determining water saturation from capillary pressure in ......the combination of these methods...

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Introduction

Capillary pressure is an important characteristic of rock that helps reservoir engineers determine where hydrocarbons and water are located in the subsurface. This characteristic can be measured from core samples analyzed in a laboratory setting and compared to other measurements taken in the field. Capillary pressure analysis can lead to optimized drilling programs, allowing reservoir engineers to find the extent of the hydrocarbon accumulations and avoid drilling into water.

This study combines well information including logs and capillary pressure from cores to determine height above free water and create a water saturation curve that can be compared to log-derived water saturation. The study also demonstrates that the capillary pressure model generated for one well can be applied to other wells in the field as long as there is no sealing fault to obstruct fluid flow.

The Arctic Alaska Petroleum Province extends from the Brooks Range-Herald Arch north to the edge of the continental shelf and from the U.S.-Canadian border west to the maritime boundary with Russia. By 2005 the province had produced about 15 billion bbls of oil, and more than 20 additional oil and gas discoveries remained undeveloped.

One of the prospects in the province is Liberty Field. Located southeast of the Endicott Field, the Liberty accumulation is estimated to contain about 125 million bbls of recoverable reserves. Like the Endicott Field, the Liberty is a structural-stratigraphic trap involving north-west trending faults and reservoir truncation by the Lower Cretaceous Unconformity.

Four wells have been drilled in the area. The Tern #3 and Liberty #1 wells indicated the presence of producible hydrocarbons within the Kekiktuk Zone 2 reservoir. According to British Petroleum (BP), both these wells also encountered a ‘tar mat’ in the Zone 2 reservoir at the base of the movable oil column.

Determining Water Saturation from Capillary Pressure in Liberty Field, AlaskaJim Lewis and Fred Jenson

Figure 1a: Arctic Alaska Petroleum Province, showing locations of principal geologic features (Houseknecht and Bird, 2006; Bird, 2001). b/c: Liberty Field location map and structural cross-section. (extracted from BP Exploration (Alaska), Inc., 2007.


In Liberty #1, the tar mat lies near the base of Zone 2 at 10,932 ft TVDSS; above it, the oil column extends to the top of the reservoir at 10,707 feet. No gas cap was encountered in this well.

In Tern #3, the tar mat extends from 10,922 to 11,045 ft TVDSS. Above it, the first eight feet in the Zone 2 reservoir (10,914 to 10,922 feet) appear to have movable hydrocarbons. Below the tar mat, a water leg occurs in the lower portion of the reservoir.

Laboratory data for Tern #3 was evaluated, conditioned and converted to the reservoir fluid system. Liberty #1 was used as the control well, to demonstrate that the model from Tern #3 could be extended to the field.

Background

Each rock and fluid type has unique features that can be determined by laboratory measurements. These physical features can be matched to field data

collected through well logs, cores, borehole images and other well data. This matching process enables the reservoir engineer to classify the rocks and fluids in the field of study. Reservoir engineers are particularly interested in identifying the gas/brine, gas/oil and oil/brine interfaces.

The pore spaces inside of rocks are microscopic, giving capillary forces a significant effect. Their densities, surface tension and the curvature due to the spaces between pores make different fluids have different pressure and as relative saturations change, pressure difference also changes. Typically, capillary pressure is measured using mercury injection, porous plates or centrifuge.

From capillary pressure, reservoir engineers can discover:

• Hydrocarbon/water contacts, even if they are below the total well depth

• Rock types in the zone(s) of interest

Figure 2a: Slabbed Conventional Core, Interval 12976.6 to 12991.1 feet (red arrow & text added to show Plug #3).Figure 2b: Core Slab with Cap Pressure Plug location for Plug #3, 12,989.30 feet.Figure 2c: Core Slab with Cap Pressure Plug location for Plug #9, 13,216.55 feet.Source a: Alaska Department of Natural Resources, Alaska Geological Materials Center Data Report No.336.Source b/c: Alaska Department of Natural Resources, Alaska Geological Materials Center Data Report No.338.

Figure 3a: SEM image, 70x, for Plug #3, 12,989.30 feet.Figure 3b: SEM image, 700x, for Plug #3, 12,989.30 feet.Figure 3c: Thin-Section image for Plug #3, 12,989.30 feet.Source: Alaska Department of Natural Resources, Alaska Geological Materials Center Data Report No.338.


• Heights of transition zones

• Connectivity across the field

Measurements from the field are often compared to laboratory analysis both as a quality control step and to broaden the analysis. For example, the water saturation and height above free water can be calculated from resistivity and other wireline logs and then compared to the depth converted laboratory core measurement of capillary pressure. The combination of these methods provides confirmation of the reliability of the analysis.

Data Acquisition

Capillary pressure plug data from conventional core was obtained from the Alaska Department of Natural Resources for the Tern #3 well. A total of 422 feet of core was recovered, but only ten plug samples comprised this capillary pressure data set.

A set of core slab photographs (indicating the plug locations), thin sections images, and scanning electron microscope (SEM) photographs indicated that there was a grain size, therefore pore size, difference between the three shallowest plugs and the deeper plugs. All ten plugs were treated as a set.

The remainder of the standard porosity and permeability measurements (191 samples) over the complete core were obtained from the Bureau of Ocean Energy Management (BOEM) through a Freedom of Information Act (FOIA) request.

A comprehensive logging package (circa 1987) for the Tern #3 consisted of conventional wireline log data (gamma ray, spontaneous potential, caliper; spherically focused, medium induction, and deep induction resistivities; sonic travel time, bulk density, and neutron and density sandstone porosities) were also obtained from the Alaska Department of Natural Resources. Other data gathered included geological tops, TOC (total organic carbon), rock-eval pyrolysis, whole oil gas chromatograms, directional surveys and surface location maps.

Comparable data for the other three wells—the

OCS-Y-0195 1, Tern #1; the OCS-Y-0196 1, Tern #2; and the OCS-Y-1650 1, Liberty #1—were also obtained from the Alaska Department of Natural Resources. Capillary pressure data was available only for the OCS-Y-0197 1, Tern #3 well.

No seismic data was obtained or used in this analysis.

Data Loading

All well data—including logs and cores—were loaded into PowerLog® for analysis. Quick analysis showed that the Tern #3 well had an apparent 232 foot hydrocarbon bearing section, overlaying a well-defined waterleg. Three of the cap pressure plugs were found to be located at the top of the interval, with the remaining seven located in the waterleg. The information released by British Petroleum (BP) stated that a tar mat existed between near the top of the interval and water zone. No mid-zone cap pressure plug samples were available, likely because of the presence of the tar mat.

The conventional core measurements of porosity, permeability, and grain density from the 191 plugs, which were taken from the 422 feet of core,

Figure 4: MICP (mercury-injection capillary pressure) measurements for Plug #3, 12,989.30 feet. Source: Alaska Department of Natural Resources, Alaska Geological Materials Center Data Report No.338.


indicated that the core depths were approximately 13.25 feet deep to the log measurements. Within the cored interval of 12,915.0 to 13,361.5 feet, the core slab photographs indicated oil stained sandstones, several coal sections, and a brecciated interval from 12,930 to 12,976 feet.

The log resistivities in the Tern #3 were unusually high, sometimes exceeding 2000 ohm-m, and therefore suspect. The logging program included only induction-based resistivity curves which are often unable to accurately measure formation resistivities when their values exceed 200 Ohm-m. Two successful wireline-conveyed Repeat Formation Tester (RFT) fluid samples (unidentified types) were reported to the state of Alaska, one of these was taken over the interval indicated as permeable by the microlog and the other was taken very near the water. No mention of a tar mat was found in any of the available state filings by Shell Western E&P,

Inc. (SWEPI), who drilled the Tern #3 well. Initial impressions of the logs were that the Liberty #1 well looked normal and did not penetrate water.

The high log-measured resistivities in the Tern #3 were suspect, as the logging program only included the induction curves, which typically are unable to resolve resistivities when they exceed 200 Ohm-m. Considerable separations between values were present for the three resistivity measurements over the Kekiktuk Zone 2 reservoir. If an impermeable tar mat were present, no mud filtrate invasion would be possible and the resistivity logs should have had near identical values for the shallow, medium and deep resistivities.

Data Conditioning

Before modeling and analysis, the data was reviewed for any needed corrections. Capillary pressure data corrections were applied to correct laboratory data for borehole conditions. Any extraneous or suspect data—including individual points, an entire series or complete collection—could have been excluded at this time as well.

Saturation data was converted from percentages to decimal values and the rock quality index was calculated. Although the PowerLog Capillary Pressure module provides an opportunity to apply stress and clay corrections, these corrections were not required for this reservoir.

Moving to the Reservoir Fluid System

Option Value Descriptionσ Res 25 interfacial tension in reservoir (oil-water)θ Res 30 contact angle in reservoir (oil-water)σ Lab 485 interfacial tension in the lab (mercury-air)θ Lab 140 contact angle in lab (mercury-air)

Table 1: MICP interfacial tension and contact angle constants for laboratory measurements and reservoir conditions. Source: OMNI Laboratory, Alaska Department of Natural Resources, Alaska Geological Materials Center Data Report No.338.

Following data correction, the fluid system used in the laboratory was converted to the fluid system found in the reservoir. Capillary pressure is a

Figure 5: Tern #3 Log Plot. Source: Data from Alaska Department of Natural Resources.


function of the interfacial tension between two immiscible fluids and the contact angle between the wetting phase and the rock surface. Consequently, to convert data from one fluid system to the other, interfacial tensions (σ) and contact angles (θ) are needed.

The Leverett J-function was used to normalize capillary pressure data to take into account variations in porosity and permeability. This method is useful for averaging capillary pressure data derived from a given rock type and reservoir and, with caution, can sometimes be extended to different reservoirs with the same lithology.

A quality control check of the oil/water height values recorded in the lab showed that they were consistent with the values calculated in PowerLog. Similarly the plug J-Function values obtained from the lab agreed with those calculated by PowerLog.

Modeling Capillary Pressure Data

Model input data were normalized for porosity and permeability using the Rock Quality Index function. A regression was then performed to fit the normalized data using a single equation for all curves.

Capillary pressure models can be built using one of three different approaches.

• Separate Equation for Each Curve—The model is the regression equation that provides the best fit to the input plug data. Several types of regressions can be run, including Thomeer (G-function) and Skelt Harrison. A separate regression equation is generated for each plug. The method for how coefficients developed for each plug are combined to yield the coefficients in the final model is then specified. Methods include taking the average, taking the median, or doing a linear regression of plug coefficients versus some specified attribute.

• One Equation for All Curves—The model is the regression equation that provides the best fit to the input plug data. All the input plug data are taken together to develop a single, combined equation. A variety of methods for normalizing the input data including Leverett

J-function, Cuddy, Rock Quality Index, and Johnson are available. The algorithm for normalizing the data (for variations in porosity, permeability, or both) was used as an input in the regression equation.

• Spatial Averaging—The model is a collection of array attributes and single-value attributes from input plugs. For example, for a saturation versus pressure model, the model might consist of saturation and pressure arrays and porosity and permeability values. Attributes are specified and the input data, in essence, becomes the model. No equation is generated. When a spatial averaging model is applied, the water saturation (Sw) for each sample in the target well is computed based on its proximity to the corresponding plug data attribute values. A sequence of linear and inverse distance weighting interpolations is performed.

Figure 6: Liberty #1 Log Plot. Source: Data from Alaska Department of Natural Resources.


In addition to the model, all three approaches output a new saturation attribute. This attribute was compared to the original to evaluate the model. Because the “one equation” approach was used, a J-function attribute was also output and compared to original data.

Crossplot QC

Quality control is a critical aspect of any subsurface analysis. Following the regression, several crossplots were generated to verify the results. These compared the modeled water saturation to:

• Pressure

• Height

• J-function pressures

• Rock Quality Index height

These crossplots showed the related fit of the regression to the input data as well as the match between the corrected laboratory-based water saturation and the modeled capillary pressure-based water saturation. Small adjustments were made to saturation, pressure and height cutoffs. Although individual data points or entire plugs could have been marked as invalid, none were marked in this case.

The regression was rerun several times until the data was in agreement.

Applying the Model

Once the water saturation model was built, it was applied to the well and compared to water saturation calculated from resistivity. There was a good agreement between the two models.

After verifying the veracity of the Tern #3 analysis, the model was applied to the Liberty #1 well. In general, capillary pressure models are applicable to wells in the same field and with similar porosity regimes and lithologies.

The water saturation-versus-pressure model was converted to a water saturation-versus-height model by replacing the pressure attribute with height above free water level (in true vertical depth), reservoir porosity and permeability. The output was a water saturation curve which had no dependency on a resistivity log measurement.

Using a structure map, the water saturation model derived from capillary pressure can be applied across the field to determine hydrocarbons present. This approach assumes that the rock is the same everywhere within the study area—deposited

Figure 8: Tern #3 CPI (computer-processed interpretation) with saturation comparison.

Figure 7: A Comparison of Capillary Pressure Based Saturations vs Height above FWL (Swcorrected from data conversion from laboratory to reservoir and SwModeled from Rock Quality Index Method Regression).


under the same conditions from the same source and with the same porosity and permeability. As long as there are no sealing faults, water level can be safely assumed to be the same, because water seeks the same level. If there are multiple zones with the same free water levels, then the zones are in communication. This helps determine compartmentalization.

Conclusions

The capillary pressure model developed from one well successfully predicted the water saturation data in another well within the same field. By applying the two separate saturation models, one based on the fine-grained samples and the other based on the coarse-grained samples, a prediction might have been possible for an expected range of water saturations for the two rock types for comparison to the actual log based water saturation.

The capillary pressure analysis of Tern #3 provided a more consistent indication of water saturation than using the traditional resistivity-based computed saturation. The water saturation curve proved consistent with Liberty #1, for which there were no capillary pressure measures available and water had not been contacted. The analysis demonstrated the ability to use capillary pressure data from one well to calculate height above free water for any other

well within the same connected reservoir even when there is no water contact. Understanding where the fluid contacts are leads directly to improved decision-making in the drilling program.

Managing all well data in a single database provides great value for iterative analysis and future modification. It also enables geoscientists to review how the data was used in the model, what assumptions were made and what calculations were applied. It makes it easy to add more data as it is acquired, enhancing the model. This practice ensures consistency across the field lifecycle.

References

Alaska Department of Natural Resources, Division of Oil and Gas, 2011, Point Thompson Area.Available online at: dog.dnr.alaska.gov.

Bird, K.J., 2001. Alaska; a twenty-first-century petroleum province, in Downey, M.W., Threet, J.C., and Morgan, W.A., eds., Petroleum provinces of the twenty-first century: American Association of Petroleum Geologists Memoir 74, p. 137–165.

BP Exploration (Alaska) Inc., 2007. Liberty Development Project Development and Production Plan. Submitted to U.S. Minerals Management Service. Anchorage, Alaska.

Holmes, Michael. “Capillary Pressure & Relative Permeability Petrophysical Reservoir Models.” Digital Formation, 2002.

Houseknecht, D.W., and Bird, K.J., 2006. Oil and gas resources of the Arctic Alaska petroleum province: U.S. Geological Survey Professional Paper 1732-A, 11 p., available online at: http://pubs.usgs.gov/pp/pp1732/pp1732a/index.html.

Omni Laboratories, Inc., 2007, Core analyses of the Shell Oil Company OCS Y-0197-1 (Tern Island #3) well (12977.25’-13221.35’); which includes permeability and porosity data, mercury injection capillary pressure data, X-ray diffraction dat, sample photographs, petrographic thin-section photographs, and SEM photographs: Alaska Division of Geological & Geophysical Surveys Geologic Materials Center Data Report 338, 41 p.

Shell Oil Company and Alaska Geological Materials Center, 2006, Core Photographs (12915’-13361.5’) dated June 2003 of the Shell Oil Company OCS Y-0197-1 (Tern Island #3) at the Alaska GMC: Alaska Division of Geological & Geophysical Surveys Geologic Materials Center Data Report 336, 3 p.

Figure 9: Liberty #1 CPI with saturation comparison.

determining water saturation from capillary pressure in ......the combination of these methods...

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