Seismic inversion in the Barnett Shale successfully pinpoints sweet spots to optimize well­bore placement and reduce drilling risks Roxana Varga1*, Roberto Lotti2, Alex Pachos1, Ted Holden1, Iunio Marini2, Elena Spadafora2 John Pendrel1 1Fugro­Jason Inc.; 2 eni E&P,San Donato Milanese

Summary

A successful drilling campaign in an unconventional shale play usually brings together disparate pieces of relevant geological, petrophysical, and geophysical information to build a realistic and accurate model of the subsurface. Including seismic inversion information in the knowledge mix promises to be a game­changer because it can pinpoint sweet spots in the play, even with sparse well control. The sweet spots should have all of the ingredients to make wells profitable – good free gas volumes, good poro­ permeability, and brittleness (hence fracable). If the rock interval exceeds a threshold of brittleness, its fracability can be reliably estimated by the combination of Poisson’s Ratio and Young’s Modulus. These two mechanical properties are combined (Rickman et al, 2008) to indicate the rock’s propensity to fail under stress (Poisson’s Ratio) and to maintain a fracture (Young’s Modulus). In this Barnett Shale project, a simultaneous AVO inversion was used to demonstrate the feasibility of constructing a subsurface geological and geomechanical model describing the thickness and complex architecture of the brittle/fracable formation portion. This information can, in turn, be used to determine the optimal well bore trajectory. Considering that the Barnett Shale has a significant structural component, an accurate design of the well bore trajectory is required to remain within the bounds of the most appropriate facies. The ultimate result of strategic well bore placement is the maximization of cumulative volumes of hydrocarbon production per barrel of frac fluid.

Historical data show that productivity is a function of the induced fracture extent and how well the formation can maintain those fractures. Fracability, the propensity of the formation to fracture and maintain the fracture, is directly correlated with brittleness. In turn, the field results validate that the formation’s susceptibility to fracturing can be reliably predicted from the brittleness as calculated using Poisson’s Ratio and Young’s Modulus (Pitcher and Buller, 2012).

Introduction

The Mississippian­age Barnett Shale, located within the Bend Arch – Fort Worth Basin of Texas, is one of the most important hydrocarbon­bearing geologic formations in North America. The structurally deepest part of the Fort Worth Basin lies to the northeast where the Barnett Shale formation is more than 1000 ft (305 m) thick and

interbedded with limestone units; westward, it thins rapidly over the Mississippian Chappel shelf to only a few tens of feet (Pollastro et al, 2007). The Barnett Shale stretches over a dozen counties in northern­central and eastern Texas and protrudes into a small area of southwestern Oklahoma. Multiple tectonic events have structurally deformed the Barnett Shale so that it is very irregular and undulating (Figure 1). The Barnett Shale is the second largest producing on­shore domestic natural gas field in the United States, after the San Juan Basin in New Mexico and Colorado. The Barnett Shale covers an area of around 5,000 square miles (13,000 square kilometers). The field is proven to have 2.5 trillion cubic feet of natural gas.

Contributions from multiple geoscience disciplines over decades have shown that the Barnett Shale is organically rich, thermally mature, and vertically variable in its lithology and geomechanical properties. Additionally, the formation is simultaneously the source, reservoir and trap for hydrocarbons. Although the Barnett Shale was discovered in the 1950s, only in the 1980s was hydraulic fracturing proven to provide an escape flow­path for the

Figure 1: The top of the Barnett Shale is very irregular and undulating. Time data were used to create an image of the surface with an exaggeration of 1,1,2 (Inline 110 ft, Crossline 110 ft, Time 2 milliseconds).

Seismic inversion in the Barnett Shale

formation’s pent­up natural gas that led to the current boom in its natural gas production.

The formation permeability is in the micro­Darcy to nano­ Darcy range and porosity varies between 0.5 and 6%. This reservoir needs to be artificially fractured in order to produce gas.

In this project, a reprocessed 3­D seismic dataset (2011), consisting of three partial angle stacks (near 0º­20º, mid 20º­35º, and far 35º­50º), along with seven pilot wells, were prepared for an elastic inversion. Some of the survey wells penetrated water zones and displayed thickness variability and lateral lithologic changes. Major natural fractures were shown by seismic structural attributes in the eastern portion of the survey area. Approximately 116 square miles of AVO­compatible PSTM­processed 3­D seismic data were inverted to extract the Barnett Shale’s rock properties with a view to fully characterize structural and stratigraphic complexities in the sequence of interest, to identify intervals with favorable characteristics for drilling horizontal wells, possible fracture barriers, and potential hazards like water conduits.

Methodology

When an exploration or development project is undertaken, the data from various geoscience disciplines need to be integrated to develop a common subsurface description. Inversion of seismic data for elastic properties has become a standard part of the workflow for quantitative reservoir characterization. The Simultaneous AVO/AVA inversion process (Pendrel et al, 2000) transforms seismic data from interface to layer properties representing the elastic parameters of the rocks. The results of inversion by G&G data integration allow a more reliable interpretation given the reduced tuning and interference effects and the increased bandwidth compared to the seismic. The key properties natively derivable from AVO/AVA inversions are P­impedance, S­impedance and Density. The latter usually requires input angles exceeding 50 degrees unless other independent information is available. For this work, the density prior model was constrained with the Gardner constraint which stabilized the process by assuming a soft relation between pressure velocity (Vp) and Density. An example of P­impedance imaged from this procedure is shown in Figure 2. Various types of crossplots were used to investigate the relationship between mechanical/elastic characteristics such as brittleness, petrophysical properties, lithology and porosity. The resulting parameters served as attributes to build a template for the interpretation of the field data from inversion.

In Figure 2, the observed relation between the estimated P­impedance and V­quartz logs is shown. Using seismic

inversion we also quantified the Barnett Shale’s brittleness factor in a way that combines both Young’s Modulus and Poisson’s Ratio. Different facies can be recognized within Barnett Fm: ductile shale, by experience not so productive due to its proclivity to “heal any natural or hydraulic fractures” (Rickman et al, 2008). On the other hand the most brittle silty shale, characterized by a higher quartz fraction, is more likely to be naturally fractured and will be more prone to accept and sustain induced hydraulic fractures. Log crossplots of Young’s Modulus and Poisson’s Ratio were made as shown in Figure 3.

Poisson’s Ratio and Young’s Modulus volumes were computed from the results of the AVO inversion. The relation used for Young’s Modulus was

YM = 2*Is 2 *(1+ PR)/RHOB (1)

where ‘YM’ is Young’s Modulus, ‘Is’ and ‘PR’ are respectively the Shear impedance and Poisson’s Ratio derived from inversion, and ‘RHOB’ is the constrained, inverted density. Brittleness was also found to be related to the quartz mineral volume (Figure 4). Poisson’s Ratio and Young’s Modulus can be linked to the brittleness of the rock (Goodway et al, 2010).

Poisson’s ratio ‘PR’ was computed by the Vp/Vs ratio using the relation:

PR = [(Vp/Vs) 2 ­2]/[2(Vp/Vs) 2 ­2] (2)

The brittleness index was calculated via the following formula:

BRIT = [(YM­1)/7]+[(PR­0.4)/(­0.25)]*50 (3)

Where ‘BRIT’ is the brittleness, ‘YM’ is Young’s Modulus and respectively ‘PR’ is Poisson’s ratio. (Rickman et al,

Figure 2: P­Impedance derived from the simultaneous AVO/AVA deterministic inversion with V­quartz logs overlaid. High V­ quartz values (see arrow above) were associated with the more brittle zones in the Lower Barnett Shale.

Seismic inversion in the Barnett Shale

2008). A brittleness seismic­derived volume was then generated.

Geostatistical co­simulation was used to obtain a cube of quartz mineral occurrence, using the elastic parameters from inversion (P Impedance, S­Impedance and Density) matching the petrophysical properties from wells (volume of quartz and effective porosity). The final result was a volume of quartz obtained from the mean of 10 realizations (Figure 5).

The set of generated property cubes data was analyzed and interpreted as shown in the Figure 6 crossplot. A discrete number of litho/geomechanical facies were defined based on statistical techniques, controlling brittleness, quartz occurrence and kerogen presence. Therefore the following facies were identified: 1) high kerogen­low brittleness, 2) medium kerogen, 3) medium to high brittleness­high

quartz, 4) low quartz­low kerogen 5) high quartz­very high brittleness.

A joint Probability Density Function (pdf) is created for each lithotype as shown in Figure 6.

The set of prior probabilities for the lithotypes determines the relative proportions of each lithology. They are inputs to Bayes’ Rule formalism which generates lithology probability volumes from the inverted elastic property volumes. The final result consisted of five distinct lithology probability volumes indicating the estimated occurrence for each of the five defined facies.

Young’s Modulus vs. Poisson’s Ratio vs. brittleness (logs)

Young’s Modulus vs. Poisson’s Ratio vs. brittleness extracted from inversion results

Figure 3: Log crossplots of Young’s Modulus vs. Poisson’s Ratio vs. V­quartz and respectively vs. Brittleness in the figure below. The arrow shows the directon of increase in brittleness and V­quartz percentage.

LITHOLOGY:

Figure 4: The log plot displays a quartz­rich zone bounded by two clay­rich zones. The quartz­rich sweet spot in this log plot, is characterized by relatively higher porosity and higher brittleness.

Figure 5: The volume of quartz obtained from the mean of ten realizations using co­simulation. V­quartz logs are overlaid. The interval shown is from the Top Barnett to the Top Viola.

Seismic inversion in the Barnett Shale

Figure 7 shows the most likely lithology which is the result of a joint analysis of all five probability volumes.

Conclusions

The Barnett Shale is a quite complex formation from both structural and stratigraphic point of view. The integration of well data and seismic inversion sub­products, mainly lithological, geomechanical and structural parameters, can be used to create a 3­D model allowing a better delineation and the deliberate management of subsurface heterogeneities for drilling and production optimization purposes.

Facies Probabilities pdfs

Figure 6: Pdfs (Probability Density Functions) of predicted volume of quartz vs. predicted brittleness. The five numbered zones each enclose similarly colored clusters of data points that indicate the different lithotypes.

Figure 7: Cross­section of the most likely lithology correlated across all of the wells from the Top Barnett to the Top Viola.

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SEISMIC INVERSION IN THE BARNETT SHALE SUCCESSFULLY PINPOINTS SWEET SPOTS TO

OPTIMIZE WELL-BORE PLACEMENT AND REDUCE DRILLING RISKS

SEISMIC INVERSION IN THE BARNETT SHALE SUCCESSFULLY PINPOINTS SWEET SPOTS TO

OPTIMIZE WELL-BORE PLACEMENT AND REDUCE DRILLING RISKS

*Roxana Varga 1, Roberto Lotti 2, Ted Holden¹,Iunio Marini², John Pendrel ¹, Elena Spadafora² and Alex Pachos¹

*Roxana Varga 1, Roberto Lotti 2, Ted Holden¹,Iunio Marini², John Pendrel ¹, Elena Spadafora² and Alex Pachos¹

1 Fugro-Jason, Inc.2 eni E&P, San Donato Milanese

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Scope

Introduction

Methodology

Summary

Prior / Pre-planning Well Results

Conclusions

Scope

Introduction

Methodology

Summary

Prior / Pre-planning Well Results

Conclusions

OutlineOutline

3

Scope

Project objective: Identify optimum areas and layers for placement of horizontal well trajectories

Perform AVO simultaneous inversion and computed a brittleness volume from Poisson’s Ratio and Young’s Modulus

Evaluate relationships between Petrophysical, Mechanical and Elastic Properties and identify five different LithoFacies based on co-simulated V-Quartz, Brittleness and Kerogen content

Create 3D Model in depth of the probability of optimum LithoFacies, illustrating its complex distribution and thickness in the Barnett Shale

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Barnett Shale – Fort Worth Basin – North TexasBarnett Shale – Fort Worth Basin – North Texas

IntroductionIntroduction

Barnett Shale – Texas mapLocations of the Barnett Formation. Source: USGS

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Hydraulic fracturing is required to obtain commercial production rates

Avoid placing well through a fault that extends into the Ellenberger

A ductile shale layer below the horizontal well bore can isolate water from the Ellenberger below

Importance of Vertical Geomechanical Barriers for Hydraulic Fracturing

Importance of Vertical Geomechanical Barriers for Hydraulic Fracturing

IntroductionIntroduction

Stratigraphic column, Forth Worth basin (Montgomery et al. 2005)

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Structural DeformationStructural Deformation

Multiple tectonic events have deformed and fractured the Barnett Shale layer,

resulting in a structurally deformed reservoir with natural fracture systems.

Negative Curvature Positive Curvature

IntroductionIntroduction

Structural deformation developing a

natural fracture system

Strong vertical and horizontal variability

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IntroductionIntroductionWell PatternsWell Patterns

~ 250 ft between trajectories

Trajectories and well information from Texas Rail Road Commission

OPTIONS

Take a chance and place well

trajectories without knowing

the location of the optimum

LithoFacies

or

Optimize for longer propped

fracture lengths with better

placement of trajectories

Avoid spending $ on

fracturing ductile layers

Place wells where a fracture

conductivity barrier exists (a

clay rich ductile interval)

above the water zone below

Avoid major faults that

extend into the water zone

below

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DataData

Upper Barnett time horizon

• Merged 3D seismic survey with three angle stacks:

0 – 20 degrees20 – 35 degrees30 – 50 degrees

• Interpreted Horizons: Marble Falls, Barnett, Forestburg, Viola

• 20 Wells: Seven chosen with P and S-Sonic Logs, Vp/Vs and Density logs

IntroductionIntroduction

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Choose the right petrophysical modelChoose the right petrophysical model

IntroductionIntroduction

Typical well log with lithological volumes

Permeability: Nano to Micro DarciesPorosity: 1-10%Organically Rich Shale: Thermally MatureHigh Vertical Variability in terms of Lithology and Brittleness

Permeability: Nano to Micro DarciesPorosity: 1-10%Organically Rich Shale: Thermally MatureHigh Vertical Variability in terms of Lithology and Brittleness

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Why invert the data? Why invert the data?

MethodologyMethodology

Interval – Forestburg - ViolaInterval – Forestburg - ViolaInterval – Forestburg - Viola

To exploit meaningful

relationships between elastic

properties from seismic inversion

and beneficial petrophysical

properties from wells

How to use the inverted data? How to use the inverted data?

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4

13

2

5

Facies related to Brittleness / FracingFacies related to Brittleness / Fracing

Brittleness - V Quartz - Kerogen Brittleness - V Quartz - Kerogen

Interval – Forestburg - Viola

Kerogen

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Define facies related to Brittleness / Rock Physics properties / Elastic properties

Use simultaneous AVO inversion to derive elastic properties for P-Impedance, S-Impedance and Density

Compute Poisson’s Ratio, Young’s Modulus and Brittleness index volumes from simultaneous inversion results

Use geostatistical co-simulation to compute a quartz volume from inversion results calibrated to the wells

Define several litho-facies based on probability distributions from crossplots of the co-simulated quartz volume, brittleness index and presence of Kerogen

Final results indicated the probability of occurrence of five distinct LithoFacies volumes

Final interpretation: An integrated stratigraphic interpretation with structural elements from Coherency and Curvature data

MethodologyMethodology

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Well 1 Well 2 Well 3 Well 4 Well 7Well 6Well 5

Inverted Full-Band P-Impedance Volume

Simultaneous AVO InversionSimultaneous AVO Inversion

Well 1 Well 2 Well 3 Well 4 Well 7Well 6Well 5

Inverted Full-Band S-Impedance Volume

MethodologyMethodology

P-Impedance

S-Impedance

Curves from Wells: above P-Impedance and below S-Impedance

• PR = [(Vp/Vs)² -2] / [2(Vp/Vs) ² - 2] (1)

• YM = 2*Is² *(1+ PR) / RHOB • Where: (2)

– Is= S Impedance from simultaneous inversion– PR=Poisson’s Ratio calculated based on (2)– RHOB=Density from simultaneous inversion

• BRIT = [(YM-1) / 7]+[(PR-0.4) / (-0.25)]*50 (3)• Where:

– BRIT=Volume of Brittleness– Brittleness curves were computed from well logs and a Brittleness Volume was

computed from Inversion and co-simulation results

Poisson’s Ratio, Young’s Modulus and Brittleness volumesPoisson’s Ratio, Young’s Modulus and Brittleness volumes

MethodologyMethodology

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15

Young’s Modulus was calculated based on inverted Density volume

Inverted Poisson’s Ratio volume

Poisson’s Ratio and Young’s Modulus are linked to rock brittleness

Poisson’s Ratio and Young’s Modulus are linked to rock brittleness

Well 1 Well 2 Well 3 Well 4 Well 7Well 6Well 5

MethodologyMethodology

Curves from Wells: above Young’s Modulus and below Poisson’s Ratio

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Computed Brittleness VolumeComputed Brittleness Volume

Brittleness calculated based on equation (3)

Brittleness

Brittleness Index Curves from Wells

MethodologyMethodology

Well3 Well4 Well5 Well6 Well7Well1 Well2

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Co-Simulation of Quartz VolumeCo-Simulation of Quartz Volume

V-Quartz Curves from Wells

The Summary of 10 Realizations

V-QuartzWell3 Well4 Well5 Well6 Well7Well1 Well2

MethodologyMethodology

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Distributions of V-Quartz vs BrittlenessDistributions of V-Quartz vs Brittleness

Litho-Facies Types

MethodologyMethodology

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Integrated Stratigraphic Interpretation with Structural ElementsIntegrated Stratigraphic Interpretation with Structural Elements

MethodologyMethodology

Most Positive and Negative curvatureStratal slices 12ms below ForestburgStratal slices 25ms below ForestburgStratal slices 12ms above ViolaStratal slices 5ms above Viola

V-Quartz Curves from Wells

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SummarySummary

Identified brittle shale zones using Simultaneous AVO Inversion results integrated with Petrophysical & Mechanical Properties from wells

Constructed a 3D Model in depth of five distinct LithoFacies for a delineation of fracable strata

Depth-based model permits pre-planning of horizontal wellbores within the optimum layer while maintaining a barrier of more ductile clay-rich shale between the horizontal well bore and the Ellenberger below

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Total Frac Fluid Pumped: 85,036 Bbl

Avg. monthly production: 43 million scf gas

MCF/Month per Bbl Frac Fluid: 0.51Average for first five months of well production

Well bore trajectory is below the optimum layer

One of the lower “production / frac” ratios

Prior Well Results

Trajectories, frac size and production data from Texas Rail Road Commission

Litho Types

5

4

3

2

1

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Prior Well ResultsFrac Fluid Pumped: 4,724 Bbl

Average monthly production: 60 million scf gas

MCF/Month per Bbl Frac Fluid: 12.9Average for first five months of well production

Well bore trajectory remains within the brittle layer

One of the higher “production/frac” ratios

Trajectories, frac size and production data from Texas Rail Road Commission

5

4

3

2

1

Litho Types

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ConclusionsConclusions

The 3D results from this work can used as part of an integrated reservoir model

This workflow optimizes horizontal well placement by pre-planning and positioning the wellbores in the best area and within the strata most suited to hydraulic fracturing and production

Offers huge economic potential for future unconventional plays

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AcknowledgementsAcknowledgements