Reservoir characterization uses digital rock physics

The Wolfcamp Formation has emerged as a major unconventional resource play in Texas. There is a wide range of oil vs. water production observed in the hundreds of horizontal wells that have targeted this formation. This variability has become a serious challenge and leads to increased risk for many operators, and there is a strong need to understand the cause. Using slabbed core from the Texas Bureau of Economic Geology (BEG) in Austin, Texas, digital rock physics (DRP) have been applied to look for some clues. The well will be referred to as Wolfcamp-1 and is located in the southern Midland Basin.

The 51.2-m (168-ft) cored interval from Wolfcamp-1 was X-ray computed tomography (CT) imaged using a dual-energy method. These data were used to select the exact locations where plug samples were needed to begin to understand the rock characteristics. Additional detailed analysis was conducted on these plug samples to define and quantify the key shale reservoir properties.

FIGURE 1. A 5.5-m (18-ft) depth interval of CoreHD data (RhoB, facies, PEF) from the Wolfcamp 1 well shows the large variability over small depth changes. (Source: Ingrain Inc.)

Methodology

DRP technology, developed by Ingrain, was applied in the Wolfcamp-1 well using a workflow especially designed for the characterization of shales. During Phase 1, CoreHD dual-energy X-ray CT imaging was carried out with a voxel resolution of about 0.5 mm. From this imaging, Ingrain computed a high-resolution vertical profile of rock bulk density (RhoB) and photoelectric factor (PEF). Bulk density is an indicator of porosity and organic matter content, while PEF is an indicator of mineralogy. The density and mineralogy information can be used to define shale facies.

This process was used to separate the data into five facies classes and was used to characterize and identify the zones of higher reservoir potential. In Figure 1, the second track to the left of the depth track shows the facies. Red and green facies represent higher porosity and/or organic content, with green being more silica-rich than red. Light blue is a more carbonate-dominated zone. These data can be generated in a matter of hours after core has been recovered, thereby aiding in horizontal wellbore placement and stimulation design.

FIGURE 2. This high-resolution SEM image from the Wolfcamp-1 well at 2,416 m (7,928 ft) clearly shows PA_OM. (Source: Ingrain Inc.)

In Phase 2 of this shale core program, plugs were selected for greater analytical detail. Initially they were X-ray CT imaged at a resolution of 40 microns/voxel. These CT volumes not only were used to guide the selection of subsamples but also are part of a very important visual catalog. During this second phase, scanning electron microscope (SEM) analyses were also conducted on ion-milled samples. SEMs allow Ingrain to obtain high-resolution images of the shale mineral grains, solid organic material and pore space. These images, as shown in Figures 2 and 3, were digitally analyzed to quantify the amount of organic matter, organic porosity, porosity associated with organic matter (PA_OM), intergranular porosity and high-density minerals (usually pyrite) present in the samples.

During Phase 3 of this project, 3-D volumes of digital rock images were obtained from FIB-SEM (focused ion beam combined with SEM). These image volumes have a voxel resolution of about 5 nm to 15 nm and form a digital rock volume that is used for computing permeability and other types of special core analysis data. Figure 4 shows an example. Segmentation and image processing allow the separation of the solid mineral, organic matter and pore space of these 3-D objects. Absolute permeability was calculated in each 3-D FIB-SEM volume using a numerical method known as Lattice-Boltzmann.

FIGURE 3. An SEM image from the Wolfcamp-1 well at 2,443 m (8,016 ft) shows predominantly intergranular porosity. (Source: Ingrain Inc.)

Results and findings

In addition to total porosity, connected porosity, solid organic matter and PA_OM, researchers also computed vertical permeability, horizontal permeability and pore size distribution. Results of these tests and hundreds of others performed over several years show that the Wolfcamp formation not only has large variability in porosity and permeability but that organic porosity and intergranular porosity are both common. In addition, both types of porosity are well-interconnected and can contribute to fluid flow.

If it is assumed that the organic-hosted porosity is primarily filled with oil or gas and that water resides mainly in the intergranular pores, then these data may help explain why some completions result in greater water cut than others. This also suggests that a good strategy might be to analyze a sufficient number of samples to determine which zones have the highest net organic porosity and then select landing zones for greater PA_OM, not just higher porosity in general. Figure 5 shows the total porosity vs. horizontal permeability for Wolfcamp-1 compared to the upper and lower bounds determined from other Wolfcamp samples in the Ingrain database.

FIGURE 4. High-resolution 3-D FIB-SEM volumes are shown from the Wolfcamp 1 well. In both images, green is solid organic material, blue is connected porosity, red is isolated porosity and the solid mineral grains are transparent. Note that the sample on the left (2,416 m [7,928 ft]) has much of its connected porosity closely associated with organic material, while the sample on the right (2,443 m [8,016 ft]) has essentially no organic material or PA_OM. (Source: Ingrain Inc.)

Reducing water cut

The collection and integration of the data from this DRP study of samples from the Wolfcamp Formation shows that rock types, porosity and permeability are highly variable and that data from the Wolfcamp-1 well are typical of other Wolfcamp samples. The DRP analysis further shows that some samples have mostly intergranular pores, while other samples have mostly porosity inside the organic material. Both types of samples may have relatively high porosity and permeability. If water resides mostly in the intergranular pores and hydrocarbons are more common in the organic pores, water cut may be reduced by targeting the completion in the intervals with greatest organic porosity.

Acknowledgments
The author would like to thank the BEG for allowing access to core samples from the BEG core storage facility in Austin, Texas. Thanks also to Juliana Anderson and Elliot Walls of Ingrain Inc. for review and editing.

FIGURE 5. These trend lines show how samples from the Wolfcamp-1 well compare to the upper and lower trend lines from other Wolfcamp samples in the Ingrain database. Permeability in this figure was computed in the horizontal plane using FIB-SEM digital rock volumes. (Source: Ingrain Inc.)