Digital Rock Physics Research Articles

Simulation of gas flow in organic-rich mudrocks using digital rock physics

Organic-rich mudrock systems play an important role in the world's volatile petroleum industry. Due to their complex pore structures with a large portion of nano pores, the flow mechanics of gas flow in the pore space may involve nanoscale effects that could not be accounted for by classic Darcy's law. It is also very difficult to experimentally probe the transport properties of extremely low permeability rock samples. Digital rock physics (DRP) obtains a direct view of the internal structure of reservoir rock sample by digitized high resolution images to compute their properties, such as porosity and directional permeability, and hence to enable the studies of multi-scale flow mechanics in mudrocks. In this study, we present a parallel lattice Boltzmann method (PLBM) for studying nanoscale effects on a three dimensional (3D) tube flow, and then to simulate the flow process of the gas flow in real 3D pore geometry of two perpendicularly cored mudrock samples (S62H and S62V), combining with some image processing methods in DRP. The pore geometry is obtained by 3D digital image data based on ultra-high resolution X-ray computed tomography (XCT) imaging. The numerical advantages of lattice Boltzmann method (LBM) make it a powerful tool to simulate gas flow in such nano pores and estimate the absolute permeability. The new parallel implementation has been successfully performed on a powerful high performance computing cluster (HPCC) and validated with the analytical solution of a 3D tube flow model, which is taken as the elementary model for the pore networks. By simulating the nanoscale effects of rarefaction, slippage and roughness on gas flow in a nano tube model, we propose some more realistic parameters for simulating the gas flow in real mudrocks to study the flow mechanics, and to calculate the apparent directional permeability. The results show: 1) the simulated porosities (7.66% for S62H and 2.58% for S62V) are close to measured porosities (5.00% for S62H and 1.76% for S62V); 2) the estimated apparent permeability of S62H is 0.032 mD, which is close to the measured permeability of 0.02 mD; 3) the apparent directional permeability of S62V is not able to be estimated because the identified pores of subsamples are not connected in any direction with the image resolution of 65 nm/voxel; 4) the permeability anisotropy of S62H is clearly observed through the velocity field visualization and calculated permeability values; 5) the characteristics of pore geometry, flow velocity distribution and transport properties can be captured using DRP and the PLBM is an effective way to simulate complex gas flow in kerogen pores and estimate the apparent directional permeability.

The effect of X-ray micro computed tomography image resolution on flow properties of porous rocks.

The study of digital rock physics has seen significant advances due to the development of X-ray micro computed tomography scanning devices. One of the advantages of using such a device is that the pore structure of rock can be mapped down to the micrometre level in three dimensions. However, in providing such high-resolution images (low voxel size), the resulting file sizes are necessarily large (of the order of gigabytes). Lower image resolution (high voxel size) produces smaller file sizes (of the order of hundreds of megabytes), but risks losing significant details. This study describes the effect of the image resolution obtained by means of hardware-based and software-based approach. Four samples of porous rock were scanned using a SkyScan 1173 High Energy Micro-CT. We found that acquisition using increased pixel binning of the camera (hardware-based resizing) significantly affects the calculated physical properties of the samples. By contrast, voxel resizing by means of a software-based approach during the reconstruction process yielded less effect on the porosity and specific surface area of the samples. However, the decreasing resolution of the image obtained by both the hardware-based and the software-based approaches affects the permeability significantly. We conclude that simulating fluid flow through the pore space using the Lattice Boltzmann method to calculate the permeability has a significant dependency on the image resolution.

Using digital rocks and simulations of pore-scale multiphysics to characterize a sandstone reservoir

The modeling and prediction of transport and elastic properties for sandstones are critical steps in the exploration and appraisal of hydrocarbon reservoirs, particularly in deepwater settings where seismic data are abundant and well costs are high. Reliable multiphysics modeling of reservoir rocks requires robust models that respect the underlying geologic character and microstructure of the geomaterial and honor the measured properties. We have developed a case study that integrates traditional laboratory measurements with computational methods to quantify and relate physical properties of reservoir sandstones. We evaluate the complementary use of digital rock simulations as a practical technology that adds physical insight into the development and calibration of rock-property relationships. We also determine the challenges faced while applying digital rock physics to interpret laboratory data, and the steps taken to overcome those limitations. Combining physical and computational methods, we achieve an improved understanding of the link between geologic properties (sorting, microporosity) with transport (single-phase permeability, electrical conductivity) and elastic properties (moduli). Combining physical measurements with numerical computations has enhanced our understanding of multiphysics relationships in a heterogeneous sandstone reservoir.

Direct scale comparison of numerical linear elastic moduli with acoustic experiments for carbonate rock X-ray CT scanned at multi-resolutions

Giant carbonate reservoirs hold almost 50–60% of the world's conventional hydrocarbons and are thus of major economic significance. The recently emerging Digital Rock Physics (DRP) based mechanical property predictions have been successful for sandstones when validated against laboratory results. For carbonates however the success has been limited due to their complex nature and heterogeneity. Typically experiments are conducted with core sample diameters in the order of several cm. Due to computational limitations numerical models are often of several orders of magnitude smaller than laboratory samples. In this study we used a standard carbonate rock called Silurian Dolomite to perform sonic wave experiments on two sample sizes: 1.5in. and 0.5in. diameter cylindrical cores. The latter unique size allowed us to compare our DRP based finite element method (FEM) simulations at a more compatible scale and higher image resolution. Through a multi-scale X-ray Micro-CT imaging of the same sample we studied the effect of resolution on elastic moduli simulation. We demonstrated the importance of determining Representative Volume Element (RVE) at each imaging resolution. Through determination of RVE as well as sampling of 40–55% volume fraction using non-overlapping cubes, we showed how our protocol leads to very satisfactory same scale validation of numerical linear elastic moduli predictions.

Estimation of three‐phase relative permeability by simulating fluid dynamics directly on rock‐microstructure images

AbstractGiven the world's growing demand for energy, a combination of geological CO2 sequestration and enhanced oil recovery (EOR) technologies is currently regarded as a promising solution, as it would provide a means of reducing carbon emissions into the atmosphere while also leading to the economic benefit of simultaneously recovering oil. The optimization of injection strategies to maximize CO2 storage and increase the oil recovery factors requires complicated pore‐scale flow information within a reservoir system consisting of coexisting oil, water, and CO2 phases. In this study, an immiscible three‐phase lattice‐Boltzmann (LB) model was developed to investigate the complicated flow state with interaction between water, oil, and CO2 systems in porous media. The two main mechanisms of oil remobilization, namely, double‐drainage and film flow, can be captured by our model. The estimation of three‐phase relative permeability is proposed using the digital rock physics (DRP) simulations. The results indicate that the relative permeability of CO2 as calculated using our steady state method is not sensitive to the initial oil fraction if the oil distribution is originally uniform. Baker's (1988) empirical model was tested and found to be able to provide a good prediction of the three‐phase relative permeability data. Our numerical method provides a new tool for accurately predicting three‐phase relative permeability data directly based on micro‐CT rock images.

An FFT-based fast gradient method for elastic and inelastic unit cell homogenization problems

Building upon the previously established equivalence of the basic scheme of Moulinec–Suquet’s FFT-based computational homogenization method with a gradient descent method, this work concerns the impact of the fast gradient method of Nesterov in the context of computational homogenization. Nesterov’s method leads to a significant speed up compared to the basic scheme for linear problems with moderate contrast, and compares favorably to the (Newton-)conjugate gradient (CG) method for problems in digital rock physics and (small strain) elastoplasticity. We present an efficient implementation requiring twice the storage of the basic scheme, but only half of the storage of the CG method.

On the path to the digital rock physics of gas hydrate-bearing sediments – processing of in situ synchrotron-tomography data

Abstract. To date, very little is known about the distribution of natural gas hydrates in sedimentary matrices and its influence on the seismic properties of the host rock, in particular at low hydrate concentration. Digital rock physics offers a unique approach to this issue yet requires good quality, high-resolution 3-D representations for the accurate modeling of petrophysical and transport properties. Although such models are readily available via in situ synchrotron radiation X-ray tomography, the analysis of such data asks for complex workflows and high computational power to maintain valuable results. Here, we present a best-practice procedure complementing data from Chaouachi et al. (2015) with data post-processing, including image enhancement and segmentation as well as exemplary numerical simulations of an acoustic wave propagation in 3-D using the derived results. A combination of the tomography and 3-D modeling opens a path to a more reliable deduction of properties of gas hydrate-bearing sediments without a reliance on idealized and frequently imprecise models.

Digital carbonate rock physics

Abstract. Modern estimation of rock properties combines imaging with advanced numerical simulations, an approach known as digital rock physics (DRP). In this paper we suggest a specific segmentation procedure of X-ray micro-computed tomography data with two different resolutions in the µm range for two sets of carbonate rock samples. These carbonates were already characterized in detail in a previous laboratory study which we complement with nanoindentation experiments (for local elastic properties). In a first step a non-local mean filter is applied to the raw image data. We then apply different thresholds to identify pores and solid phases. Because of a non-neglectable amount of unresolved microporosity (micritic phase) we also define intermediate threshold values for distinct phases. Based on this segmentation we determine porosity-dependent values for effective P- and S-wave velocities as well as for the intrinsic permeability. For effective velocities we confirm an observed two-phase trend reported in another study using a different carbonate data set. As an upscaling approach we use this two-phase trend as an effective medium approach to estimate the porosity-dependent elastic properties of the micritic phase for the low-resolution images. The porosity measured in the laboratory is then used to predict the effective rock properties from the observed trends for a comparison with experimental data. The two-phase trend can be regarded as an upper bound for elastic properties; the use of the two-phase trend for low-resolution images led to a good estimate for a lower bound of effective elastic properties. Anisotropy is observed for some of the considered subvolumes, but seems to be insignificant for the analysed rocks at the DRP scale. Because of the complexity of carbonates we suggest using DRP as a complementary tool for rock characterization in addition to classical experimental methods.

Analysis and Visualization of 2D and 3D Grain and Pore Size ofFontainebleau Sandstone Using Digital Rock Physics

Fontainebleau sandstone is sandstone found in one of the cities in France. This sandstone has unique characteristics, which is a clean-fme sandstone, composed of 99% quartz, virtually devoid of clay, with the grain size of about 200 μm. Fontainebleau sandstone is widely used as a reference in the study of rock microstructure analysis and modelling. In this work analysis regarding the grain and pore size of Fontainebleau is presented. Calculation of 2D pore size and grain size distribution were done on the 299 slice of digital image of the Fontainebleau sandstone using Feret's diameters, equivalent diameters (d = 4A/P), and by means of local thickness/separation using plate model. For the 3D grain and pore size distribution, calculation of local thickness and local separation of the structure were used. Two dimensional analysis by means of Feret's diameter and equivalent diameter reveal that both grain and pore size distributions are in the form of reverse-J shaped (right skewed) while the local thickness/separation approach produces almost similar to symmetric Gaussian distribution. Three dimensional analysis produces fairly symmetric Gaussian distribution for both the grain and pore size. Further image processing were conducted and were succeed in producing three dimensional visual of the colour coded structure thickness (grain related) and structure separation (pore related).

Effects of changes in rock microstructures on permeability: 3‐D printing investigation

AbstractRocks are naturally heterogeneous; two rock samples with identical bulk properties can vary widely in microstructure. Understanding how the microstructure and bulk properties of rocks then evolve during experiments and computations simulating diagenesis is inherently a multiscale problem. The advent of modern 3‐D printing has provided an unprecedented opportunity to link those scales by combining the strengths of digital and experimental rock physics. In this study, we take a computerized tomography‐scanned model of a natural carbonate pore space then iteratively digitally manipulate, 3‐D print, and measure the flow properties in the laboratory. This approach allows us to access multiple scales digitally and experimentally and test hypotheses about how changes in rock microstructure due to compaction and dissolution affect bulk transport properties in a repeatable manner.

Conditional reconstruction: An alternative strategy in digital rock physics

Digital rock physics (DRP) is a newly developed method based on imaging and digitizing of 3D pore and mineral structure of actual rock and numerically computing rock physical properties, such as permeability, elastic moduli, and formation factor. Modern high-resolution microcomputed tomography scanners are used for imaging, but these devices are not widely available, and 3D imaging is also costly and it is a time-consuming procedure. However, recent improvements of 3D reconstruction algorithms such as crosscorrelation-based simulation and, on the other side, the concept of rock physical trends have provided some new avenues in DRP. We have developed a modified work flow using higher order statistical methods. First, a high-resolution 2D image is divided into smaller subimages. Then, different stochastic subsamples are generated based on the provided 2D subimages. Eventually, various rock physical parameters are calculated. Using several subsamples allows extracting rock physical trends and better capturing the heterogeneity and variability. We implemented our work flow on two DRP benchmark data (Berea sandstone and Grosmont carbonate) and a thin-section image from the Grosmont carbonate formation. Results of realization models, pore network modeling, and autocorrelation functions for the real and reconstructed subsamples reveal the validity of the reconstructed models. Furthermore, the agreement between static and dynamic methods indicates that subsamples are representative volume elements. Average values of the subsamples’ properties follow the reference trends of the rock sample. Permeability trends pass the actual results of the benchmark samples; however, elastic moduli trends find higher values. The latter can be due to image resolution and voxel size, which are generated by imaging tools and reconstruction algorithms. According to the obtained results, this strategy can be introduced as a valid and accurate method where an alternative method for standard DRP is needed.

Analysis of high‐resolution X‐ray computed tomography images of Bentheim sandstone under elevated confining pressures

ABSTRACTA sample of Bentheim sandstone was characterized using high‐resolution three‐dimensional X‐ray microscopy at two different confining pressures of 1 MPa and 20 MPa. The two recordings can be directly compared with each other because the same sample volume was imaged in either case. After image processing, a porosity reduction from 21.92% to 21.76% can be deduced from the segmented data. With voxel‐based numerical simulation techniques, we determined apparent hydraulic transport properties and effective elastic properties. These results were compared with laboratory measurements using reference samples. Laboratory and computed volumes, as well as hydraulic transport properties, agree fairly well. To achieve a reasonable agreement for the effective elastic properties, we define pressure‐dependent grain contact zones in addition to mineral phases in the digital rock images. From that, we derive a specific digital rock physics template resulting in a very good agreement between laboratory data and simulations. The digital rock physics template aims to contribute to a more standardized approach of X‐ray computed tomography data analysis as a tool to determine and predict elastic rock properties.

Digital core based transmitted ultrasonic wave simulation and velocity accuracy analysis

Transmitted ultrasonic wave simulation (TUWS) in a digital core is one of the important elements of digital rock physics and is used to study wave propagation in porous cores and calculate equivalent velocity. When simulating wave propagates in a 3D digital core, two additional layers are attached to its two surfaces vertical to the wave-direction and one planar wave source and two receiver-arrays are properly installed. After source excitation, the two receivers then record incident and transmitted waves of the digital rock. Wave propagating velocity, which is the velocity of the digital core, is computed by the picked peak-time difference between the two recorded waves. To evaluate the accuracy of TUWS, a digital core is fully saturated with gas, oil, and water to calculate the corresponding velocities. The velocities increase with decreasing wave frequencies in the simulation frequency band, and this is considered to be the result of scattering. When the pore fluids are varied from gas to oil and finally to water, the velocity-variation characteristics between the different frequencies are similar, thereby approximately following the variation law of velocities obtained from linear elastic statics simulation (LESS), although their absolute values are different. However, LESS has been widely used. The results of this paper show that the transmission ultrasonic simulation has high relative precision.

Nanoscale grain boundary channels in fracture cement enhance flow in mudrocks

AbstractHydrocarbon production from mudrock or shale reservoirs typically exceeds estimates based on mudrock laboratory permeability measurements, with the difference attributed to natural fractures. However, natural fractures in these reservoirs are frequently completely cemented and thus assumed not to contribute to flow. We quantify the permeability of nanoscale grain boundary channels with mean apertures of 50–130 nm in otherwise completely cemented natural fractures of the Eagle Ford Formation and estimate their contribution to production. Using scanning electron imaging of grain boundary channel network geometry and a digital rock physics workflow of image reconstruction and direct flow modeling, we estimate cement permeability to be 38–750 nd, higher than reported permeability of Eagle Ford host rock (~2 nd) based on laboratory measurements. Our results suggest that effective fracture‐parallel mudrock permeability can exceed laboratory values by upward of 1 order of magnitude in shale reservoirs of high macroscopic cemented fracture volume fraction.

On the predictivity of pore-scale simulations: Estimating uncertainties with multilevel Monte Carlo

A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another “equivalent” sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [1], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers, extrapolation and post-processing techniques. The proposed method can be efficiently used in many porous media applications for problems such as stochastic homogenization/upscaling, propagation of uncertainty from microscopic fluid and rock properties to macro-scale parameters, robust estimation of Representative Elementary Volume size for arbitrary physics.

Technology Focus: Formation Evaluation (August 2015)

Technology Focus Comprehensive formation evaluation is performed by integrating logs, cores, well tests, and other geoscience and engineering information. It plays a critical role in resources assessment and is equally important in well-placement development and reservoir surveillance. It is one of the technical focus areas that is fundamental across almost all upstream businesses, from initial exploration through final field abandonment. So how well are we doing in modern formation evaluation? In resources exploration, we have come a long way from the historical wireline (WL) triple combination of logging of bulk density, neutron porosity, and resistivity for reservoir lithology, porosity, and saturation, respectively. With continuing development in technologies such as acoustic, mud logging, nuclear magnetic resonance, imaging, and formation testing and sampling, we can identify fluid types and contacts; quantify viscosity, free fluid, and mobility; and characterize pore structure and rock mechanical properties. In addition, elemental mineralogy logs have significantly improved multimineral formation evaluation in complex reservoirs, especially unconventional shale formations. In field development, a paradigm shift has occurred in the last decade in terms of wells drilled (i.e., we are drilling more and more horizontal, multilateral wells for maximum/extreme reservoir contact). Consequently, logging-while-drilling technologies have advanced so much that they can provide almost WL-log quality and capability. To achieve the ultimate goal of maximizing reservoir performance, looking-around and -ahead technologies are also evolving quickly. In reservoir surveillance, game-changing technologies are emerging that enable us to illuminate the reservoir in four dimensions through measurements across wells, from wellbore to surface, and monitor smart-nanoparticle movement in situ. Development of these reservoir-scale technologies is actually in line with the grand challenges facing the exploration-and-production industry identified by SPE (i.e., developing higher-resolution subsurface imaging and increasing hydrocarbon recovery factor) because they are critical for improvements in identifying bypassed oil and assessing remaining oil. Core analysis has historically been considered as a reference for log interpretation. Major developments in core analysis in the last decade are digital rock physics and unconventional-resources evaluation. These developments continue to push the envelope of our understanding of rock and of rock/fluid interactions. In summary, significant progress has been made recently in formation evaluation, and we are in the process of a great journey to help resolve the grand challenges with fit-for-purpose and cost-effective solutions, as demonstrated in the selected papers and recommended additional reading. JPT

3D printing sandstone porosity models

The petroleum industry requires new technologies to improve the economics of exploration and production. Digital rock physics is a methodology that seeks to revolutionize reservoir characterization, an essential step in reservoir assessment, using computational methods. A combination of X-ray computed microtomography, digital pore network modeling, and 3D printing technology represents a novel workflow for transferring digital rock models into tangible samples that can be manufactured in a variety of materials and tested with standard laboratory equipment. Accurate replication of pore networks depends on the resolution of tomographic images, rock sample size, statistical algorithms for digital modeling, and the resolution of 3D printing. We performed this integrated approach on a sample of Idaho Gray Sandstone with an estimated porosity of 29% and permeability of 2200 mD. Tomographic images were collected at resolutions of 30 and [Formula: see text] per voxel. This allowed the creation of digital porosity models segmented into grains and pores. Surfaces separating pores from grains were extracted from the digital rock volume and 3D printed in plastic as upscaled tangible models. Two model types, normal (with pores as voids) and inverse (with pores as solid), allowed visualization of the geometry of the grain matrix and topology of pores, while allowing characterization of pore connectivity. The current resolution of commodity 3D printers with a plastic filament ([Formula: see text] for pore space and [Formula: see text] for grain matrix) is too low to precisely reproduce the Idaho Gray Sandstone at its original scale. However, the workflow described here also applies to advanced high-resolution 3D printers, which have been becoming more affordable with time. In summary, with its scale flexibility and fast manufacturing time, 3D printing has the potential to become a powerful tool for reservoir characterization.

Assessing the utility of FIB-SEM images for shale digital rock physics

Shales and other unconventional or low permeability (tight) reservoirs house vast quantities of hydrocarbons, often demonstrate considerable water uptake, and are potential repositories for fluid sequestration. The pore-scale topology and fluid transport mechanisms within these nanoporous sedimentary rocks remain to be fully understood. Image-informed pore-scale models are useful tools for studying porous media: a debated question in shale pore-scale petrophysics is whether there is a representative elementary volume (REV) for shale models? Furthermore, if an REV exists, how does it differ among petrophysical properties? We obtain three dimensional (3D) models of the topology of microscale shale volumes from image analysis of focused ion beam-scanning electron microscope (FIB-SEM) image stacks and investigate the utility of these models as a potential REV for shale. The scope of data used in this work includes multiple local groups of neighboring FIB-SEM images of different microscale sizes, corresponding core-scale (milli- and centimeters) laboratory data, and, for comparison, series of two-dimensional (2D) cross sections from broad ion beam SEM images (BIB-SEM), which capture a larger microscale field of view than the FIB-SEM images; this array of data is larger than the majority of investigations with FIB-SEM-derived microscale models of shale. Properties such as porosity, organic matter content, and pore connectivity are extracted from each model. Assessments of permeability with single phase, pressure-driven flow simulations are performed in the connected pore space of the models using the lattice-Boltzmann method. Calculated petrophysical properties are compared to those of neighboring FIB-SEM images and to core-scale measurements of the sample associated with the FIB-SEM sites. Results indicate that FIB-SEM images below ∼5000 µm3 volume (the largest volume analyzed) are not a suitable REV for shale permeability and pore-scale networks; i.e. field of view is compromised at the expense of detailed, but often unconnected, nanopore morphology. Further, we find that it is necessary to acquire several local FIB-SEM or BIB-SEM images and correlate their extracted geometric properties to improve the likelihood of achieving representative values of porosity and organic matter volume. Our work indicates that FIB-SEM images of microscale volumes of shale are a qualitative tool for petrophysical and transport analysis. Finally, we offer alternatives for quantitative pore-scale assessments of shale.

Numerical estimation of carbonate rock properties using multiscale images

ABSTRACTCharacterizing the pore space of rock samples using three‐dimensional (3D) X‐ray computed tomography images is a crucial step in digital rock physics. Indeed, the quality of the pore network extracted has a high impact on the prediction of rock properties such as porosity, permeability and elastic moduli. In carbonate rocks, it is usually very difficult to find a single image resolution which fully captures the sample pore network because of the heterogeneities existing at different scales. Hence, to overcome this limitation a multiscale analysis of the pore space may be needed. In this paper, we present a method to estimate porosity and elastic properties of clean carbonate (without clay content) samples from 3D X‐ray microtomography images at multiple resolutions. We perform a three‐phase segmentation to separate grains, pores and unresolved porous phase using 19 μm resolution images of each core plug. Then, we use images with higher resolution (between 0.3 and 2 μm) of microplugs extracted from the core plug samples. These subsets of images are assumed to be representative of the unresolved phase. We estimate the porosity and elastic properties of each sample by extrapolating the microplug properties to the whole unresolved phase. In addition, we compute the absolute permeability using the lattice Boltzmann method on the microplug images due to the low resolution of the core plug images.In order to validate the results of the numerical simulations, we compare our results with available laboratory measurements at the core plug scale. Porosity average simulations for the eight samples agree within 13%. Permeability numerical predictions provide realistic values in the range of experimental data but with a higher relative error. Finally, elastic moduli show the highest disagreements, with simulation error values exceeding 150% for three samples.

Pore-scale analysis of electrical properties in thinly bedded rock using digital rock physics

We investigated the electrical properties of laminated rock consist of macro-porous layers and micro-porous layers based on digital rock technology. Due to the bedding effect and anisotropy, traditional Archie equations cannot well describe the electrical behavior of laminated rock. The RI-Sw curve of laminated rock shows a nonlinear relationship. The RI-Sw curve can be divided into two linear segments with different saturation exponent. Laminated sand-shale sequences and laminated sands of different porosity or grain size will yield macroscopic electrical anisotropy. Numerical simulation and theoretical analysis lead to the conclusion that electrical anisotropy coefficient of laminated rock is a strong function of water saturation. The function curve can be divided into three segments by the turning point. Therefore, the electrical behavior of laminated rock should be considered in oil exploration and development.