Digital Rock in Heavy Oil: Another Window on Petrophysics

Alberta Innovates – Technology Futures


Executive Editor’s Note

Digital-rock physics (DPR) is an emerging technology driven by rapid advances in 3D pore-scale imaging and computation. It merges three key technologies that have evolved rapidly over the last decade. One is high resolution diagnostic imaging methods that permit detailed examination of the internal structure of rock samples over a wide range of scales. The second is advanced numerical methods for simulating complex physical phenomenon and the third is high speed, massively parallel computation using powerful graphical processing units that were originally developed for computer gaming and animation. The resulting technology promises an unprecedented quantitative understanding of reservoir processes at the pore-scale. Complementing and enhancing conventional core analysis techniques, DPR could potentially be used as a building block in reservoir evaluation and characterization, development optimization, and performance predictions.

Gökhan Coskuner

Chairman, JCPT

 

Part of Alberta’s research and innovation system, Alberta Innovates-Technology Futures is helping to build healthy, sustainable businesses in the province. Through a suite of programs and services for entrepreneurs, companies, researchers, post-secondary institutions and investors, AITF provides technical services and funding support to facilitate the commercialization of technologies, develop new knowledge-based industry clusters and encourage an entrepreneurial culture in Alberta. www.albertatechfutures.ca

The Heavy Oil and Oil Sands group at AITF has an international reputation in developing and evaluating in situ bitumen and heavy oil recovery technologies, with unique facilities and extensive laboratory programs. Digital rock technology is one of many tools we use to better understand the mechanisms of in situ recovery.

Haibo Huang, PhD

General Manager, Heavy Oil and Oil Sands, AITF

 

Digital-rock technology obtains properties from high resolution images to show differences in the morphology and composition of rock. The promise of digital rock, as outlined in a previous article (Rassenfoss 2011), is for “faster, better, lower-cost analysis” of petrophysical samples. Unrestricted by the laboratory environment, this expertise complements traditional testing by understanding pore spaces and their connectivity in 3D images.

Alberta Innovates – Technology Futures (AITF) has an internally-funded program that adapts digital-rock technology to the study of unconventional petroleum resources, with a special focus on Canadian heavy oil and bitumen. Some of this is locked up in carbonate formations, which pose additional challenges to conventional analysis. AITF combines X-ray scanning and digital imaging to provide insight into these reservoirs on the pore scale. This report describes the current state of development.

 

Digital-Core Analysis

The primary goal of digital rock is to supply the services of special core analysis through detailed images of cores rather than through actual corefloods. The state of the art has been recently summarized by Blunt et al. (2013). Relative permeability and capillary pressure are predicted from fluid-flow simulations on the basis of high resolution 3D images of media.

The basic analysis consists of network-based simulation of multiphase fluid flow in the pore spaces and spatial averaging of the results to obtain macroscopic properties. Fig. 1 shows the network representation of a packing of silica sand that was generated at AITF—one that we use frequently for flow experiments—and the associated relative permeabilities obtained from ellipsoidal averaging volumes (not shown) overlaid on a simulation of multiphase flow.


Digital-rock examination allows the screening of multiple recovery scenarios involving changes to a reservoir that may affect production. The promise, ultimately, is for rapid, noninvasive characterization under a wide range of conditions. Extrapolation of conditions not attainable in a laboratory environment adds great value. We are working to extend the analysis to include behaviour in enhanced oil recovery (EOR) processes; more-focussed development, guided by industry participation, will ensue.

 

Imaging

AITF has access to four distinct methods of imaging, each addressing a different scale of resolution. Examples are shown in Fig. 2.


An entire core image in our medical X-ray computed-tomography (CT) scanner, with a nominal resolution of 350 µm, is typically the first step in the process. The resulting series of slices is assembled to highlight the makeup of the rock. These data can then be used to select plugs for closer examination with higher resolution imaging sources, but are also useful in their own right. Where large-scale features dominate flow behaviour (e.g., a vugular carbonate), direct-flow simulation at this scale may be representative and the size of sample that can be accommodated (up to 50 cm in diameter) captures heterogeneity over a wider range of scales. Alternately, this may provide input for simulation with a conventional reservoir simulator, as described next.

Micro-X-ray CT offers resolution down to a few µm—sufficient to view the pore space in typical reservoir sands—but with sample size limited by the beam intensity to a few centimetres across.

A synchrotron light source supplies an intense X-ray beam that can be used for microscale CT imaging, with enhanced-penetrating ability for larger samples. Unlike a conventional tungsten source, this can deliver a tuneable monochromatic beam, which allows for discrimination of materials on the basis of their attenuation spectra, by way of K-edge imaging, for instance. The coherent (i.e., uniform phase) nature of the tuned beam can also be exploited to detect subtle differences in material density.

Scanning electron microscopy (SEM) offers resolutions below 100 nm, suitable for shales and other tight rocks. Combined with focussed ion beam (FIB) milling, a sequence of SEM scans can be assembled into an extremely high resolution 3D image.

These spatial imaging methods are supported by X-ray diffraction analysis of mineral composition and nuclear magnetic resonance analysis for pore-size distributions.

 

Modelling

For studies of flow-related properties, a model of the pore space is extracted from the raw images. This is performed by inscribing spheres in the spaces identified as voids. From the spatial distribution of inscribed spheres, a detailed account of the connectivity of the void spaces is inferred, and this is used to construct a network representation of the pore space. Network-based models of multiphase flow incorporate both viscous and capillary effects; current early-stage development includes transport of solute and heat—major components of most EOR processes. Large-scale mixing of these components, driven by flow and tortuosity, arises naturally out of the pore-scale-flow simulation.

The morphological analysis can be inverted to yield a model of the solid space consisting of particles represented by spheres or agglomerations of spheres (Fig. 3).


By assigning properties to the interparticle contacts, commercial particle-modelling software is then used to simulate the bulk geomechanical behaviour (Fig. 4). This last step is still under development; as with flow simulation it must be calibrated, using the results of triaxial cell tests.


Finally, coarse-scale-image data from the medical scanner can supply direct input to a commercial thermal reservoir simulator. Although this is not pore-scale simulation, it offers many benefits, the greatest of which is access to a wealth of physical phenomena and fluid properties relevant to EOR processes. Moreover, it provides a bridge by which pore-scale simulation results can be scaled up to full cores (Fig. 5) and beyond.


A digital approach affords several advantages. Image analysis and simulation are simple and fast; a dirty sample can be digitally cleaned and reused any number of times, providing data for multiple processes and fluid properties. This technology is rapidly becoming a standard adjunct to experimental coreflooding. Digital rock does not stand alone as a research tool. Our extensive laboratory facilities afford many opportunities for calibration and validation—essential components of the method.

 

Experimental

AITF leverages its established expertise in laboratory studies of heavy-oil processes to add a novel dimension to digital rock—pore-scale experimentation. Traditional etched glass micromodels, designed for visual observation, are used to study oil/water/gas interactions. They have provided significant insights into foamy-oil behaviour, contributing to our kinetic field-scale model.

These 2D experiments are supplemented by a developing program of experimentation at the Canadian Light Source (CLS) synchrotron facility (Wysokinski et al. 2007). This laboratory can accommodate 3D imaging of dynamic experiments in real or realistic media, and has been used to observe the early stages of water transport in heavy-oil waterflooding (Fig. 6). Currently planned experiments will use some of the unique features of the beam (described previously) to observe the transport of solvent in solution. In the future, companion X-ray fluorescence studies, also available at CLS, will provide mineralogical information, which will guide simulations of wettability effects.

 


Carbonates

Bitumen-carbonate reservoirs are a special target for investigation by digital-rock technology, which provides new opportunities for evaluation and development of recovery processes. The growth in demand for these difficult, but resource-rich, formations is well served by this capability because these types of reservoirs are often difficult to analyze using other means over the range of relevant length scales. Morphology is characterized using a specially developed segmentation process for carbonates, providing distributions of pore sizes and 3D renderings of the pore structure (Fig. 7).


Vugs and fractures are identified on the basis of aspect ratios of bounding volumes, and the connectivity between them is inferred from the small changes in attenuation that accompany subpore-scale features. This static analysis is used to characterize and classify samples. Correlated with measured properties, it has provided insight into a wide range of carbonate-reservoir types (Fig. 8).

 

Ongoing Development

This is all part of an ongoing capability development program. The goal is to develop a complete package of pore-scale investigative capabilities for heavy-oil and bitumen resources, to complement AITF’s laboratory-scale facilities.

 

References

Blunt, M. J., Bijeljic, B., Dong, H. et al. 2013. Pore-Scale Imaging and Modelling. Advances in Water Resources 51 (January): 197–216. http://www.doi.org/10.1016/j.advwatres.2012.03.003.

London, M., Cameron, S. M., Donald, J. et al. 2014. Waterflooding Experiments with X-Ray CT Imaging. Presented at the SPE Heavy Oil Conference-Canada, Calgary, Alberta, 10-12 June. SPE-170147-MS. http://dx.doi.org/10.2118/170147-MS.

Rassenfoss, S. 2011. Digital Rocks Out to Become a Core Technology: J Pet Technol 63 (5): 36–41.

Wysokinski, T. W., Chapman, D., Adams, G. et al. 2007. Beamlines of the Biomedical Imaging and Therapy Facility at the Canadian Light Source—Part 1. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 582 (1): 73–76. http://www.dx.doi.org/10.1016/j.nima.2007.08.087.