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Multiscale and Multiphysics Processes in Unconventional Formations 2020

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".

Deadline for manuscript submissions: closed (10 January 2021) | Viewed by 32306

Special Issue Editors


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Guest Editor
Department of Chemical and Biomedical Engineering, College of Engineering and Physical Sciences, University of Wyoming, Laramie, WY 82071, USA
Interests: enhanced oil recovery (EOR); interfacial science and complex fluids
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Energy Resources Engineering, Stanford University, Stanford, CA 94305-2220, USA
Interests: visualization of transport processes in porous media; characterization of unconventional rocks; enhanced/improved recovery
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Special Issue Information

Dear Colleagues,

The emergence of production techniques for unconventional reservoirs has had a transformative effect on the oil and gas industry. Drilling in shale gas and oil reservoirs has given rise to the concept of well manufacturing, making accessibility to these resources a commercial reality. While shale production has profoundly changed energy supply, only about 5% of the oil and about 25% of the gas in oil/gas shales is recovered. Initial productivity decreases markedly after a few months. Research and development activities are required to increase long-term productivity by unveiling storage and production mechanisms that are poorly understood at present. Given the inherent multiscale nature of the rock fabric, spanning 10 orders of magnitude in spatial scales, advances in multiscale characterization and modeling techniques are needed. This Special Issue welcomes research studies on unconventional multiscale reservoir characterization, geochemical, geomechanical and geostatistical studies, model systems, phase behavior in tight rock, and modeling methods of the variety of physicochemical processes in unconventional formations. Original contributions and truly critical reviews integrating scales and disciplines are welcome.

Prof. Dr. Vladimir Alvarado
Prof. Dr. Anthony Kovscek
Guest Editors

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Keywords

  • Experimental characterization techniques
  • Transport modeling methods
  • Fundamental studies of coupled transport, reaction, and/or mechanics
  • Geochemical characterization
  • Geomechanical characterization
  • Phase behavior in unconventional rock
  • Fluid–rock interactions

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Published Papers (9 papers)

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Research

29 pages, 11129 KiB  
Article
Effects of Supercritical CO2 on Matrix Permeability of Unconventional Formations
by Arash Kamali-Asl, Mark D Zoback and Arjun H. Kohli
Energies 2021, 14(4), 1101; https://doi.org/10.3390/en14041101 - 19 Feb 2021
Cited by 9 | Viewed by 2792
Abstract
We studied the effects of supercritical carbon dioxide (scCO2) on the matrix permeability of reservoir rocks from the Eagle Ford, Utica, and Wolfcamp formations. We measured permeability using argon before exposure of the samples to scCO2 over time periods ranging [...] Read more.
We studied the effects of supercritical carbon dioxide (scCO2) on the matrix permeability of reservoir rocks from the Eagle Ford, Utica, and Wolfcamp formations. We measured permeability using argon before exposure of the samples to scCO2 over time periods ranging from days to weeks. We measured permeability (and the change of permeability with confining pressure) when both argon and scCO2 were the pore fluids. In all three formations, we generally observe a negative correlation between initial permeability and carbonate content—the higher the carbonate content, the lower the initial permeability. In clay- and organic-rich samples, swelling of the matrix resulting from adsorption decreased the permeability by about 50% when the pore fluid was scCO2 although this permeability change is largely reversible. In carbonate-rich samples, dissolution of carbonate minerals by carbonic acid irreversibly increased matrix permeability, in some cases by more than one order of magnitude. This dissolution also increases the pressure dependence of permeability apparently due to enhanced mechanical compaction. Despite these trends, we observed no general correlation between mineralogy and the magnitude of the change in permeability with argon before and after exposure to scCO2. Flow of scCO2 through μm-scale cracks appears to play an important role in determining matrix permeability and the pressure dependence of permeability. Extended permeability measurements show that while adsorption is nearly instantaneous and reversible, dissolution is time-dependent, probably owing to reaction kinetics. Our results indicate that the composition and microstructure of matrix flow pathways control both the initial permeability and how permeability changes after interaction with scCO2. Electron microscopy images with Back-Scattered Electron (BSE) and Energy Dispersive Spectroscopy (EDS) revealed dissolution and etching of calcite minerals and precipitation of calcium sulfide resulting from exposure to scCO2. Full article
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25 pages, 6931 KiB  
Article
A New Modeling Framework for Multi-Scale Simulation of Hydraulic Fracturing and Production from Unconventional Reservoirs
by J. T. Birkholzer, J. Morris, J. R. Bargar, F. Brondolo, A. Cihan, D. Crandall, H. Deng, W. Fan, W. Fu, P. Fu, A. Hakala, Y. Hao, J. Huang, A. D. Jew, T. Kneafsey, Z. Li, C. Lopano, J. Moore, G. Moridis, S. Nakagawa, V. Noël, M. Reagan, C. S. Sherman, R. Settgast, C. Steefel, M. Voltolini, W. Xiong and J. Ciezobkaadd Show full author list remove Hide full author list
Energies 2021, 14(3), 641; https://doi.org/10.3390/en14030641 - 27 Jan 2021
Cited by 17 | Viewed by 5354
Abstract
This paper describes a new modeling framework for microscopic to reservoir-scale simulations of hydraulic fracturing and production. The approach builds upon a fusion of two existing high-performance simulators for reservoir-scale behavior: the GEOS code for hydromechanical evolution during stimulation and the TOUGH+ code [...] Read more.
This paper describes a new modeling framework for microscopic to reservoir-scale simulations of hydraulic fracturing and production. The approach builds upon a fusion of two existing high-performance simulators for reservoir-scale behavior: the GEOS code for hydromechanical evolution during stimulation and the TOUGH+ code for multi-phase flow during production. The reservoir-scale simulations are informed by experimental and modeling studies at the laboratory scale to incorporate important micro-scale mechanical processes and chemical reactions occurring within the fractures, the shale matrix, and at the fracture-fluid interfaces. These processes include, among others, changes in stimulated fracture permeability as a result of proppant behavior rearrangement or embedment, or mineral scale precipitation within pores and microfractures, at µm to cm scales. In our new modeling framework, such micro-scale testing and modeling provides upscaled hydromechanical parameters for the reservoir scale models. We are currently testing the new modeling framework using field data and core samples from the Hydraulic Fracturing Field Test (HFTS), a recent field-based joint research experiment with intense monitoring of hydraulic fracturing and shale production in the Wolfcamp Formation in the Permian Basin (USA). Below, we present our approach coupling the reservoir simulators GEOS and TOUGH+ informed by upscaled parameters from micro-scale experiments and modeling. We provide a brief overview of the HFTS and the available field data, and then discuss the ongoing application of our new workflow to the HFTS data set. Full article
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19 pages, 6515 KiB  
Article
Interpretation of Gas/Water Relative Permeability of Coal Using the Hybrid Bayesian-Assisted History Matching: New Insights
by Jiyuan Zhang, Bin Zhang, Shiqian Xu, Qihong Feng, Xianmin Zhang and Derek Elsworth
Energies 2021, 14(3), 626; https://doi.org/10.3390/en14030626 - 26 Jan 2021
Cited by 9 | Viewed by 2409
Abstract
The relative permeability of coal to gas and water exerts a profound influence on fluid transport in coal seams in both primary and enhanced coalbed methane (ECBM) recovery processes where multiphase flow occurs. Unsteady-state core-flooding tests interpreted by the Johnson–Bossler–Naumann (JBN) method are [...] Read more.
The relative permeability of coal to gas and water exerts a profound influence on fluid transport in coal seams in both primary and enhanced coalbed methane (ECBM) recovery processes where multiphase flow occurs. Unsteady-state core-flooding tests interpreted by the Johnson–Bossler–Naumann (JBN) method are commonly used to obtain the relative permeability of coal. However, the JBN method fails to capture multiple gas–water–coal interaction mechanisms, which inevitably results in inaccurate estimations of relative permeability. This paper proposes an improved assisted history matching framework using the Bayesian adaptive direct search (BADS) algorithm to interpret the relative permeability of coal from unsteady-state flooding test data. The validation results show that the BADS algorithm is significantly faster than previous algorithms in terms of convergence speed. The proposed method can accurately reproduce the true relative permeability curves without a presumption of the endpoint saturations given a small end-effect number of <0.56. As a comparison, the routine JBN method produces abnormal interpretation results (with the estimated connate water saturation ≈33% higher than and the endpoint water/gas relative permeability only ≈0.02 of the true value) under comparable conditions. The proposed framework is a promising computationally effective alternative to the JBN method to accurately derive relative permeability relations for gas–water–coal systems with multiple fluid–rock interaction mechanisms. Full article
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23 pages, 2814 KiB  
Article
Multi-Scale Microfluidics for Transport in Shale Fabric
by Bowen Ling, Hasan J. Khan, Jennifer L. Druhan and Ilenia Battiato
Energies 2021, 14(1), 21; https://doi.org/10.3390/en14010021 - 23 Dec 2020
Cited by 10 | Viewed by 2736
Abstract
We develop a microfluidic experimental platform to study solute transport in multi-scale fracture networks with a disparity of spatial scales ranging between two and five orders of magnitude. Using the experimental scaling relationship observed in Marcellus shales between fracture aperture and frequency, the [...] Read more.
We develop a microfluidic experimental platform to study solute transport in multi-scale fracture networks with a disparity of spatial scales ranging between two and five orders of magnitude. Using the experimental scaling relationship observed in Marcellus shales between fracture aperture and frequency, the microfluidic design of the fracture network spans all length scales from the micron (1 μ) to the dm (10 dm). This intentional `tyranny of scales’ in the design, a determining feature of shale fabric, introduces unique complexities during microchip fabrication, microfluidic flow-through experiments, imaging, data acquisition and interpretation. Here, we establish best practices to achieve a reliable experimental protocol, critical for reproducible studies involving multi-scale physical micromodels spanning from the Darcy- to the pore-scale (dm to μm). With this protocol, two fracture networks are created: a macrofracture network with fracture apertures between 5 and 500 μm and a microfracture network with fracture apertures between 1 and 500 μm. The latter includes the addition of 1 μm ‘microfractures’, at a bearing of 55°, to the backbone of the former. Comparative analysis of the breakthrough curves measured at corresponding locations along primary, secondary and tertiary fractures in both models allows one to assess the scale and the conditions at which microfractures may impact passive transport. Full article
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14 pages, 3767 KiB  
Article
Transport Simulations on Scanning Transmission Electron Microscope Images of Nanoporous Shale
by Laura Frouté, Yuhang Wang, Jesse McKinzie, Saman A. Aryana and Anthony R. Kovscek
Energies 2020, 13(24), 6665; https://doi.org/10.3390/en13246665 - 17 Dec 2020
Cited by 14 | Viewed by 4533
Abstract
Digital rock physics is an often-mentioned approach to better understand and model transport processes occurring in tight nanoporous media including the organic and inorganic matrix of shale. Workflows integrating nanometer-scale image data and pore-scale simulations are relatively undeveloped, however. In this paper, a [...] Read more.
Digital rock physics is an often-mentioned approach to better understand and model transport processes occurring in tight nanoporous media including the organic and inorganic matrix of shale. Workflows integrating nanometer-scale image data and pore-scale simulations are relatively undeveloped, however. In this paper, a workflow is demonstrated progressing from sample acquisition and preparation, to image acquisition by Scanning Transmission Electron Microscopy (STEM) tomography, to volumetric reconstruction to pore-space discretization to numerical simulation of pore-scale transport. Key aspects of the workflow include (i) STEM tomography in high angle annular dark field (HAADF) mode to image three-dimensional pore networks in µm-sized samples with nanometer resolution and (ii) lattice Boltzmann method (LBM) simulations to describe gas flow in slip, transitional, and Knudsen diffusion regimes. It is shown that STEM tomography with nanoscale resolution yields excellent representation of the size and connectivity of organic nanopore networks. In turn, pore-scale simulation on such networks contributes to understanding of transport and storage properties of nanoporous shale. Interestingly, flow occurs primarily along pore networks with pore dimensions on the order of tens of nanometers. Smaller pores do not form percolating pathways in the sample volume imaged. Apparent gas permeability in the range of 10−19 to 10−16 m2 is computed. Full article
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19 pages, 3419 KiB  
Article
RockFlow: Fast Generation of Synthetic Source Rock Images Using Generative Flow Models
by Timothy I. Anderson, Kelly M. Guan, Bolivia Vega, Saman A. Aryana and Anthony R. Kovscek
Energies 2020, 13(24), 6571; https://doi.org/10.3390/en13246571 - 13 Dec 2020
Cited by 14 | Viewed by 4307
Abstract
Image-based evaluation methods are a valuable tool for source rock characterization. The time and resources needed to obtain images has spurred development of machine-learning generative models to create synthetic images of pore structure and rock fabric from limited image data. While generative models [...] Read more.
Image-based evaluation methods are a valuable tool for source rock characterization. The time and resources needed to obtain images has spurred development of machine-learning generative models to create synthetic images of pore structure and rock fabric from limited image data. While generative models have shown success, existing methods for generating 3D volumes from 2D training images are restricted to binary images and grayscale volume generation requires 3D training data. Shale characterization relies on 2D imaging techniques such as scanning electron microscopy (SEM), and grayscale values carry important information about porosity, kerogen content, and mineral composition of the shale. Here, we introduce RockFlow, a method based on generative flow models that creates grayscale volumes from 2D training data. We apply RockFlow to baseline binary micro-CT image volumes and compare performance to a previously proposed model. We also show the extension of our model to 2D grayscale data by generating grayscale image volumes from 2D SEM and dual modality nanoscale shale images. The results show that our method underestimates the porosity and surface area on the binary baseline datasets but is able to generate realistic grayscale image volumes for shales. With improved binary data preprocessing, we believe that our model is capable of generating synthetic porous media volumes for a very broad class of rocks from shale to carbonates to sandstone. Full article
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15 pages, 1890 KiB  
Article
Three-Dimensional Imaging and Quantification of Gas Storativity in Nanoporous Media via X-rays Computed Tomography
by Youssef Elkady, Ye Lyu, Kristian Jessen and Anthony R. Kovscek
Energies 2020, 13(23), 6199; https://doi.org/10.3390/en13236199 - 25 Nov 2020
Cited by 8 | Viewed by 2799
Abstract
This study provides the engineering science underpinnings for improved characterization and quantification of the interplay of gases with kerogen and minerals in shale. Natural nanoporous media such as shale (i.e., mudstone) often present with low permeability and dual porosity, making them difficult to [...] Read more.
This study provides the engineering science underpinnings for improved characterization and quantification of the interplay of gases with kerogen and minerals in shale. Natural nanoporous media such as shale (i.e., mudstone) often present with low permeability and dual porosity, making them difficult to characterize given the complex structural and chemical features across multiple scales. These structures give nanoporous solids a large surface area for gas to sorb. In oil and gas applications, full understanding of these media and their sorption characteristics are critical for evaluating gas reserves, flow, and storage for enhanced recovery and CO2 sequestration potential. Other applications include CO2 capture from industrial plants, hydrogen storage on sorbent surfaces, and heterogeneous catalysis in ammonia synthesis. Therefore, high-resolution experimental procedures are demanded to better understand the gas–solid behavior. In this study, CT imaging was applied on the sub-millimeter scale to shale samples (Eagle Ford and Wolfcamp) to improve quantitative agreement between CT-derived and pulse decay (mass balance) derived results. Improved CT imaging formulations are presented that better match mass balance results, highlighting the significance of gas sorption in complex nanoporous media. The proposed CT routine implemented on the Eagle Ford sample demonstrated a 17% error reduction (22% to 5%) when compared to the conventional CT procedure. These observations are consistent in the Wolfcamp sample, emphasizing the reliability of this technique for broader implementation of digital adsorption studies in nanoporous geomaterials. Full article
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22 pages, 29375 KiB  
Article
Relationships between Dynamic Elastic Moduli in Shale Reservoirs
by Sheyore John Omovie and John P. Castagna
Energies 2020, 13(22), 6001; https://doi.org/10.3390/en13226001 - 17 Nov 2020
Cited by 10 | Viewed by 2803
Abstract
Sonic log compressional and shear-wave velocities combined with logged bulk density can be used to calculate dynamic elastic moduli in organic shale reservoirs. We use linear multivariate regression to investigate modulus prediction when shear-wave velocities are not available in seven unconventional shale reservoirs. [...] Read more.
Sonic log compressional and shear-wave velocities combined with logged bulk density can be used to calculate dynamic elastic moduli in organic shale reservoirs. We use linear multivariate regression to investigate modulus prediction when shear-wave velocities are not available in seven unconventional shale reservoirs. Using only P-wave modulus derived from logged compressional-wave velocity and density as a predictor of dynamic shear modulus in a single bivariate regression equation for all seven shale reservoirs results in prediction standard error of less than 1 GPa. By incorporating compositional variables in addition to P-wave modulus in the regression, the prediction standard error is reduced to less than 0.8 GPa with a single equation for all formations. Relationships between formation bulk and shear moduli are less well defined. Regressing against formation composition only, we find the two most important variables in predicting average formation moduli to be fractional volume of organic matter and volume of clay in that order. While average formation bulk modulus is found to be linearly related to volume fraction of total organic carbon, shear modulus is better predicted using the square of the volume fraction of total organic carbon. Both Young’s modulus and Poisson’s ratio decrease with increasing TOC while increasing clay volume decreases Young’s modulus and increases Poisson’s ratio. Full article
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17 pages, 22848 KiB  
Article
Modeling Adsorption in Silica Pores via Minkowski Functionals and Molecular Electrostatic Moments
by Filip Simeski, Arnout M. P. Boelens and Matthias Ihme
Energies 2020, 13(22), 5976; https://doi.org/10.3390/en13225976 - 16 Nov 2020
Cited by 2 | Viewed by 3626
Abstract
Capillary condensation phenomena are important in various technological and environmental processes. Using molecular simulations, we study the confined phase behavior of fluids relevant to carbon sequestration and shale gas production. As a first step toward translating information from the molecular to the pore [...] Read more.
Capillary condensation phenomena are important in various technological and environmental processes. Using molecular simulations, we study the confined phase behavior of fluids relevant to carbon sequestration and shale gas production. As a first step toward translating information from the molecular to the pore scale, we express the thermodynamic potential and excess adsorption of methane, nitrogen, carbon dioxide, and water in terms of the pore’s geometric properties via Minkowski functionals. This mathematical reconstruction agrees very well with molecular simulations data. Our results show that the fluid molecular electrostatic moments are positively correlated with the number of adsorption layers in the pore. Moreover, stronger electrostatic moments lead to adsorption at lower pressures. These findings can be applied to improve pore-scale thermodynamic and transport models. Full article
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