In this paper, we present log data, pore-scale imaging, and core-flood NMR representing end-member log responses and rock quality. Results for the two plugs not discussed in this paper are intermediate to the two end-member plugs.

Core plug Sample 8 represents a high-quality reservoir sand with a log response indicating an oil-wet reservoir (Figure 4). Deep resistivity is very high, and dielectric measures very low water volumes. This sand has higher porosity and permeability (Table 1). XRD is typical for higher quality sands with predominately quartz, plagioclase, carbonates, chlorite, and illite (Tables 2 and 3). Log responses, core porosity, permeability, and XRD correspond to reservoir sands with pore morphology as shown in Fig. 2A.

Core plug Sample 34 represents a poor-quality reservoir sand with a log response indicating a more

Table 1 – Porosity and Permeability Data for Samples in the NMR Core-Flood Experiments. Core Porosity and Permeability is at Net Confining Stress

8 13.3 13.7 5.37

34 12.6 11.6 0.005

Sample NMR T1 Porosity (PU) Core Porosity (PU) Core Klinkenberg Permeability (md)

water-wet sand (Fig. 5). Deep resistivity is lower, and the dielectric data indicate variable water saturation that is higher than for plug 8. Porosity for poorer reservoir may be as high as high-quality reservoir, but permeability is much lower (Table 1). XRD indicates quartz, plagioclase, carbonates, illite, chlorite, and much higher volumes of I/S (Tables 2 and 3). Log responses, core porosity, permeability, and XRD correspond to reservoir sands with pore morphology as shown in Fig. 2B.

ResultsLog NMR T1T2 Patterns

When T1 and T2 data are collected, inversion of the combined T1 and T2apprent data result in T1T2 maps. Based on information about the estimated fluid types and fluid properties, T1T2 maps can be used to estimate liquid porosities of different fluid types located in different pore sizes (Droeven et al., 2009). The maps are plots of liquid porosity as a function of T1 and T2apparent relaxation times (Figs. 6 and 7). The vertical red line at T2apparent approximately equal to 30 ms is considered the approximate cutoff for bulk volume irreducible water (BVI). The horizontal line at elevated T1 is the “gas line.” Lines of equal ratios of T1 to T2 are the diagonal green and gray lines. The green line is at T1/T2 equal to one, and gray lines mark increasing ratios of T1/T2 (Coates et al., 1999).

The location of liquid porosity volumes measured on log T1T2 maps show consistent patterns associated with the discrepancies in estimated VCBW and reservoir quality. Better-quality reservoirs typically

Table 2 – XRD Data for Nonclay Minerals for Samples in the NMR Core-Flood Experiments

8 47.3 0.0 39.3 2.6 3.2

34 46.8 5.9 22.1 2.5 4.5

Sample Quartz K-Feldspar Plagioclase Calcite Dolomite (wt.%) (wt.%) (wt.%) (wt.%) (wt.%)

Table 3 – XRD Data for Clay Minerals for Samples in the NMR Core-Flood Experiments

8 7.5 0.0 2.5 0.0 5

34 18.3 4.9 5.6 1.0 6.8

Sample Total Clay Illite-smectite Illite and Mica Kaolinite Chlorite (wt.%) (wt.%) (wt.%) (wt.%) (wt.%)

20

Fig. 9. 2D slice of a 3D micro-CT image with registered EDX mineralogy. This is the same image view as in Figure 8. Pixel size is 2 microns.

A

B

C

QuartzK KeldsparPlagioclaseIllite/MuscoviteBiotiteKaoliniteChloriteCalciteDolomiteAnkeriteZirconRutileApatiteBaritePyriteUnclassified+traces

have four dominant porosity locations on T1T2 maps (Fig. 6). The liquid porosities in the VCBW bins of Zone A are generally weak, and have variable locations corresponding to variable T1T2 ratios and T2apparent values. Zones B through D have variable liquid porosities. Zone B is located at higher T1/T2

ratios near the bulk volume irreducible T2 line (BVI) at approximately 30 ms. Zone C has a high T1 with variable T1/T2 ratios. Zone D is close to the T1/T2 unity line. Poorer quality reservoirs have reduced liquid porosity in Zones C and D and increased porosity in Zones A and B (Fig. 7).

below bubble point. We typically see more porosity in Zone C in underpressured sands that are below bubble point. We interpreted Zone B as residual oil in smaller pores and with higher asphaltene content than the oil in Zone D. Oils with higher asphaltene content have higher T1/T2 ratios (Birdwell and Washburn, 2015), and Zone B is generally near a T1/T2 ratio between 3 and 5. Oil in small pores has been demonstrated in porosity bins near the BVI line in shale oil reservoirs (Chen et al., 2013).

Pore-scale Imaging of Wettability

Pore-scale imaging of a high-quality reservoir sand shows residual oil and connected macro- and microporosity (Fig. 8). Log characteristics of the sand for this sample are comparable to the reservoir sands shown in Figs. 3, 4, and 6. In this plug, residual oil saturation is much less than estimated flushed zone oil saturation because of significant loss of oil during core recovery. Most

Fig. 6. Log NMR T1T2 map of liquid porosity volumes as a function of T1 and T2apparent in a high-quality reservoir sand. Distinct porosity zones are labeled A-D. This T1T2 map is near Sample 8.

Fig. 7. Log NMR T1T2 map of liquid porosity volumes as a function of T1 and T2apparent in a poorer reservoir quality sand. Distinct porosity zones are labeled A through C. There is a faint porosity zone labeled D. This T1T2 map is near Sample 34.

Our hypothesis was that the liquid porosities in these zones were predominantly associated with different fluid types. We interpreted Zone A as clay-bound water and Zone D as movable oil and water. We were puzzled by Zone C and speculated it could be high GOR oil in reservoirs near or just

Fig. 8. 2D slice of a 3D micro-CT image with registered SEM with residual oil (left; brown), and connected porosity (right; blue). EDX mineralogy is shown in Fig. 9. This image is from a higher quality reservoir sand. A) Chlorite with residual oil and connected microporosity. B) Argillaceous lithic fragments composed of illite and other minerals with residual oil and connected microporosity. C) Macropore with residual oil. Voxel size is 2 microns.

residual oil resides in micropores within areas of abundant chlorite (Figs. 8 and 9A) and clay-rich lithic fragments (Figs. 8 and 9B). Although not commonly imaged due to oil evacuation during recovery, residual oil is imaged in connected macropores (Figs. 8 and 9C). These images indicate that there are at least two predominant pore sizes, macro- and micropores. Residual oil saturation is associated with chlorite, chlorite- and illite-rich lithic fragments, and open macropores.

Pore-scale imaging of poorer quality reservoir sand also shows residual oil and connected macro- and microporosity, but porosity is predominantly microporosity (Figs. 10 and 11). This plug is at a depth of 5490 ft with log data shown in Fig. 5

Fig. 10. 2D slice of a 3D micro-CT image with registered SEM with residual oil (left; brown), and connected porosity (right; blue). EDX mineralogy is shown in Fig. 11. This image is from a poorer quality reservoir sand. A) Lithic fragment composed primarily of muscovite/illite/illite-smectite and quartz with residual oil and connected porosity. B) Open pore with pore-bridging I/S partially filled with residual oil. C) Macropore with connected porosity, but no residual oil in the I/S. Voxel size is 2 microns.

and 7. The residual saturation imaged in this plug is very close to the invaded zone estimated oil saturation indicating that much less oil was evacuated during core recovery than for the high-quality plug. Surprisingly, no residual oil was imaged in the macropores, even though porosity in the macropores is connected. Nearly all of the residual oil resides in microporous and clay-rich lithic fragments (Figs. 10 and 11A). The pore- bridging I/S can be seen in the SEM-registered

USING CORE AND LOG DATA TO CHARACTERIZE WETTABILITY

Fig. 11. 2D slice of a 3D micro-CT image with registered EDX mineralogy. This is the same image view as in Fig. 10. Pixel size is 2 microns.

QuartzK KeldsparPlagioclaseMuscovite/Illite/Illite-SmectiteBiotiteChloriteCalciteSideriteDolomiteAnkeriteBariteZirconRutilePyriteApatiteUnclassified+traces

Mineral Name

A

B

C

Mineral Name

21

micro-CT images in the open macropores. Some residual oil resides in the pore-bridging I/S, but not all I/S contains residual oil (Figs. 10 and 11B).

For both high- and poor-quality samples, residual oil in the micropores is consistent with oil-wet pores within argillaceous lithic grains and authigenic chlorite. When there was no connected porosity in the lithic grains or chlorite, there was also no residual oil present. Residual oil was partially present in the pore-bridging I/S. We interpret the I/S as being partially oil-wet, but tending more towards being water-wet. There was not enough residual oil preserved in the macropores to interpret their wettability with this analysis. Macropore wettability was determined using SEM imaging of asphaltene deposition.

Pore-scale images of asphaltene deposition show mixed-wet mineral surfaces at the macro- and microscales (Figs. 12 and 13). The bumpy material present on some mineral faces are asphaltene deposits on the surface. Presence of asphaltenes on a mineral face indicates an oil-wet surface. Mineral faces that do not contain asphaltene deposits are water-wet. Wettability imaging demonstrated mixed-wet and oil-wet phases in framework grains and clays (Table 4).

The pore-scale imaging results revealed a far more complex distribution of mixed-wet pores than we had originally anticipated. Presence of oil-wet clays also could potentially explain some of the

the core experiment whereas the in-situ reservoir oil contains dissolved gas.

To assist our interpretation of the NMR data for wettability effects, it is necessary to characterize the NMR bulk fluid properties. A fluid T2 much less than the bulk T2 of that fluid indicates some wettability to that fluid in the sample. Measured bulk T2 for the produced oil is 300 ms at 150°F. Based on the Vinegar method (Vinegar, 1995; Coates et al., 1999), we calculate a bulk T2 for the synthetic brine of 2 to 3 seconds.

Core NMR for the core-flood experiments, original log T1T2, coarse-grid-sampled log T1T2, and log 2.5D results for Sample 8 are shown in Figs. 14 through 22. Considering the experimental setup of the core NMR measurements described above, the as-received core NMR T1T2 results for Sample 8 (Fig. 14) are comparable to Zones A, B, and D of the log NMR T1T2 (Figs. 6 and 21). This confirms that the fluids in Zones A and B of the T1T2 map are residual immovable fluids. But, it also indicates some residual fluids reside in Zone D. Fluids in Zone C are not present in the as-received core.

Fig. 12. SEM images of quartz (left) and carbonate (right) showing presence and absence of asphaltene deposits. Oil-wet mineral surfaces are labeled OW and a water-wet mineral surface is labeled WW.

Fig. 13. SEM images of chlorite (left) showing presence and absence of asphaltene on clay flakes. Platy illite (right) was commonly admixed with illite and is indeterminate. On the left, oil-wet clay flakes are labeled OW and water-wet mineral surfaces are labeled WW.

anomalous responses of the NMR T1 and T2 log data in these sands. If oil and not water is in contact with clay surfaces, then this could explain the lack of a “clay-bound water” response in the NMR data. Instead, images suggested that some of these sands contain “clay-bound oil.”

Core-flood NMR Experiments and Comparison with Log NMR T1T2 and 2.5D Data

The core-flood experiments were designed to mimic reservoir conditions and downhole log data as much as possible, but there are physical limitations to obtaining reservoir conditions in the lab. These limitations impact how core and log data are compared and interpreted. Core NMR T2 data have a signal-to-noise ratio of 100. Log NMR data are stacked to increase the signal-to-noise ratio for inversion. Due to the time constraints

in maintaining the core plugs at reservoir temperature, the core NMR T1T2 data have a lower signal-to-noise ratio than either core T2 or log NMR data. The lower signal-to-noise ratio of the core data reduces the resolution of the T1T2 inversion. Consequently, to compare the downhole log data to the core NMR, we resampled the downhole NMR T1T2 data to a coarser grid to mimic the reduced resolution of the core NMR T1T2 data. Unlike the downhole data, the core T1T2 does not have an applied gradient, so the core T2 data are by definition T2intrinsic. The T1 lab data have lower relaxation times than the downhole data because produced dead oil is used in

Fig. 14. As-received T1T2 map for Sample 8.

Flooding Sample 8 with produced oil increases the liquid porosity in Zone D and overlaps the as-received T1 and T2 data (Figs. 14, 17, and 19). When oil is added to the sample, oil fills the largest pores. The T2 peak of the larger pores shifts from approximately 40 ms to 80 ms consistent with oil filling the macropores. Because only oil has been added to the sample during this step, the predominant macropore oil T2 in this sample is 80 ms, much less than the bulk oil T2 of 300 ms. This indicates some oil-wetness in the macropores of Sample 8.

Flooding Sample 8 with brine results in two porosity zones in the T1T2 map, with T2 peaks at 10 ms

Table 4 – Predominant Wettability of Minerals in Reservoir Sands as Determined by SEM Imaging of

Asphaltene Deposits and Spot EDX Analysis

Mineral Predominant Wettability

Quartz Mixed-wet

Feldspars Indeterminate

Carbonates Oil-wet

Chlorite Oil-wet

Illite Indeterminate Platy illite may be oil-wet

Illite-Smectite Not imaged for wettability

22

chlorite (Fig. 2A). The 2.5D map for T1 / T2 equal to 1 also indicates that the movable fluids in Zone D are predominantly oil with some formation brine possible (Fig. 22, second from top).

The 2.5D map for T1 / T2 ratios of 3 and 5 indicate that the in-situ fluids for Zones A, B, and D are oil with molecular diffusion less than water (Fig. 22, third from top and bottom). The 2.5D map for T1 / T2 equal to 3 indicates that the oil in Zone B is oil in micropores with either slightly higher viscosity than

Fig. 15. Oil-flooded core T1T2 map for Sample 8.

Fig. 16. Brine-flooded core T1T2 map for Sample 8.

USING CORE AND LOG DATA TO CHARACTERIZE WETTABILITY

Fig. 17. Core T2 as received (red) and oil flooded (green) for Sample 8.

and 1000 ms (Figs. 16, 18, and 20). Except for the expected reduced T1 values in the core data, the brine-flooded core T1T2 map is very similar to the downhole log T1T2 (Fig. 21). The T2 lobe that peaks at 1000 ms is directly comparable to Zone C. This indicates that Zone C in the reservoir is water, most likely mud filtrate in the macropores. The upper peak T2 for water is also less than the calculated brine bulk T2 indicating weak water-wetness in the macropores.

Because these samples were not cleaned during any of the experimental steps, each sample possibly contains both oil and water in all measurement steps. To further distinguish the T1T2 correlations associated with oil and water, we used the 2.5D processed downhole data (Fig. 22). Generally, brine has a T1/ T2 ratio equal to 1 or slightly larger. The 2.5D map for T1 / T2 ratio equal to 1 contains the high T2 data confirming that Zone C is water. The inversion calculates a high molecular diffusion, in the range expected for gas. In the reservoir, the fluid in Zone C could have a high molecular diffusion due to gas, or the paramagnetic effect caused by pore-lining

Fig. 18. Core T2 oil flooded (green) and brine flooded (blue) for Sample 8. The slight loss of total liquid porosity in the brine flood is due to some liquid evaporation in the sample based on sample weight measurements.

Fig. 19. Core T1 as received (red) and oil flooded (green) for Sample 8.

Fig. 20. Core T1 oil flooded (green) and brine flooded (blue) for Sample 8.

oil in macropores, or reduced molecular diffusion due to restricted diffusion. Higher viscosity and higher T1T2 ratios of this oil is consistent with a possible higher asphaltene content of oil in the oil-wet micropores. The fluids in Zone A must be oil with very low molecular diffusion. We cannot distinguish between the effect of asphaltenes or restricted diffusion causing this reduced molecular diffusion in Zone A.

The log NMR, core-flood NMR, deep resistivity, dielectric data, and pore-scale imaging are consistent with a mostly oil-wet tight sand with mixed-wettability at micro- and macropore scales. The USBM measurement for this sample is -0.3, also consistent with a mostly oil-wet sand. Oil is in contact with clay surfaces reducing the NMR signal in the bins normally associated with clay-bound water. This could also explain the variable results comparing VCBW calculated from XRD and NMR as the signal is likely not related to the clays, but the signal is more likely related to variable wettability in the micropores.

The core-flood and NMR 2.5D processing for Sample 34 show very different results exhibited in Figs. 24 through 33. The as-received core NMR for Sample 34 shows residual fluids in Zones A and B and not C (Figs. 7 and 23). The log NMR T1T2 map shows a faint porosity signal in Zone D not detected by the as-received core NMR.

Flooding Sample 34 with oil adds more liquid porosity in the T2 bins greater than 3 ms, but also removed porosity in the T2 bins less than 3 ms (Figs. 24, 26, and 28). We would expect oil flooding to introduce oil primarily in the macropores. The T2 signal does show more liquid porosity at T2 greater than 100 ms. Although liquid porosity increases in the larger T2 bins, the peak T2 does not shift and remains at approximately 30 ms. This indicates that the macropores in Sample 34 have some oil-wetness because the T2 signal is much less than the bulk oil T2 of 300 ms.

23

Flooding Sample 34 with brine shows a good match to the coarse-grid processing of the log T1T2 (Figs. 25 and 30). Flooding with brine reduces liquid porosity in the higher T2 bins, except for a small amount at a T2 of approximately 400 ms. This increase in porosity restores the lost liquid porosity in the T2 bins less than 3 ms (Figs. 25, 27, and 29). We assume that flooding with brine replaces oil with brine in the macropores.

The peak at higher T2 bins shifts from 30 ms to 10 ms when brine replaces oil. This indicates that macropores are likely more water-wet than oil-wet. Intermediate T2 liquid porosity associated with Zone B (Fig. 7) is not affected by the brine flood.

In our study, we conducted core-flood NMR experiments on four samples, representing different patterns of log data. Of these four samples, only Sample 34 has pore-bridging I/S (Fig. 2B). Pore- scale imaging shows that the fibrous I/S is open to connected macropores and can contain small volumes of residual oil (Figs. 10 and 11). Because the fibers of I/S are open to the macropores, flow-through of liquids in this sample can affect the liquids associated with the pore-bridging I/S. In all the samples without I/S, there was effectively no change in the T2 response for bins less than 3 ms during both the oil and brine floods (e.g., Figs. 17 and 18). In contrast, during the oil flood of Sample 34, porosity was reduced in the T2 bins less than 3 ms (Fig. 26). After flooding Sample 34 with brine, porosity in the bins less than 3 ms was restored to the same value as for the as-received measurement (Figure 27). One hypothesis for this result is that fibrous I/S tend to be more water-wet. Flooding with oil could remove residual water open to the macropores, placing oil on the clay surfaces with increased T2 times. Flooding with water resulted in water in the macropores and water on the pore-bridging I/S. This would increase true clay-bound water porosity.

The 2.5D processing gave further insight into the in- situ reservoir fluids in the sand containing Sample 34 (Fig. 31). Like for Sample 8, the fluid in porosity Zone C is likely mud filtrate or a mixture of mud filtrate and formation brine in the macropores as indicated with the 2.5D processed data for a T1 / T2 ratio of 1 and 3 (Fig. 31, second and third from top). The molecular diffusion for this fluid is closer to the estimated value for water than for Sample 8. This reservoir type has very little chlorite lining the macropores and consequently is not as affected by paramagnetic effects (Fig. 2B).

The 2.5D processing shows the fluid in porosity Zone B is mostly oil with a T1/T2 ratio closer to 1 (Fig. 31 second from top), but also some water with a T1/T2 ratio of 3 or 5 (Fig. 31 third from top and bottom). Generally, formation brine has a T1/T2 ratio close to 1. However, if the formation brine contains iron cations, there can be a paramagnetic affect resulting in a T1/T2 ratio greater than 1 for formation brine (Daigle et al., 2014). GMBU-produced waters typically contain iron cations, and so it is possible for the formation

Fig. 21. Comparison of log T1T2 (top), coarse-grid processing of log T1T2 (middle) and brine-flooded coreT1T2 for Sample 8 (bottom)

Fig. 22. Log T2 D map with 2.5D processing for the log depth of Sample 8. T1 / T2 ratio = 1 for the log depth of Sample 8. Full T1 / T2 ratios combined (top), T1 / T2 ratio = 1 (second from top), T1 / T2 ratio = 3 (third from top), and T1 / T2 ratio = 5 (bottom).

24

brine to have elevated T1/T2 ratios. Presence of oil in the micropores is consistent with the residual oil pore-scale imaging (Fig. 10).

The 2.5D processing indicates the fluid in Zone A is oil and possibly some water (Fig. 31). Calculated molecular diffusion for this fluid is extremely low as seen on the 2.5D data for T1/T2 equal to 3 and 5. This small molecular diffusion is likely due to either oil in very small pores or reduced T2 and D caused by oil interacting with asphaltenes. Possibly some of this fluid is actual clay-bound water given the high estimated molecular diffusion as shown for T1/T2 equal to 1 and 3 (Fig. 31 second and third from top).

The core-flood data indicate very little exchange of fluids during oil flooding and then brine flooding within Sample 34 consistent with low permeability (Table 1). Like in Sample 8, the fluids in Zone B of Sample 34 are primarily residual oil, but there is also some formation brine with elevated T1/T2 ratios). Also like Sample 8, the fluid in Zone C of Sample 34 is likely mud filtrate or mud filtrate mixed with formation brine in the macropores. Surprisingly, the fluids in Zone A are likely oil with some clay-bound water. These sands typically show more NMR T2 porosity for T2 bins less than 2.8 ms than estimated clay-bound water from XRD data. This suggests that some of this liquid porosity is likely oil and not water. Either the oil resides in very small pores, or it has a reduced T2 caused by the interaction of oil and asphaltenes in the microporosity. The fluids in the faint porosity Zone D are likely oil and formation brine in the few macropores of this reservoir sand (Fig. 10).

Originally, we interpreted this particular reservoir sand as water-wet because deep-resistivity values are typically less than 100 ohmm, and dielectric data and our resistivity saturation model indicate formation brine is present. The core-flood NMR experiments show little exchange of fluids, which is consistent with a small proportion of macropores. Surprisingly, USBM data for this plug was -0.2 indicating a more oil-wet rock. The USBM measurement of wettability is a bulk property of the rock. But wettability in Sample 34 is segregated with more oil-wet micropores and more water-wet macropores. The presence of oil in micropores combined with a dominance of microporosity for this plug is consistent with a dominant oil-wetness as measured by USBM measurement of wettability. In contrast, reservoir macropores contain water. The wettability of this sample is segregated into micro- and macropores, but the bulk USBM

measurement responds to the dominant pore scale of wettability. If formation brine resides predominantly in mixed-wet connected macropores, this may provide a connected electrical path, thus explaining low deep-resistivity data. Consequently, pore-scale segregation of wettability explains the seemingly incongruous results of an oil-wet rock with low deep resistivity.

USING CORE AND LOG DATA TO CHARACTERIZE WETTABILITY

Fig. 23. As-received T1T2 map for Sample 34.

Fig. 24. Oil-flooded core T1T2 map for Sample 34.

Fig. 25. Brine-flooded core T1T2 map for Sample 34.

Fig. 26. Core T2 as received (red) and oil flooded(green) for Sample 34.

Fig. 27. Core T2 Oil flooded (green) and brine flooded(blue) for Sample 34.

Fig. 28. Core T1 as received (red) and oil flooded(green) for Sample 34.

Fig. 29. Core T1 as received (red) and oil flooded(green) for Sample 34.

25

DiscussionBased on field production, and log and core data, we understood that the tight-sand reservoirs in GMBU have highly variable mineralogy, rock quality, and wettability. Downhole conventional and advanced log data showed consistent patterns likely related to these variable rock and fluid reservoir properties.

Fig. 30. Comparison of log T1T2 (top), coarse-gridprocessing of log T1T2 (middle), and brine-flooded coreT1T2 for Sample 34 (bottom).

In particular, we observed that downhole NMR data in some reservoir sands measured no clay-bound water volumes. Dielectric data measures very low water volumes in these sands. But, our multimineral model and core XRD data indicate that these sands contain clay minerals and should have measureable clay-bound water. In other sands, NMR measures clay-bound water volumes significantly greater than core XRD indicated. NMR data have a different measurement volume than either standard logging suites used in our multimineral model or core XRD. Yet, there were consistent patterns in these inconsistencies, and often the differences were larger than measurement uncertainties.

To better understand these patterns, we initiated a study integrating pore-scale imaging, core-flood NMR experiments, and downhole T1T2 and 2.5D NMR processing. In this paper, we present results from the two end-member reservoir sands. The results indicate a far more complex pore-scale view of wettability and locations of oil and water in these reservoirs than we initially assumed. Nearly all reservoirs have some mixed-wet pores at micro- and macroscales. The reservoirs vary in their proportions of macroporosity and oil-wettability related to rock quality and mineralogy. These variable properties can be characterized in the field using downhole NMR T1T2 and 2.5D processing. Identification of patterns in these data permits extension of this characterization to other wells where we do not have NMR data.

The results have broader implications for interpreting NMR data in mixed-wet reservoirs. Standard NMR interpretation techniques using T1, T2, T1T2, and T2D data assume a reservoir is water-wet. T1 and T2 data with fast relaxation times are routinely interpreted as a measure of clay-bound water volumes. Liquid porosities for formation brines and variable viscosity oils are interpreted from T1T2 and T2D maps using water-wet assumptions of the NMR responses. Oil- or mixed- wet pores complicate these interpretations.

Oil-wettability reduces the T2 response of oil from the expected dominant T2 value because of increased surface relaxivity. Interpreting NMR T2 and T2D data assuming water-wet conditions can lead to an overestimation of water volumes as the oil response appears more like a water response. Core T2 NMR is commonly performed on cleaned plugs to calibrate movable and immovable fluid volumes using log T2 data. Cleaning can render a mixed-wet rock to water-wet, giving calibration results not applicable to reservoir conditions.

Fig. 31. Log T2 D map with 2.5D processing for the logdepth of Sample 34. T1 / T2 ratio = 1 for the log depthof Sample 34. Full T1 / T2 ratios combined (top), T1 / T2ratio = 1 (second from top), T1 / T2 ratio = 3 (third fromtop), and T1 / T2 ratio = 5 (bottom).

26

The possibility of oil-wet clays in a reservoir can explain anomalous log NMR results. Simply put, if there is no clay-bound water response on NMR, it does not necessarily mean the sand lacks clay minerals. It could mean the reservoir has clay-bound oil instead of water. Similarly, NMR data can indicate more clay-bound water than expected. Sometimes NMR data indicate only clay-bound water porosity with no movable fluids in a reservoir, yet the reservoir inexplicably produces oil. These anomalous results could be the result of oil-wet pores with oil residing in smaller pores, such that the oil response is in the fast relaxation bins of T1 and T2 log data, but interpreted as clay-bound water.

The possibility of oil-wet clays or oil-wet microporosity also has implications for development of petrophysical models. Given the possibility of oil volumes interpreted as water volumes in either the assumed movable or immovable relaxation times of NMR data, petrophysical models calibrated to NMR measurements may lead to an inaccurate physical description of the reservoir petrophysical properties, such as fluid total and movable volumes for oil and water. Petrophysical models using effective porosity, but calibrated to NMR VCBW bins, may be inaccurate if the fast NMR is responding to oil and not water. Similarly, petrophysical models that estimate movable water using NMR data from the BVI bins may give inaccurate estimates if the NMR response in the BVI bins is due to oil.

This study shows that NMR results can be used to characterize the pore locations and volumes of different reservoir fluids resulting from wettability variations. This study provides a recipe for data to collect and analyses to perform to utilize NMR data in mixed-wet reservoirs.

The most useful log data are standard triple- combo, dielectric, and NMR data. A dielectric model, using appropriate mineral permitivities, permits estimation of reservoir water volumes in the flushed zone for calibration of saturation models (Merkel, 2006). Triple-combo data can be used for a multimineral and saturation models for more field-wide extension of results. For fluid and wettability characterization, NMR data need to be acquired with tool activations for measuring T1, T2, and diffusion data. Once acquired, inversion of these data can be used to construct T1T2 and 2.5D maps. T1T2 maps show the correlations of T1 and T2 data for fluids in different pore sizes, but can be ambiguous for fluid typing if there are mixed-wet pores. 2.5D processing and analysis gives insight into fluid types corresponding to the porosity zones of the T1T2 maps.

These log data alone can be ambiguous with respect to wettability and fluid typing. Calibration with core data can reduce ambiguity leading to a more field-wide characterization of log data. The most useful core data are XRD, pore-scale imaging, and, if permeability permits, NMR core- flood experiments and USBM measurements of wettability. XRD data can be used to estimate volumes of clay minerals and associated clay- bound water. These data can be compared to NMR estimates of clay-bound water to determine any significant differences. SEM imaging of asphaltene deposits combined with EDX mineral identification can be used to understand wettability in the context of pore structure and mineralogy. Micro-CT scans of as-received, cleaned, and brine-filled plugs combined with registered SEM and EDX mineral maps provide additional information about wettability, locations of residual oil, proportions of micro- and macroporosity, and connected porosity. NMR core-floods compared to log NMR data and integrated with pore-scale imaging and log T1T2 and 2.5D data provide additional insight into the NMR response of oil and water in micro- and macropores. USBM measurement of wettability characterizes the bulk rock response and potentially gives insight into the wettability of the dominant connected porosity. Unlike USBM measurements, pore-scale imaging can indicate if wettability is segregated by pore type and scale.

Measurements of fluid properties are also useful. Measurement of bulk T2 of produced oil can be compared to the dominant T2 response of oil in the reservoir. Reservoir T2 values much less than the bulk T2 indicate some oil-wetness in the reservoir. SARA (measurements of saturates, aromatics, resins, and asphaltenes) of produced oil and extracted residual oil can be used to determine the amount of polar hydrocarbons in the movable and residual oil. Chemical analyses of produced water are useful to determine if cations in the reservoir brine might result in a T1/T2 water response greater than 1.

ConclusionsObserved mismatches in estimation of clay-bound water volumes from NMR and other core and log data can indicate reservoirs with variable wettability. Presence of mixed-wet microporosity and oil-wet clays can explain reservoirs with either too much or too little estimated clay-bound water from standard NMR analyses compared to other data. In this paper, we present an analysis protocol useful in characterizing variable wettability to more accurately interpret log data for types and volumes of produced

oil and water. These results have implications for petrophysical analyses beyond GMBU.

The most useful core data are XRD, pore-scale imaging, and, if permeability is sufficiently high, USBM and core floods with core NMR. XRD data are used to compare estimated clay-bound water volumes with volumes estimated from NMR to determine if there is a mismatch and potential variations in wettability. Pore-scale imaging is useful for determining the association of pore scales, pore types, residual oil, connected porosity, wettability, and mineralogy. USBM measurements and core-flood experiments can confirm and quantitatively extend the pore-scale imaging results. Core-flood NMR T1T2 map data are used to characterize fluids and fluid volumes from log NMR T1T2 maps.

The most useful log data are NMR and dielectric data, combined with standard triple-combo log suites. Log NMR, collected with activations measuring T1, T2, and diffusion data, can be inverted for T1T2, T2D, and 2.5D maps. The T1T2 and T2D maps are compared with standard water-wet interpretations. If the reservoir is mixed-wet, standard interpretations of NMR will lead to overestimation of water volumes because oil porosity will shift into locations associated with water in water-wet pores. Dielectric data, saturation models, and produced fluid volumes are used to test standard NMR interpretations. NMR 2.5D processing reduces ambiguity in fluid types and volumes residing in different pore scales.

Produced fluid types and volumes are strongly controlled by pore-scale geometries, mineralogy, and fluid types. Because oil can reside in microporosity and on clay surfaces, we cannot assume only water in these locations. Therefore, delineating the pore scales where oil and water reside in a reservoir and potential pore segregation of wettability increases the importance of pore- scale imaging combined with NMR 2.5D processing for reservoir characterization.

Beyond GMBU, these results have implications for core and log NMR analyses, and development of petrophysical models from NMR data. Typically, core NMR is measured on a clean and dried plug to determine T1 and T2 cutoffs for estimating volumes of irreducible and movable fluids from log NMR data. Clay-bound water volumes are estimated using a 2.8-ms T2 cutoff. In mixed-wet reservoirs, oil or oil and water rather than only water may reside within interpreted clay-bound and irreducible

USING CORE AND LOG DATA TO CHARACTERIZE WETTABILITY

27

volumes. When a plug is cleaned and dried, mixed-wet pores can be altered to water-wet, which can complicate estimation of cutoffs. Petrophysical models that distinguish between total and effective porosity may be inaccurate if the clay-bound water model is calibrated to NMR data actually containing oil. Similarly, estimation of produced

water volumes based on BVI estimation from NMR may be inaccurate if oil resides in the BVI bins in NMR data.

The results of this study go far beyond understanding primary fluid production in GMBU. Because Monument Butte is being subjected to

AcknowledgementThe authors would like to thank the management of Newfield Exploration Company for the release of these data. Margaret Lessenger thanks Terri Olson and Lyn Canter for fruitful discussions about pore-scale imaging and wettability.

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Freedman, R., Heaton, N., 2004, Fluid characterization using nuclear magnetic resonance logging, Petrophysics, v. 45, no. 3, p. 241-250.

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Knackstedt, M., Senden, T., Carnerup, A., Fogden, A., 2011, Improved characterization of EOR processes in 3D. Characterizing mineralogy, wettability and residual fluid phases at the pore scale, SPE 145093.

Lessenger, M., Merkel, R., Sullivan, B., Burton, D., 2013, Application of dielectric and standard logging suites to characterize the stratigraphic and lithologic variations in Archie parameters within the Green River Formation of the Greater Monument Butte Field, Uinta Basin, Utah, USA, SPWLA 54th Annual Logging Symposium, June 22-26, 2013.

Lessenger, M., Sullivan, B., Woolf, K., Burton, D., 2015, Fluid sensitivity in tight sandstones – when rocks behave badly, AAPG Memoir 110, (in press).

Marathe, R., Turner, M.L., Fogden, A., 2012, Pore- scale distribution of crude oil wettability in carbonate rocks, Energy & Fuels, v. 26, no. 10, p. 6268-6281.

Mardon, D., Prammer, M.G., Coates, G.R., 1996, Characterization of light hydrocarbon reservoirs by gradient-NMR well logging, Magnetic Resonance Imaging, v. 14, no. 7/8, p. 769-777.

Martin, P., Dacy, J., 2004, Effective Qv by NMR core tests, SPWLA 45th Annual Logging Symposium, June 6-9, 2004.

Merkel, R., 2006, Integrated petrophysical models in tight gas sands, SPWLA 47th Annual Logging Symposium, June 4-7, 2006.

Merkel, R., Lessenger, M., 2014, Characterizing the oil reservoirs in the Uinta Basin, SPE Conference Paper SPE-169510-MS.

Ramakrishna, S., Merkel, R., Balliet, R., Lessenger, M., 2012, Mineralogy, porosity, fluid property, and hydrocarbon determination of oil reservoirs of the Green River Formation in the Uinta Basin, SPWLA 53rd Annual Logging Symposium, June 16-20, 2012.

Sok, R.M., Varslot, T., Ghous, A., Latham, S., Sheppard, A.P., Knackstedt, M.A., 2010, Pore scale characterization of carbonates at multiple scales: integration of micro-CT, BSEM, FIBSEM, Petrophysics, v. 51, no. 6, p. 379-387.

Sun, B.Q., Dunn, K.J., 2005, A global inversion method for multi-dimensional NMR logging, Journal of Magnetic Resonance, v. 40 no. 2, p. 152-160.

Vinegar, H., 1995, Relaxation mechanisms, chapter 3, in Georgi, D.T., ed., 36th Annual SPWLA Logging Symposium: Nuclear magnetic resonance logging short course notes, variously paginated.

a water flood, analysis of the wettability of the various sand facies controls the effectiveness of the flood. Moreover, because of the complex mineralogy and variations in wettability, composition of the flood water, as well as injection site locations create an unexpected new set of variables for this field.

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Margaret Lessenger is a petrophysicist for Newfield Exploration Company in Denver. She has over 30 years of experience as a geophysicist, geologist, and petrophysicist working in various basins in the Rockies, North

Sea, and Gulf of Mexico. She has worked for the Superior Oil Company, ARCO Oil and Gas, Platte River Associates, the Colorado School of Mines Department of Geology, and Williams Exploration prior to joining Newfield. Margaret holds a BS in geophysical engineering, an MS in geophysics, and a PhD in geology from the Colorado School of Mines. She is a member of SPWLA, AAPG, SPE, and SCA.

Dick Merkel is president of Denver Petrophysics LLC, which is a consulting firm dedicated to developing core and log analytical techniques for petrophysical models tied to completion and production data

in complex reservoirs. As a petrophysicist for Newfield Exploration Company, he worked for six years on teams that developed reservoir models for unconventional oil and gas reservoirs in the Rocky Mountains. Dick also was with EnCana Oil & Gas in Denver where he worked on developing petrophysical models for tight-gas sandstone reservoirs. Prior to its closing in 2000, he was a senior technical consultant at Marathon Oil Company’s Petroleum Technology Center in Littleton where he worked on evaluating new logging tools and technology, and developing techniques for their application in Marathon’s reservoirs. Dick has a BS in physics from St. Lawrence University and an MS and PhD in geophysics from Penn State. He is a past president of SPWLA, the SPWLA Foundation, and DWLS.

Rojelio Medina works as a consultant for petrophysics and log analysis for Halliburton’s Formation and Reservoir Solutions (FRS) group in Houston, TX. In FRS, Rojelio has worked in many disciplines of petrophysics, including

NMR interpretations. Rojelio joined Halliburton in 2006 and worked as a field engineer before joining FRS in 2010. Rojelio received his BS degree in geology from Texas A&M University – Kingsville in 2005. Rojelio is a member of SPWLA and SPE.

Sandeep Ramakrishna is a petrophysicist for Halliburton in the US Southern Region Wireline and Perforating product service line. He has more than 17 years of experience in the industry. Sandeep has been

actively involved the development of techniques to analyze unconventional reservoirs. He holds an MS degree in petroleum engineering from the University of Tulsa, Oklahoma and a BSc degree in geology from the University of Pune, India. Sandeep is a member of SPWLA, SPE, and AAPG.

Songhua Chen is senior manager of NMR Sensor Physics at Halliburton. Before joining Halliburton, he was senior staff scientist and senior manager of Integrated Interpretation and Petrophysics in the Houston

Technology Center of Baker Hughes. He has been involved in various projects on NMR, sensor R&D, petrophysics, and carbonate and shale rock models. Prior to joining the industry, he was doing research at the Texas Engineering Experiment Station on the application of NMR for multiphase flow in porous media. Songhua received his BS degree in physics from the Nanjing Institute of Technology in China and a PhD in physics from the University of Utah in Salt Lake City, Utah.

Ron Balliet is the global NMR product champion for Halliburton. He joined Numar in 1991 and worked with oilfield NMR in several locations worldwide. Since 1997, he has held various positions with Halliburton in

West Africa and the United States, becoming the global NMR product champion in 2006. Ron holds BS degrees in geology and geophysics from the University of Minnesota (1984). He is a member of the SPWLA and SPE.

Zonghai Harry Xie is an NMR senior advisor at Core Laboratories in Houston. Before joining Core Lab, he had been working for the instrumentation industry for about 20 years. He spent several years working as a product

specialist developing and supporting laboratory NMR products (MARAN product line) at Resonance Instruments Ltd. He also spent time at Bruker as the senior applications scientist in the Time Domain NMR division, technical director of the Time Domain products for Asia Pacific, and general manager of Bruker Optics China. He received his PhD in physics from the University of Kent at Canterbury, UK.

Pradeep Bhattad is a senior project manager at FEI Company in Houston. He has over 10 years of experience in digital rock physics, micro-CT imaging, 3D image analysis, and colloids and interface science. Pradeep holds a BE

in chemical engineering from Bangalore University, India and a PhD in chemical engineering from Louisiana State University. He is a member of SPWLA, AAPG, SPE, SCA, and AIChE.

Anna Carnerup is senior lab engineer at FEI Australia, previously Lithicon Australia and Digitalcore. Prior to joining Digitalcore, she was conducting research at the University of Warwick and Lund University within physical

sciences. Anna holds a BS degree in chemical engineering from Malmö University and a PhD from the Australian National University in physical sciences.

Mark Knackstedt is director of technology development for FEI/Lithicon and a visiting professor at the Department of Applied Mathematics at the Australian National University. He is a past (2007-2008, 2009-2010,

2012-2013) SPWLA distinguished speaker, was awarded the George C. Matson Memorial Award from the AAPG in 2009, and the ENI award for New Frontiers in Hydrocarbon Research in 2010. Mark was awarded a BSc in 1985 from Columbia University and a PhD in chemical engineering from Rice University in 1990.

Authors

AN ENSEMBLED-BASED NONLINEAR STATISTICAL METHOD TO ADDRESS COHERENT SEISMIC NOISEUSING CORE AND LOG DATA TO CHARACTERIZE WETTABILITY

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AN ENSEMBLED-BASED NONLINEAR STATISTICAL METHOD TO ADDRESS COHERENT SEISMIC NOISE

Statistical Attenuation of High Amplitude Coherent NoiseDongjie Cheng, Laura N. Torres, Xiaomin Zhao, Ran Zhou, Minyu Zhang, Rafael Perez, and Dan Quinn, Halliburton; Francisco J. Olarte, PemexPresented at the Society of Exploration Geophysicists International Exposition and 85th Annual Meeting held in New Orleans, Louisiana, October 18-23, 2015.Copyright 2015, Society of Exploration Geophysicists, republished with permission.

SummaryHigh amplitude coherent noise is a problem for seismic processing. It usually carries much stronger energy than signals and can overshadow the signal energies in seismic imaging results. There are many ways to attenuate coherent noise. This paper proposes an ensemble-based nonlinear statistical method to address this type of noise. This method manipulates the noisy traces inside ensembles and uses a statistical approach to identify the noise. After the noise is identified, it can be attenuated accordingly. Being a statistical approach, this method is not sensitive to data aliasing and trace irregularity, and is model free. Refractions in a multishot vertical seismic profile (VSP) are a good example of high amplitude coherent noise, which creates problems in data processing. Tests on a 3D VSP dataset suggests that it works successfully on refraction attenuation.

IntroductionHigh amplitude coherent noise generally includes ground roll, refractions, VSP tube waves, and other guided waves. Their coherency and high energy make them difficult to be removed and contaminate the imaging result. Many methods have been developed to attenuate this type of noise. The common approach is the dip filter, which attempts to address the coherent noise by using the differences in moveout between the desired signals and the coherent noise, such as F-K filter, median filter, and t-ρ filter. However, when the moveout of the noise events is similar to the desired signal, these filters will fail.

Other methods have been developed in the past to address this issue. For example, Strobbia et al. (2011) proposed a model-based method to apply to the ground roll for land surface seismic. This method will not work for all coherent noise, especially in complex subsurface geology. A typical example is the VSP case presented in this paper whereby a refraction type of interface wave was generated during data acquisition in complex geology. These waves contain high energy and cannot be properly addressed/suppressed by Kirchhoff migration. Consequently, their energy overshadows the desired reflection image of the reservoir in the migration results. In addition, these noise events cannot be separated by using conventional wave decomposition methods, such as the median filter or F-K filter. A new nonlinear ensemble-based statistical method is recommended to address this type of coherent noise. Using the new method, the seismic traces containing the coherent noise are regrouped into ensembles. Then, a proprietary method as described below is applied in the ensembles to enable a statistical approach to effectively identify the noise energies. Finally, the identified energy can be attenuated by either scaling down, zeroing out, or deconstruction. The application on the refraction energy in a 3D VSP acquired in complex geology will demonstrate the effectiveness of this new method.

Methodology The ensemble-based statistical scheme is the core mathematical foundation of the new method. It has been used to attenuate random spike events (noise) in premigration data. In theory, a spike can be identified by comparing its amplitude to the samples of all other traces at given traveltimes inside an ensemble. Because spikes have larger amplitudes than the signals, they are statistically outliers. Several means can be used to determine those outliers. This paper presents a standard deviation approach to demonstrate the principle. Assume the data samples in the ensemble at given traveltime form a set of data. The method has three steps:

1. Calculate the reference point and the standard deviation of the absolute amplitude of all data samples. The reference point can be the mean or median.

2. Calculate the absolute difference between the reference point and absolute amplitude of each sample.

3. Identify the outliers based on a defined threshold of the difference, e.g., 3s, where s denotes the standard deviation. Any data sample with a difference larger than the threshold will be treated as an outlier and attenuated accordingly.

These steps should be repeated on all time samples throughout all traces to complete the process on the ensemble. This procedure describes the application on random noise. To extend it to the coherent noise, three key concerns should be addressed:

• Signal preservation. The signals should not be damaged during the processing.

• Coherency. The coherency of noise is the main concern for outlier (noise) identification. If the noise amplitudes can be set as outliers, then the new procedure can be applied.

• Threshold. For each ensemble, finding a robust threshold value for noise identification is crucial. For a large data volume with many traces, it is not practical to have many threshold values.

Through experiments, we have created a feasible workflow and successfully applied it to VSP data processing. Fig. 1 shows the flow chart.

Fig. 1. Processing flow of statistical coherent noise attenuation.

Strong Coherent Noise Isolation

Windowed Data Stretching

Statisical Noise Energy Identification

Noise Attenuation

Stretching - Undo and Merging Back

30

Fig. 2 through Fig. 5 illustrate the workings of this procedure. First, strong signals that have energy comparable to the noise should be excluded from processing. The simple way to do this is to pick a polygon window that includes only the noise energy and other relative weaker signals. In reality, there are no strict requirements for the size and the shape of the polygon, as long as no significant strong signals are included. Fig. 2 shows a four-trace scenario. The blue box marks a strong signal event, and the green box marks the target noise event. To protect the signal event, the dash-lined box forms a new ensemble (Fig. 3).

Fig. 2. Processing flow of statistical coherent noise attenuation. Fig. 3. New data ensemble.

Inside the new ensemble, the statistical de-noise process will be performed. The ensemble-based statistical approach requires isolated high amplitude noise along the trace number direction. The noise with coherency does not meet that requirement. Stretching the data in time has been found to make the noise pseudo-randomized in the trace number direction in the ensemble. A straightforward way is to shift the data samples with varying amounts of times for different traces (Fig. 4). After the time shift, the targeted noise is much stronger than other signals at a given traveltime, as shown by the dashed line in Fig. 4. They become strong outliers,

Fig. 4. Data stretching. Fig. 5. Noise identification and attenuation.

and a robust threshold can be easily found for the ensemble in these experiments. In VSP processing, the data is shifted using the picked first arrival time. The statistical method then can be applied on the stretched data. Fig. 5 illustrates the attenuated noise event. The identified noise amplitudes can be scaled down, zeroed out, or reinterpolated from adjacent samples. Finally, the data samples are shifted back to the original positions, and isolated ensembles are merged with the excluded data volume. This concludes the processing procedure shown in Fig. 1.

AN ENSEMBLED-BASED NONLINEAR STATISTICAL METHOD TO ADDRESS COHERENT SEISMIC NOISE

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3D VSP Data ExampleThis nonlinear ensemble-based statistical method was applied to a 3D VSP processing project. The acquired data contains strong refractions generated at a complex interface with high-velocity contrast in the subsurface. The interface is right above the target reservoir. The refraction energy severely contaminated the reservoir reflection signals on the Kirchhoff migration result. De-noising is critical for the success of the project. Fig. 6 shows 5 of 80 shot gathers of upgoing waves in a walkaway line extracted from the 3D VSP volume. The number in the green box labels the offset from the wellhead for each shot gather. The arrows mark the refraction events. Because the refractions have almost the same moveout as the signals in the shot gathers, it is impossible to isolate them from the signals using dip filters in the shot domain.

However, the refraction events were observed to have much higher amplitudes than the adjacent signals in the receiver domain. Fig. 7 shows a receiver gather of the upgoing waves of the same walkaway line. The data is sorted by offset. The refractions marked by arrows can be converted to pseudo-randomized noise. The procedure was tested on this walkaway line in the receiver domain. Each receiver gather was divided into two ensembles to address the noise in the negative and positive offsets respectively from the wellhead. In this section, the wellhead is located in the center of the figure. A time window was picked to protect the large amplitude signals in each ensemble. The first break time of each trace was used to shift the data. The threshold was 3s, and the reference value was the mean. The noise samples were reconstructed using linear interpolation from the adjacent samples. However, because it is a

Fig. 6. Shot gathers of upgoing waves of a walkaway line from the 3D VSP volume.

Fig. 7. A receiver gather of the upgoing waves.

Fig. 8. Receiver gather after noise attenuation.

Fig. 9. Difference between input and output.

Fig. 10. De-noised shot gathers of the walkaway line.

nonlinear method, small spikes were created by the de-noise process. Bandpass filters and shot domain median filters were carefully tested and found to reduce the deleterious effects of these remaining spikes. Fig. 8 shows the receiver gather after noise attenuation, and Fig. 9 shows the difference between the input and the output. Fig. 10 shows the same shot gathers as those in Fig. 6 after noise attenuation. The arrows mark the location where the refraction events were minimized. The result suggests that the coherent noise was effectively attenuated.

Fig. 11 and Fig. 12 compare the Kirchhoff migration results of the data in time domain of all 48 receivers before and after de-noise. The strong swings caused by refractions in Fig. 11 were eliminated in Fig. 12, and the overshadowed event in the center of the yellow circle was enhanced.

32

Fig. 13 through Fig. 15 show the comparison of a portion of a 3D receiver gather before and after the application of the new method to the entire 3D VSP volume. The noise attenuation procedure was similar to that for the 2D walkaway line. Fig. 13 shows the input data section where the refraction energies are located at the center in time.

Fig. 14 shows the de-noised data section. Fig. 15 shows the difference between the input and output. The difference contains mainly the refraction energies and some scattering. Thus, the method has successfully attenuated the high energy coherent noises in the 3D project.

Fig. 11. Migration image before noise attenuation.

Fig. 12. Migration image after noise attenuation.

Fig. 13. Portion of a 3D receiver gather.

Fig. 14. Portion of a 3D receiver gather after noise attenuation.

Fig. 15. Difference between input and output.

Conclusion The new method addresses high amplitude coherent noise with nonlinear en-semble-based statistical attenuation, which is not sensitive to signal aliasing and irregular trace spacing. This new method has been successfully applied on a 3D VSP project to minimize refraction energy, which is a major concern for VSP processing; the overshadowed signals were improved in imaging.

AN ENSEMBLED-BASED NONLINEAR STATISTICAL METHOD TO ADDRESS COHERENT SEISMIC NOISE

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Dongjie Cheng is an advisor at the Center for Advanced Borehole Seismic Solutions, Formation and Reservoir Solutions (FRS) group at Halliburton. He has more than 20 years of experience in seismic

processing, borehole seismic processing, data processing, R&D, and project management. Before he joined Halliburton in 2013, Dongjie worked as an advisor in the Special Processing group for VSFusion/Baker Hughes. He is a member of SEG and EAGE.

Laura N. Torres is the Borehole Seismic processing team lead for Halliburton’s Formation and Reservoir Solution Group in Houston. She has eight years of experience in borehole seismic processing,

seismic modeling, and seismic anisotropy analysis. In her present position, Laura serves as one of the key technical experts for the company on borehole seismic. Laura received her BS degree in geophysical engineering from Central University of Venezuela UCV in 2007. She is a member of the Society of Exploration Geophysicists (SEG) and the Geophysical Society of Houston (GSH).

Xiaomin (Michelle) Zhao holds a PhD in geophysics from the Massachusetts Institute of Technology (MIT). She has more than 20 years of working experience in the oil and gas industry. Her expertise

includes seismic processing and interpretation, advanced borehole seismic modeling, survey designs, data processing, depth and time VSP imaging, and results analysis. She is currently a senior geophysics advisor with Halliburton’s Formation and Reservoir Solutions.

Ran Zhou is the manager of the Center for Advanced Borehole Seismic Solutions for Halliburton Wireline and Perforating. Ran holds a PhD degree in geophysics from the University of Texas at Austin and

has 20 years of experience in R&D in VSP processing technology, microseismic, and global geophysics. Her expertise includes advanced VSP processing, imaging, and interpretation; overburden seismic anisotropy estimation and depth imaging; shear-wave birefringence and fracture characterization; and seismic amplitude AVO analysis, modeling, and calibration.

Minyu Zhang is a geophysicist and reservoir engineer for Halliburton’s Formation and Reservoir Solutions group. Minyu works on borehole seismic, including data processing, seismic modeling, seismic anisotropy

analysis, and tomographic inversion. She holds an MSc in geophysics from the University of Houston and has several publications on borehole geophysics. She is a member of the Society of Exploration Geophysicists (SEG).

Rafael Perez holds a BS degree in geophysics from Universidad Autónoma de Nuevo Leon, Mexico. He is a borehole seismic consultant in the Formation and Reservoir Solutions (FRS) group for Halliburton

Latin America. Rafael has 16 years of working experience in the oil and gas industry. His experience includes 13 years in borehole seismic processing and interpretation, borehole seismic modeling, and survey designs. He is also a recognized technical advisor in the region, where he has trained geoscientists in borehole seismic for over 10 years.

Dan Quinn is the Borehole Seismic global strategic business manager for Halliburton Wireline and Perforating, responsible for all aspects of Halliburton’s Borehole Seismic business. He holds a BSc in

geology from Old Dominion University and has 36 years of experience in the oil and gas industry, with over 34 years in borehole geophysics. Dan started his career with Western Geophysical and held various domestic and international positions. He is published and holds a patent for a marine point source array design with other patents pending. He is a member of SEG, EAGE, SPE, and AAPG.

Francisco J. Olarte received his BS degree in geophysics from Instituto Tecnológico de Cd. Madero, Mexico in 1993. He is a seismic interpreter and reservoir characterization expert for the

management of shallow water fields development for PEMEX. He has 22 years of working experience in the oil and gas industry, including five years with Halliburton Cementing. Since 2000, Francisco has worked for PEMEX where he has performed different roles in reservoir characterization and static fields characterization for both exploration and exploitation assets. He has developed an expertise in reservoirs of Tertiary and Mesozoic ages, both in land and offshore oil fields. Francisco has presented various technical papers at important conferences and technical sessions.

AuthorsAcknowledgementsWe thank Pemex and Halliburton Energy Services Inc. for allowing us to publish this work and the related data. We also thank our colleagues in Halliburton for their contribution to this work.

ReferencesStrobbia, C., A. Zarkhidze, R. May, J. Quigley, and P. Bilsby, 2011, Model-based coherent noise attenuation for complex dispersive waves: 81st Annual International Meeting, SEG, Expanded Abstracts, 3571–3575.

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A Statistical Approach to Wireline Formation Testing Provides a Higher Level of Reservoir Understanding Waqar Ahmad Khan, Rojelio Medina, Diptaroop Chakraborty, Venkat Jambunathan, Sandeep Ramakrishna, Ron Balliet, Jim Galford, Luis Quintero - Halliburton Tony Gonnell, Connie L. Bargas, Ryan T. Murphy, Arthur H. Saller - Cobalt International Energy, Inc.This paper was prepared for presentation at the SPWLA 56th Annual Logging Symposium held in Long Beach, California, USA, July 18-22, 2015. Copyright 2015, held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors.

Abstract The oil and gas potential of the presalt carbonates of Brazil and West Africa has been the focus of significant recent exploration interest. The primary oil targets within the Kwanza Basin of West Africa are complex presalt carbonate reservoirs. In discovery wells, hydrocarbon fluid identification, porosity characterization, and permeability are necessary for robust resource estimates and as input data for a strategy to determine intervals for drillstem tests.

The challenges to formation evaluation, including hydrocarbon identification, are multifold. Complex distributions of pore geometries and reservoir quality are present in the formations. Light-medium native oil identification is complicated by oil-based mud filtrate invasion. The accurate determination of fluid volumes and permeability in this challenging environment requires a solution with a higher level of reservoir understanding.

A suite of advanced logging sensors, in addition to conventional measurements, are used to acquire a significant body of data for analysis, comparison, and calibration to laboratory fluid and core measurements. The presssure gradient and samples obtained from formation testing are crucial in determining the thickness, quality, and connectivity of the hydrocarbon zone and, in turn, the commercial feasibility of the well. In the presalt play, where rig costs can exceed USD 1 million per day, the ability to focus data collection on zones that will yield good formation tests is of significant value to the asset operator.

This paper outlines a method of facies classification based on nuclear magnetic resonance (NMR) data. This method, when combined with other log data, has shown encouraging results in terms of identifying facies which have a high probability of yielding tight tests. These intervals may be avoided to improve the overall efficiency of the pressure and sampling program. The method presented uses an integrated workflow, developed by the operator and service company, and enables a significant savings in rig time and, subsequently, overall formation evaluation cost while still acquiring critical information.

IntroductionThe west coast of Angola shares geological similarities with the east coast of Brazil, which contains presalt carbonates estimated to hold large quantities of hydrocarbons. The African and South American tectonic plates separated during the Early Cretaceous time. The Kwanza Basin shares similarities with the prolific Campos and Santos Basins of Brazil, and has been the target for presalt exploration by several IOCs and Sonangol. In the last few years, several exploration wells were drilled and evaluated in this basin. Fig. 1 shows select discoveries from the presalt reservoirs of Campos Basin in Brazil, as compared to the location of Cobalt’s Kwanza basin blocks at the time of deposition.

These presalt reservoirs pose multifold challenges for formation evaluation. Complex distributions of mineralogies, formation fluids, and reservoir quality are present in these reservoirs. Light-medium native oil identification is complicated by oil-based mud filtrate invasion. A suite of advanced logging sensors, in addition to conventional measurements, are used to acquire a significant body of data for analysis. The wireline log data are compared and calibrated to laboratory core measurements. Hundreds of feet of whole

presalt core were acquired. In addition, more than 500 rotary sidewall cores have been collected. Laboratory core measurements are beneficial to understanding the range of mineralogies and porosities present in these formations while laboratory testing of bottomhole fluid samples is critical for understanding the formation fluids. X-ray diffraction (XRD) analysis, thin section descriptions, scanning electron microscope (SEM) pictures, laboratory nuclear magnetic resonance (NMR), and specialized core analysis (SCAL) are used to calibrate logging sensor response for reservoir evaluation in these presalt carbonate wells.

A higher level of reservoir understanding is one of the key requirements for optimal well design, well placement, and field development. In the discovery wells, hydrocarbon fluid identification, porosity characterization, and permeability are necessary input data for a strategy to determine intervals for drillstem tests and robust resource estimates.

Fig. 2 shows some of the exploration blocks in the Kwanza Basin, along with discoveries made by Cobalt International Energy, Inc. and others.

Fig. 1. Location of Cobalt’s Kwanza Basin blocks, as compared to Campos Basin in Brazil at the time of deposition.

Fig. 2. Lease blocks of the Kwanza Basin with Cobalt and industry discoveries.

INTEGRATION OF NMR FACIES CLASSIFICATION AND FORMATION TESTING SAVES RIG TIME AND RESERVOIR EVALUATION COST

Cobalt LicenseCobalt DiscoveryCobalt ProspectCobalt Successful WellIndustry Discovery

Blocks 9, 20, 21Cobalt 40%(Operator)

Eni Operated

Conoco Operated

Conoco Operated

Statoil Operated Repsol Operated

MaerskOperated

35

36

37

38

21

22

23 9

Angola

0 16 ml

25 km

20

Baleia Park Area2.5-3.5 BBOE

Jubarte-1 well• Produced 14,500 BOPD• Assumed dry and not flow tested when originally drilled

Cobalt Operated Blocks

Atlantic Hinge Line

Oil Discovery

Well with Oil Shows

Cobalt Discovery

2014 Cobalt Prospect

Industry Well

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Fig. 3. Regional subsea geology of Angola and Brazil.

Regional GeologyFig. 3 shows the regional subsea geology comparing the Brazil presalt with the West Africa presalt reservoirs. The results of the exploration work and recent discoveries have proven that the salt layer is a highly effective seal. Deeper seals with multiple presalt reservoirs have been discovered, which confirms the existence of mature source rocks and self-sourcing reservoirs.

Wireline ProgramData acquisition in the wells included in this study consisted of acquiring a full suite of advanced logging technologies, including spectral gamma ray, multicomponent induction, density, neutron, cross-dipole sonic, NMR, geochemical elemental spectroscopy, electrical and acoustic borehole imagers, vertical seismic profiles (VSPs), and large-diameter rotary sidewall cores. At the time of this writing, the authors have wireline data from several wells, lab core data from one well, and some preliminary reservoir data from a second well. The authors have developed a workflow and a petrophysical model that integrates the core and log data. The interpretation of the advanced logging technologies, such as NMR and geochemical elemental data, are calibrated with the core data. In this paper, wireline logs and core data from three example wells are used to discuss two reservoirs as potential targets for wireline formation testing, drillstem tests, completions, and stimulation treatments.

Analysis with Wireline SensorsNMR analysis. There were several objectives for acquiring NMR data, including complementing the measurements from the traditional sensors. Although the density and neutron sensors must assume a single lithology to calculate an estimated porosity, an NMR sensor directly measures the fluid in the pore space without the need to assume a lithology. The basic information included total bound fluid volume and irreducible water volume microporosity, moveable fluid volume, and a permeability estimate. A multifrequency NMR tool was used, and data was acquired in two passes. One log pass used a simultaneous T1- T2 acquisition; the other acquired T2-diffusion information. The simultaneous T1-T2 pass was performed using six polarization times with a set of shorter inter-echo spacings. The T2-diffusion passes used a sufficient polarization time with four different inter-echo spacings. The goal of these acquisitions was to use the on-the-fly fluid typing capabilities of the tool on a moving measurement for an assessment of near-wellbore gas and oil volumes and a total water volume. The parameters for the acquisitions were selected referencing the acquisition used in the presalt carbonates of Brazil.

Many techniques have been used to attempt to describe the connectivity of pore space. Some techniques have been well documented using NMR data to relate NMR relaxation times to describe the pore size assuming a single fluid. In conventional clastic reservoirs, a reasonable assumption can

be made that increasing pore throat size follows increasing pore size, but in the presalt carbonates studied in this project, this may not be a valid assumption. The genetic complexities of carbonate reservoir formation can produce highly variable pore connectivity. The use of fractionalized porosities, as in conventional reservoirs, to understand moveable fluids left the authors with significant uncertainties. As part of the interpretation, an irreducible fluid cutoff technique was incorporated to fractionalize the porosity, as shown in Fig. 4.

During the early days of exploration, the authors looked directly at the quantity of moveable fluids vs. the quantity of irreducible fluids and MRIL-estimated permeabilities to help pick intervals for test points that would provide good mobilities through pore connectivity. The Timur-Coates NMR permeability equation was calculated in real time on the field plots and then updated to account for the new cutoffs selected during the post-processing interpretations. The expectation was for the Timur-Coates permeability model to provide indications of qualitatively good permeability with good rock

SagSaltSalt

Sag

Syn-Rift Syn-Rift

Ocean

Brazil PresaltReconcavo, Sergipe Alagoas,

Espirito Santo, Santos & Campos Basins

West Africa PresaltKwanza, Lower Congo, Gabon

2 Bbbl*discoveredonshore, Brazil

10-20+ Bbbl*Ultimate recoverable

in deepwater Santos and Campos

5 Bbbl*discovered

onshore/shelf,West Africa

*Sources: Wood Mackenzie and IHS

Jubarte Presalt Complex (Brazil, Campos Basin)

˜ 2.7 BOEPlay Openers (Kwanza Basin)

Cameia-1 and Bicuar-1Coast

Fig. 4. T2 cutoff technique applied to T2 distribution.

Incr

emen

tal φ

(p.u

.)

T2 (ms)

Bound Fluids Movable Fluids

Microporosity IrreducibleFluid Moveable Light Oil Water

SpreadingCenter

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quality to directly indicate which zones would be conducive to formation testing. However, some zones in which the NMR permeability model showed good permeability were zones that proved to be slow building while testing with low mobilities. Because of the subjective interpretation inherently present when selecting a cutoff and because of the way in which carbonate porosity is formed, the authors determined that a technique was needed that was more straightforward and not subject to a cutoff interpretation.

An output was needed from the NMR data that was less interpretative, would still use and honor each T2 distribution data point, and could be used generically for all future wells. With this mindset, it was decided to use a technique based on rock type classification (Marzouk et al. 1998). Although this technique is more focused on providing pore size outputs, this project required a simpler technique. Although Marzouk’s technique shows how to divide pore size outputs into eight porosity facies, for this work, it was modified to classify NMR relaxation. Using a ternary diagram technique similar to that described in Marzouk’s work, Fig. 5, shows how a T2 distribution would be divided into eight NMR relaxation facies.

Fig. 5. NMR relaxation facies ternary diagram.

A T2 distribution data point with most of the porosity measured from early or fast T2 relaxation times would be classified in Facies 1, and a T2 distribution data point with most of the porosity measured from late or slow T2 relaxation times would be classified in Facies 8. Thus, the facies range from 1 to 8. The result of using this technique provided an output shown in Fig. 6 in which higher moveable fluid/irreducible fluid ratios can be easily identified. The output of the eight NMR facies would be a direct input into the statistical approach described later in this paper. Although this method provides a unique approach to fractionalizing a T2 distribution,

studying both cutoff methods, fractionalized porosities in conjunction with the NMR facies, strengthens the ranking of intervals that are better for testing. As the Kwanza Basin project progressed, this NMR facies classification became an important tool that was available for real-time wireline formation testing and sampling.

Because different fluids in the sensitive volume will also change relaxation times, it is necessary to be very cautious when trying to describe pore connectivity with NMR alone. For this reason and because of the oil-based mud used to drill these wells, the direct use of Marzouk’s pore size technique could be misinterpreted by changes in relaxation times based on the mixing and varying quantities of fluids in the sensitive volume. Eq. 1 is used to describe T2 relaxation:

(1)

Where: T2,app means apparent T2 relaxation, T2S means surface relaxation, T2B means bulk relaxation, and T2D means Diffusion. Surface, Bulk, and Diffusion are the three relaxation mechanisms.

The same rock with the same permeability and pore connectivity could result in different T2 relaxation times, based on whether the sensitive volume contains oil-based filtrate, native oil, water, or a mixture of these three fluids. It is assumed that regardless of the actual fluid in the pore space or

the actual size of the pore itself, our technique will provide straightforward outputs of intervals with late T2 relaxations. A range of fluids will create different T2 relaxations, based on their bulk relaxation as well as their diffusivity; consequently, the direct use of the Marzouk’s pore size technique could be misinterpreted. With that mindset, carbonate porosity variations again came into play. Isolated porosity would also be classified in NMR Facies 8 and gives the impression of connected pores, which is known to not be the case. Although this technique simplified the overall NMR output, more data had to be examined to integrate into this statistical approach. Integrating borehole image analysis and interpretation provided additional information that helped with selecting test points.

Image analysis. The introduction of high-resolution imaging technology makes the study of the features observed on the borehole wall more explicit. High-resolution resistivity and acoustic images make it possible to identify the fractures in the formations and to precisely pick their dip angle and orientation. The imaging technologies are very advanced and provide very high-resolution images. Conversely, these images have variable sensitivity to borehole rugosity and mud. For example, not all drilling conditions or mud systems are ideal for all microresistivity imaging tools. The acoustic imager or ultrasonic imager has a better level of accuracy in mud systems, which are not very conducive for microresistivity imagers, but it can be affected more by borehole rugosity. In oil-based mud environments, the probable open fractures (conductive to fluid) would appear bright on the microresistivity image as a result of the resistive mud filling in the aperture. At the same time, the healed or mineralized fractures would appear bright, being more resistive than the matrix. To distinguish the open fractures from the mineralized fractures, the acoustic image must be examined, which provides the acoustic amplitude (impedance) and traveltime. Fractures appearing to be resistive (lighter) on the electrical imager and showing lower amplitude (darker) on the acoustic imager could be possible open fractures. Fig. 7 shows an example of a possible open fracture from one study well, identified using both microresistivity and acoustic image information. Therefore, it is important to combine the different tool sensors and interpretation techniques to identify and characterize the fractures definitively in order to propose the correct intervals to test and define initial field development.

Fractures are among the most common discontinuities observed in rock exposures. In nature, fractures can be broadly classified as extension or tensile fractures

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and shear fractures. The former preferentially occur in certain mechanical layers approximately perpendicular to the mechanical layer boundaries, whereas the latter show a high degree of clustering that can be independent of mechanical layers. Shear fractures are often at an oblique angle, rather than perpendicular, to the layer boundaries and commonly cut across bedding.

Natural fractures in reservoirs are of critical significance because the fracture permeability can enhance productivity and impact conformance.

Therefore, the knowledge of the fracture locations and their characteristics is of primary importance to understand the reservoir and for the well completion design and field development. Microresistivity and ultrasonic image logs are most commonly used to identify fractures in the subsurface. This paper includes a discussion of an interpretation technique that integrates conventional openhole logs, NMR, and borehole images to identify ideal zones for testing. This work indicates that fracturing, when present in the study wells, is typically comprised of short localized shear fractures rather than

Fig. 7. 1:10 scale image of the borehole imagers showing a possible open fracture.

large tensile fractures. In this paper, all fractures discussed are short localized shear fractures unless specifically stated to be tensile fractures. Fig. 8 illustrates the fracture direction in three intervals.

Natural fractures were identified and characterized into the following types:

• Resistive/low-amplitude fractures. Thesefractures are identified from the resistivity and acoustic image. They appear as light-colored traces (high resistivity) across the resistivity image and dark-colored traces (low amplitude) on the acoustic image. They are present as near-complete to complete traces across the plane of the image. Because of the presence of nonconductive mud/filtrate in the borehole, these fractures are most likely to be open at the wellbore and conductive to fluid.

• Partial resistive fractures. These fracturesare identified from the resistivity and/or acoustic image. They appear as light-colored traces (high resistivity) across the resistivity image and dark-colored traces (low amplitude) on the acoustic image. They are present as partial traces across the plane of the image. Because of the presence of nonconductive mud/filtrate in the borehole, these fractures are most likely to be open at the wellbore and conductive to fluid.

• Conductive fractures. These fractures areidentified from the resistivity image. They appear as dark-colored traces (low resistivity) across the resistivity image and, if observed, they appear as dark-colored traces (low amplitude) on the acoustic image. They are present as partial or near-complete to complete traces across the plane of the image. Because of the presence of nonconductive mud/filtrate in the borehole, these

Fig. 8. The strike of possible open fractures and their density distribution shown for three reservoir intervals.

Depth Range: 4949 - 4952 m

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fractures are most likely to be closed/clay-filled at the wellbore and nonconductive to fluid.

• Fault/microfault. Fractures that showed a noticeable displacement across the plane are identified as faults, and are identified from the resistivity image.

Fracture density analysis. The manually picked fractures are used to calculate the fracture density in a 0.5-m window, with the value representing the number of fractures per 0.5 m.

Fractures that are most likely open at the wellbore are used. These included the resistive fractures, partial resistive fractures, and only those faults that have a resistive appearance on the electrical image, but not the conductive fractures.

An important possibility that cannot be overlooked before the open fractures are identified from the image data is that the fracture might have spalled at the wellbore interface, but an inch or two into the formation, it may be completely closed and have no aperture. The fracture density technique takes into consideration a quantitative number, rather than individual fractures at specific depths, therefore statistically reducing the uncertainty. To identify the open flowing fractures more accurately, the study needs to be integrated with full-wave acoustic data, which is outside the scope of this paper.

Formation Testing and SamplingThe advent of modern formation testing tools, primarily wireline, occurred in the early 1990s. Depending on the configuration of the testing program, the probe dimensions varied from ½ to 1 in. in diameter, with some probes approaching the 2-in. mark. In addition to the circular probes, there are oval and focused oval probes.

Formation testing and sampling in this study utilized a tool which has been run in various probe configurations in the wells tested. The latest tool configuration uses two oval probe sections for pressure and sampling purposes and has proven to be the best suited to the wellbore environment in these reservoirs. Proett et al. (1999) explains the various configurations possible with the formation tester tool.

For fluid identification purposes, the formation tester tool is configured with two independent sensor bodies. The primary measurements for one of the sensor bodies include fluid density, temperature, resistivity, and capacitance. The importance of

accurate density measurements is reflected in the number of applications in which in-situ density is essential, such as pressure gradient analysis, fluid contacts, zonal compartmentalization analysis, delineation of oil-water transition zones, contamination analysis during sampling, and fluid identification analysis for immiscible fluids. The second assembly is fitted with a sensor that enables the fluids to be characterized downhole in real time. In this assembly, light shines through downhole fluids to the sensors. Each sensor is programmed to recognize the chemical nature, or optical fingerprint, of a specific fluid component, such as methane, ethane, propane, aromatics, saturates, or water (Jones et al. 2012). Although the conventional sensors are helpful in calculating downhole contamination, the downhole fluid characterization takes it a step further and helps to characterize the fluid in real time.

For formation pressure measurements, the tool uses a quartzdyne gauge placed at an offset from the probes, dependent on the tool configuration. Along with the quartzdyne gauge, strain gauges are also used across the various probes.

A primary challenge in the testing of highly heterogeneous formations has been the identification of a key variable to minimize the occurrence of tight tests and maximize the possibility of a good test thus optimizing the formation testing and sampling program. Because of the heterogeneity common in carbonate reservoirs, blindly performing a formation testing program puts a higher probability of placing the probe in a location that will result in a tight test.

The methods described here revolutionized the testing program used in the presalt Kwanza Basin carbonates. The key is provided by coupling the

facies determined from the relative relaxation of the T2 curve with the fracture density (running average of fractures computed per 0.5-m length) to identify zones having a high chance of yielding tight tests, and in turn, avoiding testing such zones.

Field StudyThe presalt Kwanza Basin is located offshore West Africa. In addition to the challenges associated with reservoir characterization, the expense of deepwater rig rates requires continual optimization of the data-acquisition program. Steps were taken to improve the operational efficiency and to optimize the formation testing and sampling program. The focus of this paper is the optimization of the formation testing program with the goal of maximizing the probability of obtaining a good test.

Three wells were studied in detail for this paper: (1) A Reference Well had already been logged, and some preliminary lab data on reservoir properties were available at study inception; (2) Blind Well #1 was logged during the development of the methods applied here and served as a validation for the predictive workflow; and (3) Blind Well #2 logging operations were a direct application of the method in the field. Log data from the Reference Well was thoroughly analyzed to determine trends or patterns in the data to indicate the good tests and tight tests.

It was clear from the data analysis that tests performed in NMR Facies 1 and 2 always resulted in tight tests. Fig. 9 shows the testing points for the Reference Well. A total of 10 tests were attempted for NMR Facies 1. A test usually required approximately 10 minutes. The elimination of these tests would result in a substantial time savings. For this study, measurements obtained from a variety of different logging tools are assessed. Elemental data

Fig. 9. Snapshot of all the tests attempted in the Reference Well.

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obtained with a geochemical tool and derived mineral volumes, such as calcite and dolomite, did not provide a clear-cut valid test discriminator. Although clay content had shown a definite trend, i.e., increasing amounts of clays led to a greater probability of tight tests, a definite cutoff was not evident from one well to another. Acoustic properties determined from the sonic tool also did not show a definitive trend.

Fig. 10 shows a diagram of all testing performed on Blind Well #1 to prove the concept. Facies 1 and 2 failed to show a valid test as expected.

Fig. 11 and Fig. 12 show Blind Well #1 zoned into two distinct sections, “Reservoir A” and “Reservoir B.” After zoning the well into different sections, most of the tight tests appear to be located in Reservoir B. Facies 4, 5, 7, and 8 produced good tests in Reservoir A, with some tight tests observed across Facies 7. By comparison, Facies 7 and 8 have produced only tight tests in Reservoir B. The facies classification is based only on the relative proportion of the early, middle, and late time relaxations, and does not take into account the absolute porosities. The tight tests can be attributed to a number of factors, such as low permeability, damage induced while drilling owing to mud particle invasion and/or bit metamorphosis, and/or carbonate heterogeneity.

Another independent variable considered was fracture density. Zones having a high relative fracture density can be more conducive to obtaining good-quality pressure measurements in less time since they are less affected by drilling-induced formation damage such as mud particle blockage. This is important as perforating or stimulating past near-wellbore damage is not an option prior to openhole wireline logging.

Fig. 13 and Fig. 14 show the two different sections in Blind Well #1 overlaid with fracture density. The fracture density indicates the amount of fractures per unit length. This variable enables the quantification of the fractures observed in the image data and target sections showing the highest fracture density.

Overlaying the fracture density with the NMR facies helps to explain some of the anomalies. The fracture density has been divided into bins of 0.5. Bin 0-0.5 corresponds to the bin with the lowest fracture density possibly having a relatively higher extent of formation damage. Fig. 13 shows that a fracture density as high as 1.5-2.0 has been observed in Reservoir A in Blind Well #1.

Fig. 10. Snapshot of all the tests attempted in Blind Well # 1.

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Fig. 14 shows the fracture density overlaid with NMR facies in Reservoir B as seen in Blind Well #1. The relatively high amount of tight tests observed is possibly due to the relative low porosity as compared to Reservoir A, which appears to have better rock quality in this well. This may not necessarily hold true across the field.

Fig. 15 shows the result for Blind Well #2. The evaluation program for this well included full implementation of the methods described in this paper to minimize the probability of unsuccessful formation tests. The lack of tight tests in this well clearly demonstrates the effectiveness of the workflow.

Conclusions• The method of integrating NMR with image

data introduced in this paper greatly helps in the optimization of the wireline-formation testing program.

• Because of the highly complex nature of carbonates and multifaceted challenges in characterizing them, the integration of all available information is necessary to fully understand the reservoir.

• The workflow is reservoir-dependent, and care must be exercised before adopting the workflow for different reservoirs.

• The method presented enables significant savings in rig time and subsequently reduces overall formation evaluation cost.

Fig. 13. Complementing NMR facies with fracture density in Reservoir A.

Fig. 14. Complementing NMR facies with fracture density in Reservoir B.

Fig. 15. Snapshot of all the tests attempted in Blind Well #2. Complementing NMR facies with fracture density led to an efficient formation testing program with only one tight test.

AcknowledgementsThe authors would like to thank the management of Cobalt International Energy, Inc., Sonangol Pesquisa e Produção, and Sociedade Nacional de Combustíveis de Angola - Empresa Pública for the release of this data.

Thanks are also due to several people at both Cobalt International Energy and Halliburton for their input and valuable advice in using advanced logging technologies to understand and evaluate the presalt carbonates of the Kwanza Basin.

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ReferencesJones, C.M., Atkinson, R., Chen, D., Pelletier, M., Perkins, D., Shen, J., and Freese, B., 2012, Laboratory quality optical analysis in harsh environments. Paper SPE-163289-MS presented at the SPE Kuwait International Petroleum Conference and Exhibition, Kuwait City, Kuwait, 10-12 December.

Marzouk, I., Takezaki, H., and Suzuki, M., 1998, New classification of carbonate rocks for reservoir characterization. Paper SPE-49475-MS presented at the Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, UAE, 11-14 November.

Proett, M.A., Gilbert, G.N., Chin, W.C., and Monroe, M.L., 1999, New wireline formation testing tool with advanced sampling technology. Paper SPE-56711-MS presented at the SPE Annual Technical Conference and Exhibition, Houston, Texas, USA, 3-6 October.

Waqar Khan is a reservoir engineer with the Halliburton Deepwater Reservoir Solution Center. During his time in the industry, he has worked extensively on both offshore and onshore reservoirs. Currently, Waqar

is focused on global deepwater projects specializing in pressure testing and sampling, production management, and reservoir simulation. He has experience working in deepwater reservoirs in the Gulf of Mexico, Angola, the Falkland Islands, and Brazil. Waqar holds an MS degree in petroleum engineering from Texas A&M University.

Rojelio Medina works as a consultant for petrophysics and log analysis for Halliburton’s Formation and Reservoir Solutions (FRS) group in Houston. In FRS, Rojelio has worked in many disciplines of petrophysics,

including NMR interpretations. Rojelio joined Halliburton in 2006 and worked as a field engineer before joining FRS in 2010. Rojelio received his BS degree in geology from Texas A&M University – Kingsville in 2005. Rojelio is a member of SPWLA and SPE.

Diptaroop Chakraborty is a geologist with the Formation and Reservoir Solutions team in Halliburton Angola. He is involved in openhole formation evaluation, working primarily with borehole imaging technologies and

solutions. He has an MS degree in applied geology from the Indian Institute of Technology, Roorkee, India and a BS degree in geological sciences from Jadavpur University, India.

Authors

Venkataraman Jambunathan is a petrophysicist with the Deepwater Reservoir Solutions Center in Halliburton. He is involved in openhole and cased-hole formation evaluation, production logging,

formation testing, and sampling. He has an MS degree in petroleum engineering from the University of Oklahoma at Norman and a BS degree in mechanical engineering from Visvesvaraya National Institute of Technology, India.

Sandeep Ramakrishna is a petrophysicist and the manager of the Deepwater Reservoir Solutions Center for Halliburton in the Wireline and Perforating product service line. He has more than 16 years of

experience in the industry. Sandeep has been actively involved in the development of techniques to analyze conventional and unconventional reservoirs. He holds an MS degree in petroleum engineering from the University of Tulsa, Oklahoma and a BSc degree in geology from the University of Pune, India. Sandeep is a member of SPWLA, SPE, and AAPG.

Ron Balliet is the global NMR product champion for Wireline and LWD. Ron began his career in 1984 as a wireline field engineer and joined NUMAR in 1991, working with oilfield NMR in several locations worldwide, including

a position as regional operations manager for the North Sea, Middle East, and West Africa. Since 1997, he has held various positions with Halliburton in West Africa and the USA. Ron has BS degrees in geophysics and geology (1984) from the Institute of Technology at the University of Minnesota. He is a member of SPWLA and SPE.

Jim Galford is a chief scientific advisor in the LWD and WL Sensor Physics group at Halliburton. Previously, he was a member of the Formation Evaluation Technology group, and prior to that, he worked

on nuclear magnetic resonance (NMR) petrophysical applications and interpretation. He holds a BS degree in physics from West Virginia University. Jim has written several technical papers on various logging applications for conventional nuclear and magnetic resonance imaging logs. In addition, he has contributed to a number of patents related to conventional nuclear logging methods and NMR logging applications. Jim is a member of SPWLA and SPE.

Luis F. Quintero is global advisor – production management for Halliburton’s Formation and Reservoir Solutions, based in Houston. Prior to joining Halliburton, he worked as president and technical leader

of Oilfield Development Specialists (ODS); and for a service company and PDVSA. Luis obtained a BS degree in electronic engineering from Universidad Simon Bolivar (Venezuela), and MSc and PhD degrees in petroleum engineering from Louisiana State University. Luis started his career in 1984 as a wireline logging engineer in India (offshore and onshore). He later advanced to positions in petrophysics, reservoir engineering, business development, financial analysis, project management, and production management. He has been responsible for reservoir optimization plans for fields in Colombia, Guatemala, Kazakhstan, Uzbekistan, Turkmenistan,

Azerbaijan, Turkey, Bulgaria, Romania, Hungary, and Poland. Luis was also the lead for production/reservoir evaluations, operations support, and training for fields/clients in Ukraine, Bahamas, USA (Texas), Libya, Colombia, Indonesia, South Africa, and India. Luis’ numerous publications span from permeability in carbonates using NMR, to variable “m” using electromagnetic tools, to coiled tubing and production logging. Luis is the current vice-president technology of SPWLA and a recipient of the Medal of Honor for Career Services of SPWLA.

Tony Gonnell is the senior petrophysicist for Cobalt International Energy, Inc. for West Africa. He joined Cobalt in 2012 after holding similar positions at Hunt Oil, Oxy O&G, Devon, and Southwestern Energy. He began

his career in 1977 with Schlumberger as a field engineer. In his 38-year career, Tony has experience in log evaluation and wireline operations in most US and Canadian oil provinces and on every continent. Tony has a BSc in physics from the University of North Texas and is a member of SPE and SPWLA.

Connie Bargas is vice president, chief reservoir Engineer for Cobalt International Energy, Inc. She previously served as subsurface manager for the Angola Cameia development project and worked as

a reservoir engineer supporting exploration, appraisal, and development activities in Angola and deepwater Gulf of Mexico. Prior to joining Cobalt in 2008, she held numerous reservoir engineering positions at Amoco and BP, including reservoir engineering advisor and lead reservoir engineer on the deepwater Gulf of Mexico NaKika and Atlantis development projects. She has 35 years of oil and gas experience and received BS degrees in petroleum engineering and chemistry from the New Mexico Institute of Mining and Technology.

Ryan Murphy received a degree in geology from Western State College of Colorado in 2000 and an MS degree in geology from the Mackay School of Mines, University of Nevada, Reno in 2004. He has primarily worked in

regional to prospect-scale exploration settings from Africa to the Gulf of Mexico in past roles with ExxonMobil and Hess Corporation. In 2012, Ryan joined Cobalt International Energy, Inc., where he has worked as an exploration geologist and exploration manager for West Africa and is presently the appraisal manager for West Africa and the Gulf of Mexico.

Art Saller is a stratigrapher and carbonate sedimentologist working for Cobalt International Energy, Inc. in Houston. He went to school at the University of Kansas, Stanford, and Louisiana State University. Art worked

for Cities Service/Occidental, Unocal, and Chevron prior to joining Cobalt in 2012.

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Optimized Fracture Stage and Perforation Placement in Horizontal Wells Using a New Calibrated Pulsed-Neutron Log WorkflowJeff Dahl, James Samaripa, and John Spaid, Devon Energy; Erek Hutto, Dan Buller, Bill Johnson, and Chris McIlroy, HalliburtonThis paper was prepared for presentation at the SPE Annual Technical Conference and Exhibition held in Houston, Texas, USA, 28 -30 September 2015.Copyright 2015, Society of Petroleum Engineers. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

Abstract Evidence continues to mount to indicate that the geometric placement of fracture stages and perforation clusters in horizontal wells results in variable well production, with many clusters contributing little or no production. Any engineered completion design should require stages to be segregated by similar petrophysical and mechanical properties. The authors propose to reduce the cost per barrel of oil equivalent (BOE) and to improve estimated ultimate recovery (EUR) by using a novel log-derived completion method to better select perforation clusters and stage location to provide better fracture placement.

A low-risk, pumped-down, cased-hole pulsed-neutron log (PNL) is used after the well is cemented before completion. Using readily available geosteering software, the geologic projection of vertical well log measurements and the interpreted formation properties along the horizontal well enable a rigorous calibration method for PNL interpretation. Inelastic pseudodensity, neutron porosity, and resistivity-sigma calibrations can then generate a cased-hole triple combo. Elemental yields for silica, calcite, and potassium are used with additional clay inputs for a basic mineralogy interpretation. These inputs, within a specialized workflow, calculate a “production index” and “frac index” used to generate custom staging designs.

Experience in a major unconventional play has shown a dramatic reduction in the number of stages and the completion cost per well. In addition, data from producing wells, using a software-derived stimulation design, has been matched to geometrically staged wells in the area. The addition of PNL data to interpret the position of the lateral well has been observed to reduce uncertainty when compared to the logging-while-drilling (LWD) gamma ray (GR) alone. The completion results for stages also provide good evidence that the overall efficacy of the stimulation treatment was increased by the perforation placement. The conclusions from this work show substantial completions cost savings per well while maintaining overall EUR in a difficult unconventional shale play. Based on pressure observations during stimulation, it is believed that stimulation efficiency has been increased. Using fewer stages to target the more productive rock and perforation clusters to target the sweet spots for stimulation has provided a substantial cost/BOE reduction.

Although the technology for using a PNL log in the horizontal well has been attempted previously, there was not the benefit of a rigorous calibration method. The geologic projection of vertical wells is a novel approach to calibrate thousands of feet of logged PNL data. In addition, the custom staging design uses a novel, unbiased approach to select the optimum stage and perforation placement to minimize completions cost while maximizing productivity.

IntroductionThe optimization of stage and perforation placement requires an understanding of the petrophysical and mechanical properties along the lateral well. To evaluate these properties, operators should consider how to acquire the data needed to obtain an accurate and reliable interpretation. Some important factors to consider include price, risk, and reliable data that can be integrated into a repeatable petrophysical workflow. The industry has largely avoided logging-while-drilling and wireline openhole technologies because of the cost associated with additional rig time and the traditional risks associated with openhole logging. Although previous work has identified successful workflows for cuttings analyses to optimize staging (e.g., Buller et al. 2014), continuous log resolution data to complement the cuttings is still needed. These issues have led to a

majority of lateral wells with no data other than an LWD GR.

Earlier papers have correctly identified PNL as the optimal solution to determine petrophysical and mechanical properties along the lateral well (Buller et al. 2010). However, previous methods required the calibration of the PNL to the openhole dataset on the same well. This requirement led to the need to acquire pulsed-neutron and openhole data on either vertical or horizontal wells with similar casing and hole size. This data must be acquired regularly to maintain the calibration within an acceptable distance to the lateral well, which increased the overall data acquisition cost for the wells in which logging the additional pulsed neutron for calibration was necessary. The older calibration process of using a vertical well with both pulsed-neutron logs and openhole logs has also some added uncertainty in the curve prediction from the calibration well to the lateral well.

The authors propose that the low-risk, pumped-down PNL continues to provide the most cost-effective and reliable solution for deriving continuous petrophysical and mechanical properties in the lateral well for optimized completion. However, the addition of a workflow that uses geosteering software to project nearby vertical logs along the lateral well enhances the calibration method. This enhancement removes the need to regularly add a PNL to select vertical wells. In addition, this method reduces the uncertainty in the PNL calibration and interpretation.

Pulsed-Neutron Analysis - Theory and Definition The cased-hole pulsed-neutron tool is a multidetector device that can induce high-energy neutrons. The detectors on the device measure the spectral energy and decay time of the induced GRs from the formation, casing, and cement. Various pulsed-neutron curves are generated from the normalized GR spectrums measured, as shown in the previous methods (Buller et al. 2010). The interpreter may then use either deterministic (including fuzzy logic or regression analysis) or nondeterministic (such as neural networks and self-organizing maps) curve prediction methods to predict resistivity, neutron porosity, and bulk density from the pulsed-neutron curves generated. This interpretation process requires some understanding of the PNL curves.

Inelastic Initially, the high-energy neutrons generated inelastically collide with elemental nuclei in the

LOW-RISK, PUMPED-DOWN PNL FOR COST-EFFECTIVE COMPLETIONS IN LATERAL WELLS

43

formation. The specific energy level of the GRs produced in this higher range is related to the element involved in the collision and the energy level of the bombarding neutron. These inelastic count rates and ratios between detectors are related to formation bulk density properties (Quirein et al. 2005). The industry has used the inelastic count rate ratio (RIN), the hydrogen index corrected counterpart (RINC), and the density index (RHOI) in the derivation of a bulk density curve (Jacobson et al. 2004). Previous studies show that large flasked bismuth germinate (BGO) detectors provide improved counting efficiency and much better sensitivity to the higher energy gamma rays encountered when compared to their sodium iodide (NaI) counterparts (Stromswold 1980 and Galford et al. 2009). This improved efficiency and sensitivity is extremely desirable to derive reliable bulk density calculations.

Capture As the neutrons continue to collide, their energy levels (velocities) reduce; they also have elastic collisions where energy is transferred to the nucleus, and the neutron continues to slow until it reaches thermal speeds (thermalization). This later time thermal capture spectrum generates a capture count, and its associated capture count ratio from different detector spacings (RNF) is traditionally used to derive neutron porosity.

Sigma After the thermalization of the neutron, successive interactions with atoms quickly lead to its capture. The capture cross section of the nuclei determines the decay rate of the number of thermal neutrons. This capture cross section (sigma) strongly correlates with the amount and type of fluid in the formation, similarly to conductivity. Curve prediction methods use sigma to derive resistivity for this reason.

Pulsed-Neutron-Based Completion Optimization - MethodThe method used to optimize stage and perforation placement requires a minimum dataset to build consistent petrophysical and mechanical models. In this study, the pilot or offset well contained, at a minimum, a resistivity, density, neutron porosity, density photo-electric (PE), natural or spectral GR, and preferably a dipole acoustic log. This method does not require the addition of a cased-hole PNL in the vertical well. The lateral application well contained a minimum of a directional survey, LWD GR, and PNL in the capture and/or inelastic mode. A separate pass with the pulsed-neutron tool in passive mode measured spectral natural GR, which improved the interpretation by providing potassium, thorium, and uranium yields.

This program optimally acquired the pulsed-neutron data after the well was cemented. The operation typically used pumped-down conveyance to minimize cost and risk; however, wireline tractoring is also an option. This is the minimum dataset required to derive an unbiased perforation and stage placement design from petrophysical and mechanical properties.

Vertical Pilot or Offset InterpretationLike most reservoir development programs, the team spent time, energy, and capital acquiring accurate subsurface information in the form of seismic surveys, LWD or wireline logs, core analysis, and other methods. This process included developing sufficient, dependable, repeatable models of volumetrics. The volumetrics included clay volumes, quartz, carbonate, and other minerals that may significantly affect empirical porosity and saturation results. In the source rock interval, the interpreters derived the solid hydrocarbon component, kerogen, to correct porosity. Finally, the petrophysicists derived the core-calibrated relative volumes of fluids (water and hydrocarbon) occupying the pore space.

Log data alone does not provide a unique volumetric solution. The petrophysicists built models using the best available core analyses, such as X-ray diffraction, pyrolysis, and GRI-analysis derived porosity and permeability. In a field-wide petrophysical program, a team must develop rigorous processes and procedures for the interpretation and propagation of petrophysical properties. The petrophysicists used these methods to ensure the most accurate petrophysical and mechanical properties interpretation of vertical log data.

Within this context, the evaluation produced for this procedure included, at a minimum, the following:

• Conventional log-driven mineralogy normalized to 100%, including total wet or dry clay volume and principal matrix constituents of quartz and calcite/carbonate, kerogen, effective porosity, and fluid volumes.

• Closure pressure gradient using a rock model that at least assumes transverse isotropy with a vertical axis of symmetry (TIV).

• Young’s modulus- and Poisson’s ratio-based brittleness, as well as mineralogical brittleness. In addition, recent papers have shown the value of examining brittleness correlations to neutron porosity as a method for brittleness derivation (Jin et al. 2014). Because a pulsed-neutron tool is the principal dataset in the lateral well, this was also examined.

This list ensured sufficient information for lateral well interpretation and calibration. The software- derived engineered completions design must use this information to determine stage and perforation placement.

Lateral Application Well Pulsed-Neutron CalibrationAfter the interpreter built the required petrophysical models, the operator drilled the lateral well using, at a minimum, an LWD GR. Next, the operator cased the well and removed the drilling rig. Wireline operations then conducted two passes of the pulsed-neutron tool. The engineer ran the first pass in passive mode to record the spectral natural gamma ray, which provided the relative constituents of potassium, uranium, and thorium. The engineer ran the second pass in active mode at a maximum of 10 ft/min; this pass provided the neutron-induced spectral gamma data.

After acquiring the data, the petrophysicist used geosteering software to correlate the lateral well logs to those in the vertical pilot or nearby offset. In this process, the software projected the vertical data along the length of the lateral well, which is subsequently referred to as “projected logs.” The petrophysicist used the lateral well pulsed-neutron capture ratio with the projected neutron porosity, inelastic ratio with the density, and sigma with the resistivity to improve the geosteering interpretation.

At this stage, the petrophysicist has lateral well pulsed-neutron logs and geosteering projected logs. Using petrophysical software and curve prediction techniques, the pulsed-neutron pseudo-openhole logs (pseudologs) were derived. The authors examined deterministic and stochastic methods and concluded that deterministic methods, such as regression analyses, work sufficiently well to derive excellent resistivity, density, and neutron porosity pseudologs.

The petrophysicist used calcium, silicon, and potassium yields, as well as sigma and GR potassium and thorium to derive a mineralogy model, as described by Jacobson et al. (2009). This model was calibrated to the projected mineralogy interpretation. This PNL-derived mineralogy and the pseudologs were sufficient to derive a volumetric PE calibrated to the projected PE.

Lateral Application Well Petrophysical and Mechanical InterpretationThe authors applied the petrophysical models to the pseudologs to interpret mineralogy, porosity, and saturation. Two methods were then evaluated

44

LOW-RISK, PUMPED-DOWN PNL FOR COST-EFFECTIVE COMPLETIONS IN LATERAL WELLS

to derive the principal mechanical properties of brittleness and closure stress. The first method directly solved for these curves using the projected logs to build curve prediction models. The second method used volumetric response equations for the compressional and shear traveltimes to derive these acoustic slownesses. From here, mechanical properties could be computed using traditional empirical methods. Both models agreed closely, and areas of interpreted high stress predicted stages that did not pump to completion as designed. These predicted stresses also closely correlated with the lateral projected logs.

Stage and Perforation Placement DesignThe authors used automated completion design software with the full petrophysical and mechanical properties interpretation. The purpose of this software is to maximize the use of the available information and data to engineer the process of stage and perforation cluster placement. To do this, the software generated two indices: the production index and the frac index.

An overall production index was computed as a weighted average from several user-selected quality curves, such as facies, brittleness, and effective porosity. Facies were calculated from mineral contents from the formation. The production index is used to quantify the relative quality and producibility of the rock surrounding the wellbore. Lower values indicated areas of reduced producibility. Two user-selected thresholds for the production index categorized the rock as good, marginal, or bad production quality.

An overall frac index was computed as a weighted average of several user-selected quality curves. In this case, the PNL-derived closure pressure gradient alone was found to be sufficient in the prediction of relative ease in fracturing and stimulating a stage. In the same way as the production index, two user-selected thresholds are used to categorize the rock as having good, marginal, or bad fracture quality.

As expressed in the software, the overall goal of computing both a production index and frac index is to group “like” rock into specific stages of “similar” stress.

Using best practices and user-driven constraints for staging and perforation placement, the software generated two custom designs. Staging was initially controlled by the production quality. The first design sought to optimize the staging only around the rock identified as good for both production quality and fracturability. The second design optimized staging

in good and marginal intervals, which yielded a design that provided greater coverage of the lateral well. The perforation placement was optimized to reduce the differential closure stress within a stage to below a user-desired limit.

Eagle Ford Case HistoryThe area of study is restricted to units within Lavaca county, Texas. At the writing of this paper, more than 20 wells have been stimulated using engineered completions with the described workflow. Drilling and completion costs ranged between USD 8 to 12 million. Traditional stimulation consisted of 200-ft geometric stages, which led to an average staging of approximately 25 stages per well.

The early user-driven parameters to constrain the design intentionally retained a conservative change from the original designs. Table 1 shows typical parameters used early in the program. The results from these designs reduced the number of stages in wells from approximately 25- to 30-stage geometric

Table 1 – Initial Optimized Completion Parameters in Lavaca County

Maximum stage length

Minimum stage spacing

Minimum perforation spacing

Minimum number of perforation clusters per stage

Maximum number of perforation clusters per stage

Maximum stress contrast allowed

Staging requirements

Name Description Value

Minimum stage length is half of the maximum

Space from the last perforation cluster in one stage to the first perforation cluster in the next stage

Minimum difference between two perforation clusters

May not always meet this parameter because of constraints from other parameters

Difference between the maximum stressed perforation cluster and the minimum

Only stage when production and frac indices are greater than the specified cutoff

400-450 ft

30 ft

30 ft

6

6

200-400 psi

Production index > marginal cutoff frac index > marginal cutoff

completions to 16- to 19-stage optimized completions. The stimulation savings in the early wells ranged from 35 to 45%. Production results for cumulative BOE were matched over a 200-day timeframe when compared to adjacent geometric stimulated wells.

In addition to the improvement in cost/BOE, in several cases, this method has led to a better understanding of well placement over the LWD gamma ray alone. It has also built a considerable library of data and results that will be valuable in both future planning and look-back studies. The following sections provide a walkthrough of a typical evaluation with associated results and conclusions.

Vertical Eagle Ford WellRigorous methods are essential to the success of any optimized completion strategy. Each step in the process can potentially propagate uncertainty and error if petrophysical principles are not carefully applied. The first step, and arguably the most important, is the development of calibrated

Pilot Well

Fig. 1. Petrophysical results of the pilot over the intended target.

45

petrophysical models in vertical science wells. Source rock analyses must apply rigorous petrophysical models that correct for the clay content and the solid hydrocarbon (kerogen) component.

This case study presents two sets of data. The first set is the pilot data that covers the intended target of the lateral well. The second set is the lateral wellbore data. In the pilot, the operator acquired spectral gamma, resistivity, neutron porosity, density, and dipole acoustic data. Using models built for the area, the petrophysical team produced the results that assisted in calibrating and interpreting the PNL in the lateral well. Fig. 1 shows these results.

The results of the model show a strong correlation between the anisotropic stress gradient and the clay volume. Entering the primary input curves into the curve prediction techniques, a stress gradient model with an R2 of 0.932 was produced (Fig. 2). Similar results were achieved for brittleness.

Fig. 3. Interpreted geosteering using LWD gamma ray only.

Fig. 4. Raw pulsed-neutron measurement results.

Fig. 5. Reinterpretation of lateral well using pulsed neutron with pilot data.

Fig. 2. Predicted stress vs. measured stress using principal components that will be available in the lateral well.

Mea

sure

d St

ress

- pp

ft

Compare PlotPredicted Stress / Measured Stress

Active Zone: 3 Zone C

Zone(2) Zone B(3) Zone C(4) Target

Predicted Stress - ppft216 points out of 216

Lateral Target WellThis section provides information about the geosteering projection, pseudolog calibration procedure, lateral well interpretation procedure, and optimized completion design for the lateral target well.

Geosteering Projection After the pilot drilling and evaluation processes, the operator kicked off a lateral well toward the intended target. The geosteering program consisted of an LWD gamma ray measurement. Afterward, the interpreter, using the LWD and pilot data, interpreted the well to be placed as shown in Fig. 3. The lateral well appeared

in one interval to exit the intended target and enter into Zone C. Interpretation was difficult in this case because of the narrow range of gamma ray in the interval of interest and the larger signal-to-noise ratio present in the LWD gamma measurement.

The well was then cased, and the rig was removed. After a fracture injection test (DFIT), the pulsed-neutron tool was pumped down, and two separate passes were logged. Fig. 4 shows the raw results of spectral KUTh gamma ray and sigma passes. In the last third of the lateral well where LWD total gamma ray exhibits no drastic changes; the pulsed neutron indicated that the lateral well had again exited the intended zone. A reinterpretation of the lateral well using pulsed-neutron data as additional information yielded the results shown in Fig. 5.

This reinterpretation produced projected logs. The projected logs are defined as the correlated well logs from the offset well into the horizontal well and represent the log values that would have been measured or evaluated at that particular point in the lateral well. This method assumes lateral homogeneity and accurate interpretation of the location of the lateral well in relation to the geologic marker beds. Because of the difference in resolution between the vertical data, survey data, and lateral pulsed-neutron measurements, the projected logs should be considered to be an approximation. However, the results are sufficient for the purpose of calibrating the pulsed-neutron petrophysical results.

Pseudolog Calibration Procedure Fig. 6 shows a comparison between the projected openhole

Zone A

Zone B

Zone C

TargetZone D

Zone E

Base Target

Zone B

Zone A

Zone CTargetZone D Zone E

46

LOW-RISK, PUMPED-DOWN PNL FOR COST-EFFECTIVE COMPLETIONS IN LATERAL WELLS

Fig. 6. Comparison of projected logs to pulsed-neutron measurements for revised projection.

Fig. 7. Crossplot comparison of density, neutron porosity, and resistivity for projected logs vs. pseudologs.

logs and the calibrated pseudolog results. The density photo-electric factor (PE) curve must be separately derived using curve prediction and/or elemental yields from the pulsed-neutron spectral measurement. These are principally potassium, silicon, and calcium yields that can be used to derive a pulsed-neutron-based mineralogy for volumetric PE curve prediction.

This interpretation requires special attention because these pseudologs will be used in the petrophysical models. The interpreter must be aware of lateral variations that can and will result in differences between the projected model and the measured model. Areas in which a high degree of certainty in the correlation between the two should be preferentially weighted when deriving the pseudologs. Fig. 7 shows the crossplot and histogram comparisons for the case study.

Lateral Well Interpretation Procedure This procedure results in a set of lateral pseudo-conventional data that includes gamma total,

47

gamma potassium-thorium resistivity, neutron porosity, density, and PE. The interpreter can use this data to proceed to the generalized interpretation procedure shown in Fig. 8. A close correlation between the projected volumetric results and pseudologs, shown in Fig. 9, provides additional support to the interpreted geosteering result and to the accuracy of the pulsed-neutron measurement. In this case, no adjustment of the vertical model was required.

The last task to be completed before the optimized staging and perforation software can be run is to derive a pseudo-brittleness and closure stress. There are two major methods for completing this task. The first, more direct method uses observed relationships in the vertical and projected logs with regression analysis, neural networks, and other statistical curve prediction methods to directly determine closure pressure and brittleness. The second method (shown as blue “Method B” curves in Fig. 11) uses mineralogy to derive acoustic slowness data, including compressional and sheer. From this

Fig. 9. Pulsed-neutron petrophysical interpretation as compared to projected logs.

Fig. 8. Generalized interpretation procedure for pulsed-neutron data.

Input Data Process

Pseudo Resisitivity, Density, Neutron Porosity

YK, YSi, YCa

PNL Pseudo-Logs Yields TOC

Volumetrics PNL Pseudo-Logs

Derive TOC Using Vertical Model

Derive Relationships Between Yields and Projected Minerals

Apply Probabilistic Volumetric Model

Predict Stress and Brittleness

48

LOW-RISK, PUMPED-DOWN PNL FOR COST-EFFECTIVE COMPLETIONS IN LATERAL WELLS

data, industry-standard mechanical properties, including brittleness and closure stress, can be determined. Both methods yield similar results and virtually identical optimized completions outputs.

Optimized Completion Design The interpretation results are finally entered into the automated completion design software. The parameters used for the case study represent early design parameters for the field. Fig. 10 describes the principle parameters used in the results shown in Fig. 11.

As shown, the optimization software generates two engineered designs. Custom Design 1 represents a result that only seeks to complete the rock with the best production and fracturability indices. Custom Design 2 is designed to stage the entire lateral well while still optimizing the perforation cluster placement to reduce the differential closure stress within a particular stage. In this case study, Custom Design 1 avoids the two identified sections of the lateral well in which the uppermost clay-rich and higher stress intervals were breached.

Fig. 10. Optimized completion parameters vs. geometric.

Fig. 11. Final optimized completion results.

49

ConclusionsThese results presented in the case study align with optimized completions in other area wells, as shown in Dahl et al. 2015. However, the decision was still made to stage the second breached interval at the toe as one stage, while avoiding the first breached interval. This decision resulted in a final actual stimulation design that included 13 stages. All stages were pumped to completion as designed with the exception of the added stage at the toe. During the second half of the added stage, the pressure increased until the pumps turned off after the maximum pressure was reached. The decision was made to abort the stimulation of the stage with no further pumping, and move to the engineered stages in Custom Design 1. All engineered stages were pumped to completion with no reported problems.

Using stimulation software to design the stage and perforation placement reduces the number of stages necessary to stimulate the Lower Eagle Ford while decreasing the stress contrast within a stage (Fig. 12). The stimulation cost is reduced by 40% on average; production results remain on par because of a perceived increased perforation efficiency. EUR is constrained by reservoir thickness, which is a fixed parameter; consequently, any efforts made to mitigate the stimulation cost will improve the economics of the area.

ReferencesBuller, D., Scheibe, C., Stringer, C., and Carpenter, C. 2014. A New Mineralogy Cuttings Analysis Workflow for Optimized Horizontal Fracture-Stage Placement in Organic Shale Reservoirs. Presented at SPE Annual Technical Conference and Exhibition, Amsterdam, The Netherlands, 27-29 October. SPE-170908-MS. http://dx.doi.org/10.2118/170908-MS.

Buller, D., Suparman, F., Kwong, S., Spain, D., and Miller, M. 2010. A Novel Approach to Shale-Gas Evaluation using a Cased-Hole Pulsed Neutron Tool. Presented at SPWLA 51st Annual Logging Symposium, Perth, Australia, 19-23 June. SPWLA-2010-87257.

Dahl, J., Samaripa, J., Spaid, J., Hutto, E., Johnson, B., Buller, D., and Dusterhoft, R. 2015. Application of an Engineered Completion Methodology in the Eagle Ford to Improve Economics. Presented at SPE Unconventional Resources Technology Conference, San Antonio, Texas, USA, 20-22 July. URTEC-2153805.

Jin, X., Shah, S., Truax, J., and Roegiers, J. 2014. A Practical Petrophysical Approach for Brittleness Prediction from Porosity and Sonic Logging in Shale Reservoirs. Presented at SPE Annual Technical Conference and Exhibition, Amsterdam, The Netherlands, 27-29 October. SPE-170972-MS. http://dx.doi.org/10.2118/170972-MS.

Quirein, J., Smith, H. Jr., Chen, D., Perkins, T., and Reed, S. 2005. Formation Density Prediction using Pulsed Neutron Capture Tools. Presented at SPWLA 46th Annual Logging Symposium, New Orleans, Louisiana, USA, 26-29 June. SPWLA-2005-QQ.

Stromswold, D. 1980. Comparison of Scintillation Detectors For Borehole Gamma-Ray Logging. Presented at SPWLA 21st Annual Logging Symposium, Lafayette, Louisiana, USA, 8-11 July. SPWLA-1980-EE.

Fig. 12. Stress contrast comparison for case study well.

In addition, beneficial results were observed from the workflow. First, pulsed-neutron data can improve the geosteering interpretation of the lateral well, providing additional insight regarding why particular stages may exhibit stimulating or producing difficulty. Second, the continual data acquisition and use of this workflow has helped the team to engage in additional modifications to the initial optimized completions parameters to design larger stages to further increase cost/BOE efficiencies.

Pulsed-neutron data, when acquired with suitable detector technology, provides sufficient results to accurately design optimized completions when incorporated into a rigorous calibration workflow. Strong evidence shows that proper stress, brittleness, and volumetrics can be characterized and applied directly to reduce costs and improve the field development economics.

Galford, J., Truax, J., Hrametz, A., and Harambourne, C. 2009. A New Neutron-Induced Gamma-Ray Spectroscopy Tool For Geochemical Logging. Presented at SPWLA 50th Annual Logging Symposium, The Woodlands, Texas, USA, 21-24 June. SPWLA-2009-40058.

Jacobson, L., Durbin, D., and Reed, S. 2004. An Improved Formation Density Measurement using PNC Tools. Presented at SPE Annual Technical Conference and Exhibition, Houston, Texas, USA, 26-29 September. SPE-90708-MS. http://dx.doi.org/10.2118/90708-MS.

Jacobson, L., Truax, J., Kwong, S., and Durbin, D. 2009. Mineralogy Analysis From Pulsed Neutron Spectrometry Tools. Presented at SPWLA 50th Annual Logging Symposium, The Woodlands, Texas, USA, 21-24 June. SPWLA-2009-71035.

Vertical (Value) Axis Major Gridlines

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LOW-RISK, PUMPED-DOWN PNL FOR COST-EFFECTIVE COMPLETIONS IN LATERAL WELLS

Jeff Dahl is a senior completion engineering advisor for Devon Energy. He has over 30 years of industry experience with engineering positions for large and small E&P operators, in addition to R&D,

global business development, and US field engineering operations assignments for a major service company. Areas of expertise include hydraulic fracturing in both conventional and unconventional reservoirs, artificial lift, waterflooding, conformance control, and sand control. Jeff recently led a multidiscipline team in an integrated reservoir characterization project in the liquids rich area of the Barnett Shale and is currently helping direct a similar study within the Eagle Ford Shale. Jeff received a BS in civil engineering from the University of Illinois – Urbana/Champaign and studied for an MS in petroleum engineering at the University of Oklahoma. He is an author or coauthor of numerous publications and is the holder of eight US patents and three Canadian patents. He is a member of SPE, API, and Pi Epsilon Tau – Petroleum Engineering Honor Society.

James Samaripa has had a 37-year career in the oil industry, where his experience includes drilling, production, completion, and business development. Most recently with Devon Energy, James graduated

from Oklahoma University with a BS in petroleum engineering. He is an author and member of SPE.

John Spaid is a senior advisor, geological at Devon Energy and has been with the company for 12 years. Previously, he worked for Petro-Hunt, LLC (5 years) and Marathon Oil (18 years). His current interests

include integrated reservoir characterization, earth modeling, reservoir simulation, and completions. John has authored and/or coauthored more than five technical papers. He holds a BS degree in geology from James Madison University and an MS degree in geology from Southern Methodist University. John is a licensed professional geologist in Texas and a member of AAPG.

Erek Hutto is a Halliburton Formation and Reservoir Solutions advisor in Denver. He graduated from the Colorado School of Mines with a BS in electrical engineering. He began his career as an openhole

wireline engineer on the western slope of Colorado. From there, he transitioned into log analysis and reservoir evaluation working in Denver. In 2014, he moved to Oklahoma City to work on the implementation of new software, technologies, and services for petrophysical evaluation. He has developed experience in working in difficult conventional and unconventional plays all over the world.

Dan Buller is a senior global advisor for unconventional optimization in Halliburton’s Formation and Reservoir Solutions group. He has 33 years of industry experience spent in the petrophysical

interpretation of, and completion applications in, low-perm clastics, shales, and complex carbonates. Dan holds BS degrees in physics and math from Nebraska Wesleyan University and an MS degree in physics from Kansas State University. He is a member of SPWLA, SPE, and AAPG.

Chris McIlroy is the global pulsed-neutron product champion for Halliburton Wireline and Perforating’s Integrated Cased-Hole Services. Chris has 11 years of experience with Halliburton, including wireline

field engineer in Bakersfield, California, and log analyst and consultant positions within Formation and Reservoir Solutions (FRS) in Denver, Colorado. He holds a BS in mechanical engineering from California Polytechnic State University and an MS in industrial technology, with honors, from California State University. Chris has authored and coauthored several technical papers and is a member of both SPWLA and SPE.

Authors

CONVEYANCE METHOD AIDS IN LARGE RIGLESS PRODUCTION ENHANCEMENT

51

CONVEYANCE METHOD AIDS IN LARGE RIGLESS PRODUCTION ENHANCEMENT

Successful Utilization of E-line Tractor in Horizontal, High-Pressure and High-Temperature Gas WellsMuhammad Hamad Al-Buali, and Abdullah Abdulmohsin Al-Mulhim, Saudi Aramco; Neeraj Sethi, Halliburton; Hani Hatem Sagr, Welltec; José Solano, HalliburtonThis paper was prepared for presentation at the SPE Kuwait Oil & Gas Show and Conference held in Mishref, Kuwait, 11-14 October 2015.Copyright 2015, Society of Petroleum Engineers. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

Abstract Growing gas resource exploitation in Saudi Arabia has increased activity in drilling deep, high-pressure gas reservoirs with marginal to low permeability. Such wells generally require stimulation operations to induce production. To increase the reservoir contact area, a significant number of wells are constructed with long-reach horizontal sections. Multistage fracture operations are primarily conducted using plug and perforation technology to establish reservoir connectivity and production. The stimulation work involves multidisciplinary teams conducting simultaneous operations in a limited workspace and time. The primary well-intervention challenges include the following:

• Effective deployment of cement and casing inspection tools in the horizontal section

• Safe, reliable, and efficient technology to convey the perforating bottomhole assembly (BHA) to the target depths in the long horizontal section during some stages of the plug and perforation operations

• Available, reliable, and readily deployable contingency perforating option for plug and perforation operations

High-pressure, high-temperature (HPHT) horizontal gas wells have traditionally been challenging for performing tractor operations because of reliability issues. Recent technical improvements have enhanced the operating range of the tractor, enabling more consistent and dependable operations in these environments.

Based on the experience of conducting several plug and perforation stimulation jobs in Saudi Arabia, the electric-line (e-line) tractor has proven to be a reliable and consistent well intervention solution. The tractor-conveyed cement evaluation tools have produced high-quality interpretable data used to design the multistage fracture job. Post-fracture diagnostic work has also been successfully performed in the horizontal sections to evaluate tubular integrity, providing valuable information for future fracture design. Moreover, tractor-conveyed perforating has proven to be an effective solution for conducting stage-1 toe perforations in comparison to other options from several aspects. The option of contingency perforating in a closed system without fluid injectivity into the previously perforated stages has helped to maintain the continuity of operations. Successful tractor interventions have been performed in wells with more than 3,000 ft of horizontal sections, total depth (TD) of more than 17,000 ft, temperatures greater than 325°F, and pressures greater than 10,000 psi.

This paper describes how the state-of-the-art technology has helped to meet the technical objectives of, and had a positive effect on, large rigless production enhancement.

IntroductionOver the past few decades, horizontal drilling has become increasingly important to the oil and gas industry to enable efficient access to complex structures and marginal fields, and to increase the reservoir contact area. New technologies have emerged during this time to address post-drilling intervention challenges in such wells. Gravity-assisted conveyance methods are generally limited to wells with maximum deviations of 70 to 80° and that are unable to negotiate tortuous well paths. As a result, coiled tubing and e-line tractors are required to deploy bottomhole intervention assemblies in these wells.

E-line tractor technology has been successfully deployed in Saudi Arabia for reservoir surveillance using production logging assemblies in mature fields (Al-Buali et al. 2010). Tractors provide specific advantages,

Tight Gas Operations in Saudi ArabiaThe Ghawar field in Saudi Arabia is one of the world’s largest giant oil-producing fields (Fig. 2). The field also has large associated gas reserves (Sahin 2013).

The Khuff formation, shown in Fig. 2, is a late Permian-age deep, heterogeneous carbonate-dolomitic gas reservoir with two major producing zones (B and C). The Khuff-C zone has been extensively drilled and exploited since the 1970s;

as compared to other forms of conveyance, such as coiled tubing, and can successfully negotiate complex well trajectories in horizontal openhole well completions, enabling acquisition of good-quality flow profiles in producers and injectors.

The application of horizontal drilling to HPHT gas wells in Saudi Arabia introduces newer challenges in horizontal well intervention, including, but not limited to, operating tractors with perforating guns with the configuration shown in Fig. 1, conveying heavier weight BHAs, and performing jobs at higher bottomhole temperatures (greater than 300°F). The technology and deployment strategies had to be enhanced to perform successful tractor interventions in these wells.

Other equipment that may be run:

- Release devices

- Weight bars as spacers

- Cable head swivels

- Head tension sub

Gun Head

Tractor

CCL

Safe Sub

Shock Sub

Fig. 1. Typical tractor configuration for perforating.

52

CONVEYANCE METHOD AIDS IN LARGE RIGLESS PRODUCTION ENHANCEMENT

the tighter Khuff-B zone has recently been a focus of an extensive development program with horizontal drilling and completion (Al-Kanaan et al. 2013). Wells with low permeability in the Khuff-B undergo acid-stimulation operations using a multistage plug and perforation method or multistage fracture liner systems. Key features of the reservoirs and completions are described by (Kasnick 1987; Temeng et al. 1998; and Turki 1991).

The heterogeneity of the formation and uncertainty of the sweet spots sometimes require long intervals to be connected to the reservoir with perforating charges to improve the likelihood of success with the stimulation operation. This environment introduces a combination of factors that present a unique and challenging setting for performing well intervention with tractors, and requires the optimization of several technical and operational factors to be successful.

Tractor Technology for Saudi Arabian HPHT Gas FieldsPlanning e-line and tractor operations in such wells require addressing the following concerns:

• Corrosive environment: The levels of H2S and CO2 content of these wells require specially designed corrosion-resistant e-line cables constructed from a high-nickel alloy (Camesa 2015) that are rated to 425°F for medium levels of H2S and CO2. One important downside of these lines is the high electrical impedance, as compared to nonsour

service wirelines. The high impedance can be quite obstructive to the transmission of electrical power (especially AC power) to downhole assemblies.

• Higher temperature: With deeper reservoir targets, the requirement for tractor deployment has reached 300 to 330°F and could possibly increase beyond that range in the future.

• Longer and heavier BHAs: Longer and heavier BHAs (especially perforating guns), as compared to reservoir surveillance production logging operations, must be conveyed.

From a tractor deployment standpoint, the tractor must be able to satisfy the following objectives:

• Perform reliably under high-temperature conditions

Fig. 2. Structure of the Ghawar field (Jauregui et al. 2014).

• Operate on long, high-impedance wirelines

• Withstand high shock loads with the explosives perforating guns

At the heart of the tractor is the electric motor, which drives the hydraulic pump that supplies power to the wheels. Both AC- and DC-powered motors are used in e-line tractors. Although AC-powered tractors have a good track record with high-temperature operations, they are not suitable for operating on long high-impedance lines, such as the lines deployed in corrosive environments, as previously described.

As described in Table 1, the DC-based motors provide a much more feasible and operationally viable option for tractor deployment, albeit with some concerns over its track record on high-temperature operations. With recent technological advancements in DC motors incorporated in the design of tractors provided by leading providers, DC-powered tractors can sustain extended operations at higher borehole temperatures, as described by (Peoples et al. 2014), and have been selected for operations in the wells described in this paper.

Shock loading is mitigated by the following:

• Testing and incorporating shock tolerance into the tractor tool design

• Using a shock absorption tool between the tractor and the perforating guns to reduce impact

• Performing condition-based maintenance to ensure that tractors are exposed to a finite number of perforating runs before they are returned to the lab for comprehensive disassembly, maintenance, and refurbishment

Table 1 – Comparison of AC-Tractor vs. DC-Tractor Technology

• Highly reliable and proven track recordwith high-temperature operations

• Limitations on long high-impedance S77 corrosion-resistant wirelines

• Heavy surface equipment

• Lack of fine control for tractor operator

AC Tractors DC Tractors

Pros • Enable the use of with high-impedance cables• Enable simultaneous communication and power

transmission, as well as logging down with the e-linetools below the tractor

• Provide better operational control for the tractor operator, reducing deployment risk

• Limited experience with high-temperature (300°F) operationsbefore 2013; this paper provides information about recentexperience to demonstrate that the improvements have extended the range of DC-based tractors

• More complex design, as compared to AC motors

Cons

53

Operational ReliabilityWith tractor deployment, as with other downhole electronics technologies, there are three major aspects to reliability:

• Operating envelope

• Qualification

• Condition-based maintenance

Operating Envelope The operating envelope is primarily defined by the technology and design. New DC-motor design for tractors significantly expands the operating envelope for high temperature, as shown in Table 2, and enables operations on high-impedance H2S-resistant wirelines. The operating envelope is defined by functional testing of the equipment to destructive limits, as shown in Fig. 3 and Fig. 4.

Qualification One recent key addition to the prejob operational preparation of the tractor has been heat testing of the assembly at the expected bottomhole temperature to ensure a high degree of confidence under downhole conditions.

Table 2 – DC-Tractor Temperature Operating Envelope with Leading Provider

300˚F >400 hr

300 to 325˚F -100-400 hr

325 to 335˚F -24-100 hr

350˚F Up to 24 hr

Well Temperature Operating Hours

The advantages of the e-line tractor are its modularity, combinability, and light weight. It is transported to the wellsite easily and rigged up with minimal footprint or interference with other operations at the wellsite. In specific jobs, the tractor operations provide a superior well intervention strategy from a health, safety, and environmental (HSE) and operational efficiency perspective. Table 4 compares coiled tubing vs. e-line tractor operations.

Case Study of Tractor Intervention in High-Temperature Gas OperationsThe following case study presents the culmination of work performed over several months of inducting

Table 3– Khuff Gas Environment

Bottomhole temperatures 270 to 330˚F

Bottomhole pressures 7,000 to 9,700 psi

H2S 3 to 6%

CO2 3 to 6%

Downhole treatment 12,000 to 16,000 psi pressures

Characteristic Range

Fig. 3. Stepped temperature lab test.

030:00 1:30:00 230:00 3:30:00 4:30:00 5:30:00 6:30:00

Time

300

250

200

150

100

50

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pera

ture

˚F

Fig. 4. Shock testing for vibration envelope.

Condition-Based MaintenanceThe other important process aspect that has been implemented for hostile-environment tractor operations is to establish a finite limit on the number of runs a tractor can make before replacing critical internal components before they actually fail. Several conditions are factored into the criteria for determining the end of useful life for a given piece of downhole equipment, including, but not limited to, transportation, pressure, shock exposure, temperature, and environment. This process has significantly improved the performance and reliability of the tractor at high temperature and high shock loads.

Suitability of Well InterventionTechnology: an Operator’s PerspectivePlanning rigless stimulation and well intervention requires the coordination of logistics, supply chain, economic, personnel, and technical aspects of operations. Additional remote field operations in the emerging gas business in Saudi Arabia introduce contingencies requiring effective mitigation plans. From an operator’s standpoint, suitability and cost effectiveness intervention strategies include, but are not limited to:

• Suitability of the technology for specific requirements

• Reliability of the solution

• Wellsite deployability and efficiency

• Availability of auxiliary, unplanned, and contingency solutions

The decision to deploy wireline-tractor technology is weighed against alternative horizontal conveyance methods, generally coiled tubing, and based on the factors outlined in Table 3.

0:00:05 0:00:7 0:00:9 0:00:11 0:00:13 0:00:15

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54

CONVEYANCE METHOD AIDS IN LARGE RIGLESS PRODUCTION ENHANCEMENT

Table 4 – Comparison of Tractor vs. Coiled-Tubing Operations

Coiled Tubing (CT or e-coil) E-Line Tractor

Equipment Footprint and HSE Pros • No additional footprint if coiled tubing is part of • No additional equipment footprint with the initial plan. wireline unit.

Cons • Significantly larger footprint; more personnel and more heavy lifting is required.

Integration with Operations Pros • Better integrated with chemical treatment, milling, • Can be mobilized with minimal interference. or cleanout operations. Deploys on existing e-line setup at the wellsite. - No additional footprint. - Lower cost of third-party (crane) equipment, compared to coiled-tubing operations.

Cons • Mobilization, rig up, rig down, and demobilization can be logistically time consuming. • Require heavier, more expensive cranes.

Operational Efficiency Pros • Tractor jobs tend to be much more efficient than coiled-tubing jobs.

Cons • Generally, requires longer to rig up and rig down and overall operations.

Wellbore Environment Pros • May be more suitable in wells with excessive • E-line-deployed solutions pose no artificial choking debris or complex completions. or flow restriction, enabling better production • Provides additional benefits of pumping and profile evaluation. cleanout during intervention. • Can better negotiate sharp doglegs.

Cons • In low-rate flows for production evaluation, CT • May be more sensitive to debris and completion can pose a choking effect and adversely affect profiles in horizontal wells. the flow profile evaluation. • Wireline-conveyed options in wells with sharp bends pose risk of cutting/damaging the cable.

Fig. 5. Well-A profile.

technological advancements and assembling a fit-for-purpose solution for a specific production enhancement opportunity tailor made for tractor-conveyed well intervention.

Well-A, illustrated in Fig. 5 and Fig. 6, was drilled (sidetracked) in 2013 toward the minimum stress direction. This well achieved 3,000 ft of lateral and was completed with a cemented liner as planned for horizontal plug and perforation completion as a candidate for multistage fracturing. The well was completed with a 4.5-in. tubing and liner with a minimum restriction of 3.688 in.

The first attempt to fracture the well encountered tractor deployment complications. Toe stage perforating was subsequently performed using coiled tubing. The lack of fluid injectivity at this stage eliminated the possibility of performing pumpdown plug and perforation operations.

To improve injectivity, it was decided to extend the cluster length and to stimulate the well in one combined stage of 60 ft as part of a revised strategy. In addition, a review of tractor operations, available technology, and an audit of the quality-control processes was performed; the improvements previously described were implemented over a period of several months, and the job was redesigned.

The following runs were planned:

• Multifinger caliper log to obtain well integrity information for suspected well deformation resulting from previous operations

• One run of blank guns

• Three runs with 20-ft fracture guns

To convey the e-line tools to depth, the 3.125-in. DC tractor was selected. From a mechanical deployment perspective, the dogleg severity was well within the limit imposed by the leading tractor companies of 32 deg/100 ft. In anticipation of potential well integrity issues, the tool

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55

length was limited to 60 ft as a precautionary measure, as shown in Fig. 7.

The multifinger caliper tool string for casing inspection was centralized using a combination of strong, optimally placed spring-loaded roller and stiff arm centralizers. The logging string was decoupled from the tractor section using a flex joint to enable consistent tool position and centralization in the well (Fig. 8), resulting in the acquisition of good-quality casing profile data using the multifinger caliper (Fig. 9).

Five tractor-conveyed runs were sequentially conducted in the well with a maximum bottomhole temperature of 322°F to evaluate the integrity of the tubing and to establish connectivity with a longer reservoir section.

The tubing was found to be undamaged, and a decision was made to continue with the stimulation operation. The well was successfully stimulated after the extended-tractor well intervention.

Tractor deployment enabled a much more efficient well intervention solution to evaluate and establish well integrity, as compared to an equivalent e-coil intervention. The total wireline operating time of 67.5 hours for five runs was approximately 40% less than the estimated time for a similar e-coil intervention (approximately five days).

The resources and processes of multiple service companies were integrated in this operation and implemented under the operator’s supervision. Multilevel managerial engagement was crucial to the achievement of this goal.

Fig. 6. Dogleg severity.

Fig. 7. Perforating tool string.

STNDCH-1-7-16_STD-CH1 7/16” Halliburton Standard Cable Head2 1/8” GuardianSwivel - 2 1/8” SwivelJoint2 1/8” GuardianSwivel Joint-(SJO)ART-H-2 1/8”2.125” ART-H

WELL_TEC-318_TRACTORWELTEC 3.125” TRACTOR

X-OVER-Pin-to-PinX-OVER_Pin-to-PinWELL_TEC-3_18_SAFE_SUB3.125” WELLTEC SAFE SUB

GPLT_SUBS-GPLT_TDC3 3/8” Gamma Perforator Large Tool-GPLT TDC

SHOCK-SUBS-3.125_ShockSub3 1/8”Shock Absorber Sub

SHOCK-SUBS-3.125_ShockSub3 1/8”Shock Absorber SubPERFORATING-3_125_QuickChange3 1/8” Quick ChangePERFORATING-3 1/8” TopSub3 1/8” Gun Top Sub

GUNS- 22ft_3 1/8”_MaxForce3 1/8” MaxForce Frac 22ft

PERFORATING-3 1/8” - BullPlug3 1/8” Gun Bull Plug

Fig. 8. MIT casing inspection tool string.

CHD-AES (000001)Cable Head

Schematic Description

ART-H-2-1/8”2.125” ART-H

Swivel-Wireline

WELL_TEC-318_TRACTORWELTEC 3.125” TRACTOR

PSJ-008 (219255)Production Swivel Joint

XTU-002 (10011686)Crossover Ultrawire Toolbus to Ultralink

Flex-Flex-Mono2” Flex Monoconductor

CCL-015 (216550)Casing Collar Locator

PRC-062 (10011581)

Overbody-22 3/4” Overbody Cent

MIT-027 (10008889)Miltifinger Imaging Tool (UW 40F)

Overbody-22 3/4” Overbody Cent

PRC-062 (10018766)

BUL-006 (000002)Bullnose Terminator

Measured Depth: 10875.98 ftDogleg Severity: 9.84 deg/100 ft

Measured Depth: 12582.02 ftDogleg Severity: 9.13 deg/100 ft

56

CONVEYANCE METHOD AIDS IN LARGE RIGLESS PRODUCTION ENHANCEMENT

ConclusionsThe following conclusions can be inferred from this work:

• Tractor-based well intervention in high-temperature tight-gas wells is a viable option in the growing production enhancement business in Saudi Arabia.

• Specific challenges of production enhancement operations are more suitable for tractor-based operations in deep wells than other methods of conveyance.

• The advancement of DC-tractor motors for high-temperature operations has been proven with sustained tractor operations at high temperature and heralds a step change in the technology.

Fig. 9. Good centralization and data quality in the horizontal section with the multifingered caliper.

57

Neeraj Sethi is the technical sales manager for Halliburton in Saudi Arabia. He has 19 years of international experience in the oil and gas industry. His areas of expertise include formation

evaluation and wireline well intervention in a wide range of environments, including remote offshore, deep water, unconventional, exploration, and development. He is a member of SPE and has several patents and publications to his name. Neeraj is a graduate of IIT Mumbai.

Hani Hatem Sagr is a senior account manager for Saudi Arabia, Kuwait, and Bahrain for Welltec. Prior to joining Welltec in 2014, Hani worked for Schlumberger in various roles in Malaysia, Brunei, and Saudi

Arabia where he led their first deepwater operation for Saudi Aramco. He also worked for Schneider Electric, Services Department of Medium Voltage Switchgear, as a testing and commissioning engineer, and later served as the engineer in charge of the Western Region, Saudi Arabia. Hani received his BE degree in electrical engineering from King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia, in 2005.

José Solano is currently a technical sales advisor for cased-hole e-line services working for Halliburton Energy Services in Saudi Arabia. Jose’ has more than 14 years of experience in the petroleum

industry. His primary areas of support involve a combination of technical and operational expertise for conventional and unconventional Saudi Aramco South Ghawar gas, oil, and water wells, as well as investigations and implementation of new technology for elite Saudi Aramco projects. Previous experiences and assignments include being a hydroelectric power plant energy production operation leader as well as a Halliburton e-line field engineer in several countries worldwide, providing cased-hole technical support and auditing global operations. He has also been a project manager of downhole intelligent power units, electromechanical actuators, and production logging tools in the Halliburton Technology Center in Houston. Jose’ has a BSc degree in electronics and is an active member of SPE.

Muhammad Hamad Al-Buali is a chemical engineer who graduated from King Fahad University of Petroleum and Minerals, Dhahran, Saudi Arabia in 2002. He started his career working as a production

engineer for Saudi Aramco looking after gas, oil, and water wells. Since 2010, Muhammad has worked in gas well completion operations executing and supervising all rigless activities on onshore gas wells, including fracturing, well intervention, and well testing.. He has worked on several projects supporting production enhancement, cost optimization, well interventions, well integrity, and cutting-edge technologies, such as CO2 fracturing. Muhammad is an SPE member and has participated in many SPE events as a paper author, presenter, and delegate

Abdullah A. Al-Mulhim is currently working as the acting oil production engineering general supervisor in Saudi Aramco’s Southern Area Production Engineering Department. His experience includes work in

various petroleum engineering departments as a well log analyst, geosteering MWD/LWD engineer, petrophysicist, oil and gas production engineer, and acid stimulation specialist. In 2002, Abdullah received his BS degree in petroleum engineering from King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia. In 2008, he received his MS degree in petroleum engineering – petrophysics from the Colorado School of Mines, Golden, Colorado.

Authors

ReferencesAl-Buali, M.H., Dashash, A.A., Guraini, W.K. et al. 2010. Enhancement of PLT Tool Reach in Horizontal Wells Using Advanced Wireline Tractor. Presented at the Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, UAE, 1-4 November. Paper SPE-137205-MS. http://dx.doi.org/10.2118/137205-MS.

Al-Kanaan, A., Makmun, A., Al-Anazi, M. et al. 2013. Evolving Khuff Formation Gas Well completions in Saudi Arabia: Technology as a Function of Reservoir Characteristics Improves Production. Presented at the SPE Unconventional Gas Conference and Exhibition, Muscat, Oman, 28-30 January. Paper SPE-163975. http://dx.doi.org/10.2118/163975-MS.

Camesa. 2015. EMC Product Catalog. http://www.camesainc.com/product-catalog/1N32-Monoconductor-S77. (accessed 13 July, 2015).

Jauregui, L., Alonso, J., Ghurairi, A. et al. 2014. Engineered Perforating Charges Designed for Stimulation. Presented at the SPE Annual Technical Conference and Exhibition, Amsterdam, The Netherlands, 27-29 October. Paper SPE-170617-MS. http://dx.doi.org/10.2118/170617- MS.

Kasnick, M.A. 1987. Khuff Gas Production Experience. Presented at the Middle East Oil Show, Bahrain, 7-10 March. Paper SPE-15764-MS. http://dx.doi.org/10.2118/15764-MS.

Peoples, M., Hammill, T., Alferez, O., and Murrill, G. 2014. Electric Line Tractor-Based Conveyance in High Temperature Wells: a Collection of Local Case Stories. Presented at the SPE/ICoTA Coiled Tubing and Well Intervention Conference and Exhibition, The Woodlands, Texas, USA, 25-26 March. Paper SPE-168243-MS. http://dx.doi.org/10.2118/168243-MS.

Sahin, A. 2013. Unconventional Natural Gas Potential in Saudi Arabia. Presented at the SPE Middle East Oil and Gas Show and Conference, Manama, Bahrain, 10 -13 March. Paper SPE-164364. http://dx.doi.org/10.2118/164364-MS.

Temeng, K.O., Al-Sadeg, M.J., and Al-Mulhim, W.A. 1998. Compositional Grading in the Ghawar Khuff Reservoirs. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana, USA, 27-30 September. Paper SPE-49270-MS. http://dx.doi.org/10.2118/ 49270-MS.

Turki, W.H. 1991. Drilling and Production of Khuff Gas Wells, Saudi Arabia. Presented at the SPE/IADC Drilling Conference, Amsterdam, The Netherlands, 11-14 March. Paper SPE-21975- MS. http://dx.doi.org/10.2118/21975-MS.

58

Operator Uses Advanced Perforation Flow Laboratory to Support HMX Perforating by Coiled Tubing in HPHT FieldDennis Haggerty, Jet Research Center-Halliburton; Steven Christie, DONG EnergyThis paper was prepared for presentation at the SPE European Formation Damage Conference and Exhibition held in Budapest, Hungary, 3-5 June 2015.Copyright 2015, Society of Petroleum Engineers. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

AbstractBy using the advanced perforation flow laboratory (APFL), the depth of penetration performance of shaped charges can be measured at downhole conditions to confirm whether or not the formation penetration will exceed the depth of formation damage attributable to drilling. In tubing-conveyed perforating, HNS explosive shaped charges have historically been used in elevated temperature environments. The option of using deeper penetrating, but less heat-resistant HMX explosive shaped charges is possible in the Hejre field wells in the North Sea because the depth to the reservoir interval to be perforated is within the reach of coiled tubing. This process requires less time for the perforating guns to tolerate elevated temperatures, and coiled tubing provides a means of circulating cooling fluid, further increasing the charge lifespan. Based on conservative run times for deploying guns on coiled tubing (estimated to be 4 to 6 hours from surface), there will be sufficient time to position the guns at depth before detonation, and sufficient time to retrieve the gun string from the wellbore in the event of a misfire.

All perforation flow lab tests in the APFL were run at Hejre pressures, with overburden stress at 17,500 psi and pore pressure at 14,600 psi; several tests were run at the reservoir temperature of 160°C (320°F). Aligned with American Petroleum Institute Recommended Practice 19B Section 4 (2006), the APFL tests were conducted to closely match the expected conditions in the Hejre field, requiring minimal scaling of the results.

Tests in the APFL comparing the different explosive powder charges showed a nearly 50% increase in formation-analog target penetration using the HMX charge vs. the HNS charge. This depth of penetration increase improves the prospect of penetrating the estimated drilling damage zone to vastly improve production and the effectiveness of further stimulation. This paper discusses the methodology, obstacles encountered and means of addressing them, and the test program results.

Before the construction and development of testing equipment to shoot a shaped charge at elevated temperatures and high pressures, extrapolations had to be used to predict perforator performance with a higher level of uncertainty.

IntroductionKnowing what to expect about the perforating performance for an expensive offshore oil well reduces risk. It has been shown that laboratory testing with equipment capable of matching the high-temperature and high-pressure conditions provides that data. High pore pressure reduces penetration performance, and high pore pressures create very high velocities between the sandface and the wellbore when underbalanced perforating because the gun in the wellbore is sealed to protect the explosives in 1 atm space. By conducting these enhanced American Petroleum Institute Recommended Practice 19B Section 4 (2006) tests, data can be collected to guide the process for selecting the best perforator and deployment technique.

The common explosives used in the manufacturing of perforating charges are categorized by thermal stability, and a chart of heat resistance vs. time is widely used to select the explosive type for specific conditions (Fig. 1).

In locations around the world, it is widely known that oil and gas reservoirs are at temperatures that exceed the practical limits of certain high-performing explosives. Heat-resistant explosives can then be substituted and should also be tested in a Section 4 laboratory as near to reservoir conditions as possible.

What makes the APFL an advanced laboratory is the pressure and temperature range that it covers. Before constructing the APFL facility, perforating flow laboratory limits were 10,000-psi overburden stress and 5,000-psi simulated wellbore and pore pressure at ambient temperature. The APFL can now handle 25,000-psi overburden stress and 20,000-psi simulated wellbore and pore pressure to temperatures up to 400°F (205°C). Most new reservoir discoveries are deeper, resulting in higher pressures and temperatures, and testing should be conducted at actual conditions (Shafer et al. 2008).

DONG Energy was aware that the common North Sea operator was relegated to using HNS-type explosive in the selected charges because of temperatures exceeding 300°F in wells deeper than 15,000 ft (4,572 m). DONG Energy was also aware that HNS shaped charges had a shorter penetration depth than HMX charges.

Testing in the Advanced Perforating Laboratory (APFL)The primary objective of a Section 4 test is to match downhole conditions and the wellbore configuration expected to be encountered in the field as closely as possible. The shaped charge from a manufactured lot is sealed in a chamber and situated with a specified offset above a simulated scalloped gun carrier (or gun carrier without scallop in the case of oriented guns). For this undertaking, the gap between the gun wall and casing is set

Fig. 1. Temperature vs. time ratings for perforating explosives with approximate deployment times for the three common conveyance methods (Barker 2013).

600

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350

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Tubing-Conveyed Perforating Time Frame

CONFIDENT CHARGE SELECTION THROUGH SIMULATING REAL-WORLD CONDITIONS

59

to match a centralized gun in the 5 or 51⁄2-in. casing, depending on the gun to be deployed; the cement composition and thickness are also designed to match that expected in the well. Target components, such as scalloped gun carrier, casing, and cement that are curved surfaces in the field, are made flat in the simulated laboratory setup to enable seals capable of high pressure, as shown in Fig. 2.

The conditions in the Hejre field included the following:

• Reservoir temperature: 160°C (320°F)

• Overburden: 17,500 psi

• Pore pressure: 14,600 psi

• Effective stress: 2,900 psi

• Wellbore pressure: 12,100 psi(2,500 psi underbalance)

• Open hole (drill bit): 81⁄2 in.

• Centralized production liner: 5-in. 23.2 lb/ft ID4.50 in. 110Cr13S for 27⁄8-in. guns

Table 1 – Platform and Reservoir Details

Number of production wells 5

Reservoir thickness, approximately 30 m

Reservoir depth 5-6 km

Reservoir fluid Volatile oil

Reservoir pressure 1010 bar

Reservoir temperature 160°C

Oil processing capacity (estimated) 35,000 stb/day (barrels of oil per day)

Gas processing capacity (estimated) 76 million scf/day (standard cubic feet of gas per day)

Expected lifetime production 170 million barrels oil equivalent

Length of new export oil pipeline 90 km

Length of new export gas pipeline 24 km

A

B

D

C

Fig. 2. Test assembly: A) wellbore chamber, B) core sample, C) overburden fluid, D) single shaped charge in simulated perforating gun. Shown in horizontal, all tests were run with the assembly in the vertical position, shooting downward.

• Centralized production liner: 51⁄2-in. 26.8 lb/ft ID 4.50 in. 110Cr13S for 33⁄8-in. guns

• Production liner cement: more than eightadditives (UCS approximately 2,900 psi)

From this data, it was determined that coiled tubing could handle these conditions, in terms of depth to target, pressure, and temperature (aided by cooling fluid circulation capability and misfire contingency plans). Table 1 provides platform and reservoir details (DONG Energy 2014).

The perforation details included the following:

• Test charges: 27⁄8-in. HMX, 27⁄8-in. HNS, 31⁄8-in.HMX, 31⁄8-in. HNS

• Gun systems: 27⁄8-in. oriented (slick wall), 33⁄8-in. oriented (slick wall)

• Average core properties of closest field-matching analogue rock (Berea buff sandstone (TerraTek, Inc. 1999))

- 5,290 psi unconfined compressive strength (UCS)

- 20.4% porosity

- 220 mD

System ConfigurationFig. 3 shows a simplified diagram of the high-pressure system with two, independent 3-gallon capacity piston accumulators. One accumulator is used to supply odorless mineral spirits (OMS) to the wellbore side, and the other is used to supply OMS to the pore side driven by nitrogen below the pistons. Pressure transducers are located above

Fig. 3. Simplified diagram of high-pressure system.

Pressure Transducer

Direction of Flow

Pressure Vessel

Bypass Valve

WB Accumulator Pore Accumulator

Valve

Accumulator Piston

each accumulator for the continuous monitoring of wellbore and pore pressure before, during, and after the perforation event. After the perforator was detonated, the time to achieve equilibrium between the wellbore and pore pressure was recorded for an indication of perforation effectiveness. All flow is axial from the bottom upward.

Test ResultsTable 2 shows the average core penetration for each set of tests differentiated by charge size, gun system, explosive type, and temperature. All perforation tests were conducted with 17,500-psi overburden stress applied, 14,600-psi pore pressure, and 12,100-psi wellbore pressure for a 2,500-psi overbalance. The significance of identifying the gun systems in these tests relate to the specific charge standoff, gun scallop, and fluid gap used to ensure that the results can be applied to the field. The 27⁄8-in. gun system would be used in a 5-in. liner and the 33⁄8-in. gun system in a 51⁄2-in. liner, resulting in similar fluid gaps and casing thickness matched in these tests. The significance of the oriented term in the gun’s description is that no scallop is cut in the gun body, enabling the charges in the gun to shoot at a preset orientation.

60

CONFIDENT CHARGE SELECTION THROUGH SIMULATING REAL-WORLD CONDITIONS

From the APFL HP-room temperature test data, the 27⁄8-in. HMX penetrated 22.5% deeper than the 27⁄8-in. HNS, and the 31⁄8-in. HMX penetrated 32.6% deeper than the 31⁄8-in. HNS. The HPHT tests showed the 31⁄8-in. HMX charge provided 28.4% better penetration than the smaller, 27⁄8-in. HMX.

The differences between the ambient and reservoir temperature results show that the casing hole size and penetration depths either remained the same or decreased for the reservoir temperature tests. More tests would strengthen this observation that shows the 27⁄8-in. HMX DP penetrated 0.73 in. less at temperature for a 14.4% reduction. The 31⁄8-in. HMX DP penetrated 0.17 in. less, for a 2.7% reduction.

The resulting percent open perforation for all systems was virtually 100% of total penetration; this was expected because of the 2,500-psi pressure overbalance before perforator detonation (differential from the pore to the wellbore). Results from the ambient, room temperature tests also showed that the pore and wellbore pressures quickly equilibrated, within 15 to 30 seconds after detonation. Results from the reservoir temperature tests showed that pore and wellbore pressures equilibrated even faster than the ambient tests, between 5 and 10 seconds, after detonation. Viscosity of the OMS is reduced by three fold at reservoir temperature, which results in higher cleanup velocities at the 2,500-psi static underbalance.

The core hole size was observed to have increased dramatically for the initial reservoir temperature tests. Also, the cement coupons were observed to have reduced in thickness after removal from the testing assembly. After a brief investigation, it was determined that the stress and time at temperature caused the cement coupon size to shrink and to reduce the stress transfer between the core and cement contact. Therefore, for the second set of reservoir temperature tests, the additive MicroBond HT™ cement was added to the Class G cement. As shown in Table 3, the differences were

Table 2 – Results of API RP 19B Section 2/4 Tests Conducted at 2,500-psi Underbalance

Charge Gun System Temperature Total Core Penetration (in.) Casing hole size (2-shot ave.) (2-shot ave.)

27⁄8-in. HNS DP 27⁄8-in. oriented Room Temp. 3.92 0.198

27⁄8-in. HMX DP 27⁄8-in. oriented Room Temp. 5.06 0.247

31⁄8-in. HNS DP 33⁄8-in. oriented Room Temp. 4.19 0.206

31⁄8-in. HNS DP 33⁄8-in. oriented Room Temp. 6.22 0.241

27⁄8-in. HMX DP 27⁄8-in. oriented 320˚F (160˚C) 4.33 0.229

31⁄8-in. HMX DP 33⁄8-in. oriented 320˚F (160˚C) 6.05 0.242

significant, and the additive is always included in the cement in heated Section 4 tests.

The second set of reservoir temperature tests was subjected to post-perforation flow analysis. Fig. 4 compares the production ratios of the 27⁄8-in. HMX DP charge and the 31⁄8-in. HMX DP charge. The production ratio (PR) is the post-perforation flow index divided by the preperforation flow measurement. The PR for the 31⁄8-in. HMX DP averaged 0.75, as compared to an average PR of 0.49 for the 27⁄8-in. HMX DP.

As with the cement discovery, measuring flow rate above 14,000 psi also needed improvement. A new method of determining the flow rate through the

core at the high pore pressure was successfully instituted. Fig. 5 shows the inflow/outflow curves for the 27⁄8-in. HMX DP and 31⁄8-in. HMX DP generated using WEM nodal analysis populated with the reservoir data under conditions in the Hejre field previously described and the perforation penetrations and average tunnel diameters from the Section 4 tests.

Comparing HMX to HNS Equal DP Chargesat High-Pressure ConditionsThis section provides details about the comparison of 31⁄8-in. HMX and HNS DP charges and 27⁄8-in. DP HMX and HNS charges in high-pressure conditions.

31⁄8-in. HMX and HNS DP Charges. As shown in Fig. 6, the photos showing the split cores from the tests using the 31⁄8-in. HMX charges are approximately 30% deeper than the 31⁄8-in. HNS charges. Note the large diameters of all the perforation tunnels attributable to the high-velocity cleanup from the 2,500-psi underbalance magnified in the heated tests with low-viscosity OMS, approximately 0.87 cP at 320°F and 14,600 psi. The viscosity of OMS in the nonheated tests is approximately 5.2 cP.

Fig. 4. Flow data comparing the production ratio (PR) of the 27⁄8-in. HMX DP to the 31⁄8-in. HMX DP charges.

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0 100 200 300 400 500 600

HP/HT Post-Perforated FlowProduction Ratio vs. TimeElapsed Time (seconds)

Table 3 – Core Entry Hole and Perforation Tunnel Volume Data

Core Entry Hole, in. (2-shot ave.) (1-shot) Perforation Tunnel Volume, cc (2-shot ave.) (1-shot)

Charge Temperature Low-Temp Cement High-Temp Cement Low-Temp Cement High-Temp Cement

27⁄8-in. HNS DP Room Temp. 0.422 16.0

27⁄8-in. HMX DP Room Temp. 0.728 26.5

31⁄8-in. HNS DP Room Temp. 0.646 22.5

31⁄8-in. HMX DP Room Temp. 0.668 44.5

27⁄8-in. HMX DP 320˚F (160˚C) 1.180 0.600 42.0 34.0

31⁄8-in. HMX DP 320˚F (160˚C) 0.914 0.784 60.0 46.0

61

27⁄8-in. DP HMX and HNS Charges. As shown in Fig. 7, the photos showing the split cores from the tests using the 27⁄8-in. HMX charges are approximately 22.5% deeper than the 27⁄8-in. HNS charges. The tunnels were clean of debris because of the 2,500-psi static underbalance.

Comparing Charge SizeThe last step was to determine how much deeper the 31⁄8-in. HMX DP penetrated as compared with the 27⁄8-in. HMX DP charge. As shown in Fig. 8 and Fig. 9, the 31⁄8-in. HMX DP penetrated approximately 1.3 in. deeper using the larger charge.

ConclusionsThe coiled-tubing deployment of perforating guns in the Hejre field is an option and would enable the use of HMX charges by keeping the amount of time at elevated temperatures within the safe zone.

Fig. 6. Two split core images of the perforation tunnels made by the 3 1⁄8-in. HMX DP charge (left) and two split core images of the perforation tunnels made by the 3 1⁄8-in. HNS DP charge (right). The difference in penetration between the two averages 2.03 in., which is more than 30% deeper.

Fig. 7. Two split core images of the perforation tunnels made by the 2 7⁄8-in. HMX DP charge (left), and two split core images of the perforation tunnels made by the 2 7⁄8-in. HNS DP charge (right). The difference in penetration between the two averages 1.14 in., which is 22.5% deeper.

Fig. 8. The 2 7⁄8-in. HMX DP split core photo and a CT image of the same. The depth was measured to be 4.723 in.

Fig. 9. The 3 1⁄8-in. HMX DP split core photo and a CT image of the same. The depth was measured to be 6.079 in.

Fig. 5. WEM nodal analysis showing production estimates for the 2 7⁄8-in. HMX DP and the 3 3⁄8-in. HMX DP gun systems using APFL results (P.E. Moseley & Associates 2014). The larger 3 3⁄8-in. gun system delivers approximately 28% more bbl/day based on the simulation.

15000

14500

14000

13500

13000

12500

Rese

rvoi

r Pre

ssur

e, p

si

250 5000 10000 15000 20000 25000 30000 35000 40000

Production, B/D

27⁄8-in. HMX outflow27⁄8-in. HMX inflow31⁄8-in. HMX outflow31⁄8-in. HMX inflow

21,690 bbl/D - 27⁄8-in. HMX30,195 bbl/D - 33⁄8-in. HMX@ ˜ 550 psi drawdown

Charge Productivity Analysis

62

CONFIDENT CHARGE SELECTION THROUGH SIMULATING REAL-WORLD CONDITIONS

All tests were successfully shot at 320°F and 17,500-psi overburden, with an effective stress of 2,900 psi on the Berea buff sandstone core. The 27⁄8-in. and 33⁄8-in. oriented HMX gun systems had no problem penetrating the target at these extreme conditions.

Tests conducted in the advanced perforation flow lab indicate a performance increase using HMX charges compared with HNS charges at the high pressures and temperature expected at the Hejre field in the North Sea. The 31⁄8-in. oriented HMX charge penetrated the core 6.08 in., and the 27⁄8 -in. oriented HMX charge penetrated the core 4.77 in. Nodal analysis using reservoir data coupled with the perforation penetration and perforation tunnel diameter indicate a 28% production increase for the 31⁄8-in. HMX DP charge in the 33⁄8-in. gun shooting in a 51⁄2-in. liner over the 27⁄8-in. HMX DP charge in the 27⁄8-in. gun shooting inside a 5-in. liner.

Both tests showed that the perforations were able to produce with high production ratios. The 31⁄8-in. oriented HMX charge outperformed the 27⁄8-in. oriented HMX charge in hole size, depth of penetration, and flow performance. The high static underbalance produced virtually 100% clean perforation tunnels in the core.

MicroBond HT cement additive was needed in the heated tests to eliminate cement shrinkage and ensure stress was transferred from the core to the cement. The core entry diameter for the final 27⁄8-in. oriented HMX test was 49% smaller than the initial heated tests that did not have cement additive. It is thought that shrinkage of the cement because of heat may have caused a stress discontinuity between the core-cement interface creating an artificially enlarged core entry hole. As with the core hole size effect, there was agreement between the second heated core penetration measurement and the averaged nonheated core penetration measurements further indicating that full contact was made between the cement and core during the heated tests with the additive.

A new method to measure flow rate at the HPHT reservoir conditions was needed and successfully devised to enable the use of the high-accuracy flowmeters without exceeding their limits.

Dennis Haggerty is a senior technical advisor for Halliburton’s Advanced Perforating Flow Laboratory (APFL) at the Jet Research Center (JRC) in Alvarado, Texas, where he has worked for the past 10 years.

Prior to that, he spent six years on a DOE reservoir characterization project at the Illinois State Geological Survey and 10 years at Westport Technology Center and Core Laboratories in Houston. Dennis has written several SPE papers and holds several patents, all related to perforating. He received a BS degree in petroleum engineering from Montana Tech in Butte, Montana.

Steven Christie is a senior completion engineer for DONG Energy in Denmark, working on several projects, including the HPHT Heijre project in the North Sea. Previously he worked for Shell as a completions engineer, and with Schlumberger as an engineer, starting in 1997.

AuthorsSI Metric Conversion Factorspsi x 6.894 757 E + 00 = kPain. x 2.54* E + 00 = cm˚C = 0.555 x ˚F - 17.77*Conversion Factor is Exact

AcknowledgementsThe authors would like to thank DONG Energy, Bayerngas, and Halliburton for supporting this effort and for permitting the publication of this paper.

ReferencesAmerican Petroleum Institute. 2006. RP 19B, Recommended Practices for Evaluation of Well Perforators, second edition, API, Washington, DC.

Barker, J.M. 2013. Thermally Stable Explosive System for Ultra-High-Temperature Perforating. Presented at the SPE Annual Technical Conference and Exhibition held in New Orleans, Louisiana, USA, 30 September-2 October. SPE 166179-MS. http://dx.doi.org/10.2118/166179-MS.

DONG Energy. 2014. Facts about the Hejre Project. http://www.hejre.com/en/the-project/facts. Accessed March 4, 2014.

P.E. Moseley & Associates. 2014. Well Evaluation Model (WEM) version 11.2.8.

Shafer, J.L., Boitnott, G.N., and Ewy, R.T. 2008. Effective Stress Laws for Petrophysical Rock Properties. Presented at the SPWLA 49th Annual Logging Symposium, Edinburgh, Scotland, 25-28 May.

TerraTek, Inc. 1999. Rock List, Drilling and Completions Laboratory.

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UPDATED EXTENDED-STROKE DPU OFFERS DEPENDENDABILITY, POWER, AND SAVINGS

Pulling Subsea Wellhead Plugs Using a Slickline Downhole Electrical Power Generator ToolJacques Babin, Jack Clemens, and Bryce Sauser, Halliburton; Gabriela Davalos, StatoilThis paper was prepared for presentation at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition held in Nusa Dua, Bali, Indonesia, 20-22 October 2015.Copyright 2015, Society of Petroleum Engineers. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

AbstractA downhole electro-mechanical power-unit tool was used to provide anchored power to pull crown plugs in a single run and in reduced time. This setup has the capability to pull subsea crown plugs that often require greater force than is possible with traditional conveyances without requiring time and resources to reduce hydrostatic pressure. In deepwater environments, reducing time can significantly impact costs because of the extra equipment and logistics necessary to properly operate in those conditions. The downhole electrical power generator tool proved to be a viable and cost-effective option.

A Gulf of Mexico job for Statoil required the removal of the upper and lower crown plugs just below 8,000 ft with 10.6 lbm/gal fluid in the riser. While on location, the crew ran a conventional pulling tool to attempt pulling the upper crown plug. While latched into the plug, an integrated workover control system (IWOCS) pumped fluid in between the two plugs to decrease the differential across the plug to assist in pulling. The crew was unable pull the plug on two separate attempts. A 3.59-in. extended-stroke downhole electro-mechanical power-unit tool with a crown plug latch tool capable of an effective stroke of 36 in. and a linear pulling force of 60,000 lb was the program’s contingency. It was deployed and pulled the crown plug.

There were indications that the IWOCS system had failed, and the downhole electro-mechanical power-unit tool pulled the upper crown plug with the full differential of the hydrostatic head. A conventional pulling tool was used to attempt to pull the lower crown plug, again without success. The downhole power tool was then used to retrieve the lower crown plug successfully.

In a subsea tree, crown plugs are used to isolate the wellbore from the environment. Often, one of the first required tasks of a subsea well intervention is to pull the subsea crown plugs from the wellhead to gain access to the wellbore. Hydrostatic pressure associated with fluid in the riser creates a large pressure differential across these wellhead plugs that seal the cross-sectional area of the tree. If the plugs cannot be removed from the profile conventionally, the fluid is displaced to lighten the hydrostatic head before the plug can be pulled. This operation requires a minimum of 24 hours of rig time.

Slickline and coiled tubing have limited constant pulling force because of the finite-strength limits of the conveyance. Deep water and debris often compound the required pulling force. These forces are well above the tensile-strength limit of slickline wire and even the pulling strength of coiled tubing. A subsea wellhead plug requires a steady pull along the entire length of the sealbore.

Conventional slickline methods are limited to creating extremely high, but short-duration impact loads; however, brief impact loads are not suitable because the seals tend to reseat after each impact and are forced back on seat by hydrostatic pressure from above. Therefore, using mechanical or hydraulic jars to simplify the delivered force does not effectively retrieve the plug from the wellhead.

IntroductionA great amount of planning is required for subsea well interventions. After a rig or intervention vessel is mobilized to the location to connect the floating rig to the subsea wellhead with a marine riser, the subsea crown plugs must be pulled out of the subsea wellhead. Subsea trees typically have upper and lower crown plugs for a dual-redundant sealing barrier. The crown plugs isolate the wellbore from the environment. During the planning process, a removal method must be selected for pulling crown plugs from the subsea tree. There are many methods for removing crown plugs, including a rig, coiled tubing (CT), and slickline, which is preferred for its low cost, quick setup, and speed of execution.

Conventional slickline methods using mechanical spang jars have been successfully deployed to pull crown plugs in shallow water. Slickline jars create very short-duration, high-impact forces to slowly work the crown plug out of the sealbore, which is ideal in shallow water because hydrostatic pressure from the column of fluid above the crown plugs is typically less than the surface shut-in pressure. Additionally, debris in the marine riser can cause further issues. When debris falls and settles on top of the wellhead plugs, the accumulation can make pulling the crown plug more difficult.

Advancement in process and technology development has continued to occur at deeper water depths. Higher hydrostatic heads have made impact tools less effective. Hydrostatic pressure created by the water column can be greater than the surface shut-in pressure, which creates a differential on the large cross-sectional area of the crown plug. This differential pressure can be great enough to hold the wellhead plug in place. Owing to low-wire tensile strength, conventional slickline has an extremely limited pull force. Because the line must be relaxed to recock the jar, any jar force, even a substantial one, cannot work the plug out of the sealbore. Every time the line is relaxed, the crown plugs go back down in the sealbore, which limits the use of conventional slickline jars to pull crown plugs. While conventional slickline services have successfully pulled many crown plugs using spang jars, spring jars, and hydraulic jars from shallow-water subsea wellheads, the more demanding deepwater subsea wellheads require a more constant force. Hydrostatic head pressure, debris above the plugs, momentary impact forces created by conventional slickline services, and limited tensile wire strength limit the success of conventional slickline services in pulling crown plugs over the entire distance of the crown plug sealbore.

When conventional slickline is unsuccessful in pulling the subsea wellhead plug, other methods must be used. Historically, the preferred method after slickline is CT because it has a much greater pull capability than slickline. Generated with an electro-mechanical power unit, the tensile strength of most CTs is less than 60,000 lb. CT services can also be significantly higher in cost because of equipment size, rig-up time, longer deployment times, and number of personnel required. The advantages of slickline over CT for pulling crown plugs in deepwater subsea wells include:

• More economical service

• Smaller footprint areas

• Faster tripping speeds and higher tensile forces

64

An alternative to conventional slickline or CT services and tractors is necessary to reduce deepwater subsea well servicing costs. A system that produces a constant high force over a long linear distance is necessary to reliably pull subsea crown plugs. A battery-powered electro-mechanical pulling tool or downhole power unit (DPU) with extended stroke was developed to overcome conveyance limitations. This technology has provided the required constant high-pulling force across the entire distance of the sealbore to overcome the pressure imbalance of the crown plugs from the sealbore. The extended-stroke DPU has 36 in. of linear travel. The tool is configured with a special latch mechanism to engage and pull the upper and lower crown plugs in a subsea wellhead. It is capable of applying up to 60,000 lbf of linear pulling force directly to the crown plug for the full stroke and has successfully pulled crown plugs in eastern Canada, the Gulf of Mexico, Brazil, and West Africa.

A battery module within each DPU powers a motor/gearbox, which activates a linear drive connected to a power rod. The battery-powered tool provides a gradual, controlled tensile force directly to the tool attached to the power rod. The power rod travels at approximately 0.5 in./min when activated at the target depth. The tool operates at up to 250°F using common C size alkaline batteries.

Once configured at surface and powered, the unit operates in an autonomous mode and starts the tool sequence when the programmed time has elapsed. Available in multiple sizes, the current DPU tools have been successfully and globally operating since 1995. Any downhole task that requires linear motion at high force can be powered by a DPU. Owing to its reliability and special operating characteristics, it is a preferred service tool in many locations.

In use for nearly 20 years, the DPU concept has proven to be a reliable, cost-effective, nonexplosive setting tool when used within its published operating limits. The original configuration has undergone several revisions that have helped it to meet increasing oilfield demands and more challenging operating limits. The latest updates have addressed the requirements of pulling crown plugs and setting wellbore sealing devices. This evolution is discussed in the following section.

Downhole Electro-Mechanical Power-Unit Tool HistoryThe DPU was originally developed as a setting tool to set wellbore sealing devices on slickline without using explosives. Building a reliable, low-cost, battery-powered electro-mechanical setting tool was the design goal.

Introduced in the mid-90s, the first-generation downhole power units met the well conditions of that era. Powered by alkaline batteries, the tool had a simple, digital logic-based timer that switched on the motor when the timer elapsed. The setting of wellbore devices was enabled by the motor/gearbox/linear drive without the use of explosives. The power rod was capable of traveling inward or outward with a constant force over the entire stroke length. The linear speed was approximately 0.5 in./min, which is favorable compared to setting wellbore sealing devices because it permits slips and sealing elements to slowly expand and conform to the tubing’s inside diameter (ID). The slow linear speed continues until the release mechanism shears and the tool is free from the wellbore sealing device. It did not provide any information about the tool performance.

As time progressed and projects shifted into the deeper, higher-pressure fields, the DPU required some updates to meet the challenging new well parameters.

Because of increased temperature, as well as more frequent running of tools and in greater types of service, updates were required to the simple timer-based control logic to meet the more demanding environments. Commercially available electronic components have also improved greatly since the DPU was initially designed. For higher temperature operations, a custom hybrid electronic circuit was developed to ruggedize the printed circuit board (PCB). With time, it became clear that the custom hybrid circuit needed more modifications as demands grew for additional options and more flexibility.

To improve reliability while expanding the operating envelope, several design advances were made to the DPU controller. To enable limited communication reception from the surface, circuit controls were added. A method was developed to disable the tool to help prevent it from setting while moving or at the wrong depth. Logic improvements helped to prevent a partial set, limited redundancy was added to the circuitry, and the dual parallel configuration decreased the current flow in each component added.

PCB Memory and Control LogicThese updates improved reliability and tool performance, but greater control logic for modern demanding jobs was necessary. These tools did not have memory to examine post-job results. While a tool could be run and brought back to the surface, the downhole operation remained a mystery. There was no way to measure if adequate force was applied downhole. Additionally, actual temperature inside the tool was unknown, and there was no way to determine the activation time or the stroke distance and force. This collection of unknowns did not build confidence in the actual downhole operation.

This led to a new memory circuit being developed for the PCB. This circuit is capable of recording and plotting each prejob shear test and downhole job. The stroke distance, activation time, run time, force, temperature, voltage, and current are all collected each time the tool is activated. As an added safety measure, an overload protection system was included that allows the DPU to reach maximum current, but prevents mechanical damage in case of mechanical overload.

This data allows the tool’s performance to be reviewed and documented, and can be used for preventative maintenance and verification of proper operation. While multiple improvements enhanced the temperature and pressure capabilities through the years, the basic tool design remained consistent. The original tool design could not limit the tool setting force. In the event of a mechanical overload, the tool kept driving the motor until the board failed, and the board would either be replaced or repaired.

Modernization of the ServiceTo update and meet the industry’s demand on efficiencies, a microprocessor-based timer and control board were developed, which added significant tool operation benefits, including:

• Onboard memory recording of the tool’s operational data during downhole operations.

• Overload shutdown setting—under tool overload conditions, the tool shuts down, and no damage occurs.

• Timer parameters can be set with a simple rotary switch or programmed directly into the microprocessor.

• Crystal-controlled clock for stable timing parameters.

• Motion-based telemetry to control the tool.

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65

The tool’s ability to record operational data is particularly important during a setting operation—the battery voltages, motor currents, tool motion, and tool temperature are recorded against time to provide a detailed record of the setting operation. The tool records the programming and whether the tool performed the sequence as programmed. To ensure that the device sets correctly, the actual setting force can be calculated from the tool current, and a job report can be quickly produced from the downloaded data to show the correct timing and shear force.

This recorded data allows the tool’s performance to be reviewed and documented. The data is used to guide preventative maintenance and verify proper tool operation. The ability to provide pulling and setting data on each job is required by today’s marketplace. This information is particularly useful when pulling deepwater subsea crown plugs, which can require extremely high forces, owing to high hydrostatic loading or because the crown plug has been in place for an extended period of time. Contributing factors to pulling forces greater than the tool rating include high overbalance forces and settlement on top. The latest generation downhole power units offer high pulling forces and the job data necessary for diagnosing incidences where the tool was unsuccessful in pulling the crown plug.

Crown Plug Pulling SystemTypically, subsea wellheads have two crown plugs located in the tubing hanger, which serve as dual-isolation barriers for the subsea well. During well-intervention services, both crown plugs must be removed from the tubing hanger. Previously, the plugs were removed with slickline, CT, or a rig. When experiencing increased water depth or debris buildup, removal forces commonly exceed the capabilities of slickline or CT.

The challenge for new tool development was to find a low-cost, reliable alternative to traditional services that had the necessary direct force to pull the wellhead plugs. Developed primarily to set wellbore sealing devices that required additional stroke, an extended-stroke DPU was investigated to see if it would also generate the high force necessary to pull subsea wellhead plugs. The releasing latch mechanism attached to the bottom of the DPU was designed to latch into the plug, and the DPU was configured to engage a shoulder (no-go profile) located inside the wellhead tree bore. To ensure alignment between the latching tool and the plug, a centralizer was employed. The landing shoulder in the tree provides a predictable feature into which

the DPU can locate. While the DPU locates onto the landing shoulder, the latch simultaneously engages the fishing neck in the plug. The DPU thrusts down against the landing shoulder to apply upward retrieval force to the plug and continues to pull until the seals are released from the sealbore and the well equalizes. Once this occurs, the crown plug can be retrieved to surface using the slickline.

Similar to standard slickline pulling tools, the latch tool, with its external collet fingers that collapse while entering the internal plug profile, engages the crown plug. When fully engaged and located into the internal fishing profile of the plug, overpull is applied by the slickline unit to verify full engagement. Often, slickline bailing tools may be necessary for debris removal that has accumulated on top of the crown plug before engaging the internal fishing neck in the crown plug.

If for unforeseen reasons the latching tool needs to be released, an emergency release feature can cause pressure inside the riser to be increased, and the tool string can be returned to the surface. This latch-tool release is designed to release the collets from the fishing neck when pins are sheared by overpressure applied to the riser. The shear-pin values are determined for each well by the hydrostatic pressure at pulling depth. The water depth and fluid weight are used to correctly select the tool’s shear release pins.

The wellhead tree manufacturer establishes the size and location of the landing shoulder in the wellhead. The landing shoulder is typically located at the top of the tubing hanger running tool. The landing shoulder in the tree and the no-go on the DPU must be sufficiently strong enough to withstand the pulling forces and have fluid bypass (flutes, grooves, or holes) to prevent hydraulic lock (Fig. 1).

As shown in Fig. 2, the conventional no-go shoulder sleeve is dedicated to each specific subsea tree and machined to length and OD for a particular subsea tree. A more flexible no-go sleeve has been developed to cover a broad variety of subsea trees, and the entire length of the sleeve is threaded. It is much easier to machine a replacement nut for a no-go to accommodate different tree configurations.

Fig. 1. Downhole power unit, no-go sleeve, power rod, and the latch tool with centralizer.

Fig. 2. No-go shoulder sleeve.

Fig. 3. Subsea plug latch tool.

The latch tool used to pull the crown plugs is depicted in Fig. 3. The centralizer ensures that the latch aligns with the internal fishing neck in the crown plug. The same latch tool is compatible with the most common crown plugs and is sized for the internal fishing neck in the crown plug. The latch tool is designed with a pressure-assisted emergency-release mechanism. If an emergency release is required, the riser is pressurized to release the CP latch.

Case HistoryOn a job in the Gulf of Mexico for Statoil, the upper and lower crown plugs needed to be removed just below 8,000 ft. The marine riser was filled with 10.6 lbm/gal fluid. In an attempt to pull the upper crown plug, the crew initially ran a conventional pulling tool. While latched into the plug and to assist in pulling, an IWOCS pumped fluid in between the two plugs to decrease the differential across the plug. On two separate attempts, the crew was unable to pull the plug. There were indications that the IWOCS system had failed, and the downhole

Adjustable no-go nut

Full-length threaded sleeve

Conventional one-piece no-go sleeve

Collets

Centralizer

Centralizer

Plug latch tool

Power rod

No-Go ShoulderDPU

66

Bryce Sauser is currently an account representative – technical sales for Halliburton Slickline in Houston. He started with Halliburton in June 2011 as a Wireline and Perforating (WP) field engineer. He went through

slickline training courses and technical training before learning the advanced slickline tools. Previously, Bryce worked offshore as a field engineer for Halliburton WP Slickline, running conventional and advanced slickline tools. He holds a BS degree in mechanical engineering from Texas A&M University – Kingsville.

Gabriela Davalos is a senior drilling and well engineer operations for offshore Gulf of Mexico with Statoil. She holds a petroleum engineering degree from the University of Tulsa. After graduating,

she joined Schlumberger as a drilling engineer in 2002. Gabriela has held several drilling and well engineering positions throughout North and South America for onshore. In 2011, she joined Statoil in Norway as a senior drilling and well engineer for offshore operations. Currently, Gabriela is responsible for drilling and well operations for Statoil and partner-operated leases offshore Gulf of Mexico. She is an active member of SPE.

electrical power generator tool could provide more force at the plug to pull the upper crown plug with the full differential of the hydrostatic head. The program’s contingency program included a 3.59-in. extended-stroke downhole electrical power generator tool with a crown plug pulling tool, which was deployed and successfully pulled the crown plug. A conventional pulling tool was used again to pull the lower crown plug without success. The downhole electrical power generator tool was then used to retrieve the lower crown plug, and the attempt was successful. This system saves substantial rig time by preventing multiple unsuccessful attempts and uses more efficient conveyance.

ConclusionsThe extended-stroke DPU has distinct advantages when used as a crown plug pulling tool. Two methods are traditionally used to pull a crown plug—slickline or coiled tubing. In shallow water, conventional slickline with a jar is typically the first consideration. CT might also be considered in deeper water. Whether in shallow or deep water, the DPU should be the primary means of conveyance because it can provide some unique advantages, including:

Dependability• Dependability of the downhole power unit is

proven over its 20-year history.

• Pulling the lower crown plug all the way past the upper crown plug sealbore with the long-stroke (36 in.) DPU puts the plug above both tight spots.

Power• Hydrostatic pressure enhances the DPU forces.

• Full, slow, consistent power throughout the entire stroke is maintained.

• Constant pulling force does not create high-impact forces that can cause damage to fishing profiles.

Performance Monitoring• The audible “on” feature confirms that the tool is

properly configured for the downhole job.

• PCB provides a job history or memory logic in the DPU that details:

- Voltage used - Distance traveled

- Current used - Force generated

- PCB temperature

• A force overload shutdown helps prevent the tool from damaging itself and latched tools.

ReferencesBargawi, R.A., Dean, D., Clemens, J. et al. 2008. New Electro-Mechanical Perforating Technology Reduces Cost and Increases Safety in Workover Operations. Presented at the 2008 SPE/ICoTA Coiled Tubing and Well Intervention Conference and Exhibition, The Woodlands, Texas, 1-2 April. SPE-113805-MS. http://dx.doi.org/10.2118/113805-MS.

Foster, J., Clemens, J., and Moore, D. 2001. Slickline-Deployed Electro-Mechanical Intervention System, a Cost-Effective Alternative to Traditional Cased-Hole Services. Presented at the SPE Production and Operations Symposium, Oklahoma City, Oklahoma, 24 -27 March. SPE-67201-MS. http://dx.doi.org/10.2118/67201-MS.

McDaniel, D., Cromb, J., Walton, J. et al. 2008. Extended-Stroke Downhole Power Unit Successfully Pulls Subsea Wellhead Plugs. Presented at the SPE/ICoTA Coiled Tubing and Well Intervention, The Woodlands, Texas, 1-2 April. SPE-113806-MS. http://dx.doi.org/ 10.2118/113806-MS.

Savings• Faster rig-up times

• Cost of less operating hours

• Not having to displace fluids to lighten up the hydrostatic head

There is a huge value in the ability to provide enough power to pull crown plugs in a single run and in reduced time. For pulling subsea crown plugs that often require greater force than is possible with traditional conveyances, this setup is ideal because it does not require time and resources to reduce hydrostatic pressure or to rig up coiled tubing. Reducing time in subsea environments can significantly impact costs because of the extra equipment and logistics necessary to properly operate in those conditions. The track record for this configuration has shown that it is a viable and cost-effective option.

Jacques Babin is the global slickline product champion for Halliburton Wireline and Perforating, where his responsibilities include commercialization of new technologies around the globe.

Jacques also works with the Technology groups in Singapore, Houston, and Carrollton, Texas to provide support for field operations. Since joining Halliburton in 1995, he has held several field operations and managerial positions in deepwater operations in the Gulf of Mexico. Jacques is a member of SPE.

Jack Clemens is a technical advisor in the Halliburton Wireline and Perforating group. Jack has 30 years of industry experience through his work with Halliburton, as well as other oilfield-related jobs

prior to Halliburton. His area of expertise is downhole electromechanical tools. Jack earned a BSME from the University of Arkansas and is a registered Professional Engineer in the state of Texas. He has 14 patents and has coauthored numerous technical papers.

Authors

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