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At least 181 records · Page 10

Fracture Sustainability in Enhanced Geothermal Systems: Experimental and Modeling Constraints

Enhanced geothermal systems (EGS) offer the potential for a much larger energy source than conventional hydrothermal systems. Hot, low-permeability rocks are prevalent at depth around the world, but the challenge of extracting thermal energy depends on the ability to create and sustain open fracture networks. Laboratory experiments were conducted using a suite of selected rock cores (granite, metasediment, rhyolite ash-flow tuff, and silicified rhyolitic tuff) at relevant pressures (uniaxial loading up to 20.7 MPa and fluid pressures up to 10.3 MPa) and temperatures (150–250 °C) to evaluate the potential impacts of circulating fluids through fractured rock by monitoring changes in fracture aperture, mineralogy, permeability, and fluid chemistry. Because a fluid in disequilibrium with the rocks (deionized water) was used for these experiments, there was net dissolution of the rock sample: this increased with increasing temperature and experiment duration. Thermal-hydrological-mechanical-chemical (THMC) modeling simulations were performed for the rhyolite ash-flow tuff experiment to test the ability to predict the observed changes. These simulations were performed in two steps: a thermal-hydrological-mechanical (THM) simulation to evaluate the effects of compression of the fracture, and a thermal-hydrological-chemical (THC) simulation to evaluate the effects of hydrothermal reactions on the fracture mineralogy, porosity, and permeability. Furthermore, these experiments and simulations point out how differences in rock mineralogy, fluid chemistry, and geomechanical properties influence how long asperity-propped fracture apertures may be sustained. Such core-scale experiments and simulations can be used to predict EGS reservoir behavior on the field scale.

15 GEOTHERMAL ENERGY↗

Osmotic Pressure Gradient Effects on Water Diffusion in Porous Rock: Can They Pervert Permeability Tests?

Abstract Generation of a large network of hydraulic cracks is of key importance not only for the success of fracking of shale but also for the recent scheme of sequestration of CO2 in deep formations of basalt and peridotite, which are mafic and ultramafic rocks that combine chemically with CO2. In numerical simulation of the creation of a fracture network in porous rock, an important goal is to enhance the rock permeability. The objective of this article is to calculate the effect of osmotic pressure gradients caused by gradients of concentration of the ions of Ca, Mg, Na, etc. on the effective permeability of the rock. The basic differential equations are formulated, and their explicit solutions for appropriate initial and boundary conditions are obtained under certain plausible simplifications. The main result is explicit approximate formulas for the critical time before which no water permeation through a test specimen can be observed. Depending on various parameters, this time can be unacceptably long, which is manifested as a zero water outflow. The solution may also explain the unreasonably small permeability values reported for some shales.

Mechanics↗

A machine-learning inverse model framework for rapid forecasting and history matching in unconventional reservoirs

Model-based optimization for real-time forecasting in unconventional reser-voirs requires novel methods and work?ows since the strategies and work?ows used in conventional reservoirs are either inapplicable, or prohibitively expen-sive and time-consuming. Insu?cient site data and computational expense of high-?delity simulations mean that work?ows with high-?delity simulations are not ideal for usage in comprehensive uncertainty quanti?cation stud-ies that require 1000s of forward model runs. We present an alternative, novel work?ow for unconventional reservoirs, based on the interplay between reduced-order models and machine-learning. Our physics-informed machine-learning (PIML) work?ow addresses the challenges to real-time reservoir management in uncoventionals, namely lack of data (the time-frame for which the wells have been producing), and computational expense of high-?delity modeling. We use the machine-learning paradigm of transfer-learning to bind together fast but less accurate reduced-order models with slow, but accurate high-?delity models and circumvent the di?culties inherent in the current state-of-the-art for unconventionals. Such a PIML work?ow, grounded in physics, is a viable candidate for real-time history matching and production forecasting in a fractured shale gas reservoir. The signi?cance of our approach is that while it is developed for a particu-lar well and site in the Marcelus Shale gas reservoir of the Appalachian basin (MSEEL), it is not wedded to it. We expect the same work?ow can be ap-plied to other shale formations (e.g., Woodford, Barnett, Utica, EagleFord) should site-data become available, using the same set of machine-learning techniques from transfer learning. Some ?ne-tuning (or minimal retraining of the neural networks) will be required to transfer knowledge across shale gas sites/formations but it is a clearly superior alternative to developing a new machine-learning model altogether when considering a di?erent site.

Srinivasan, Shriram↗

Changes in environmental and engineered conditions alter the plasma membrane lipidome of fractured shale bacteria

ABSTRACT Microorganisms that persist in fractured shale reservoirs cause several problems including secreting foul gases and forming biofilms. Current biocontrol measures often fail due to limited knowledge of their in situ activities. The plasma membrane protects the cell, mediates many of its critical functions, and responds to intracellular cues and ecological perturbations through physicochemical modifications. As such, it provides valuable insight into the physiological adaptation of microorganisms in disturbed environmental systems. Here, we (i) demonstrate how changes in salinity and hydraulic retention time (HRT) influence the plasma membrane intact polar lipid (IPL) chemistry of model bacterium, Halanaerobium congolense WG10, and mixed microbial consortia enriched from shale-produced fluids and (ii) elucidate adjustments in membrane IPL chemistry during biofilm growth relative to planktonic cells. We incubated H. congolense WG10 in chemostats under three salinities (7%, 13%, and 20% NaCl), operated under three HRTs (19.2, 24, and 48 h), and in drip flow biofilm reactors under the same salinity gradients. Also, mixed microbial consortia in produced fluids were enriched in triplicate chemostat vessels under three HRTs (19.2, 24, and 72 h) and biofilm reactors. Lipids were analyzed by ultra high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Our results show that phosphatidylglycerols, cardiolipins, and phosphatidylethanolamines were predominantly enriched in planktonic H. congolense WG10 cells grown at hypersalinity (20%) compared to optimum (13%). In addition, several zwitterionic phosphatidylcholines and phosphatidylethanolamines were higher in abundance during biofilm growth. These observations suggest that microbial adaptation and biofilm formation in fractured shale are enabled by strategic plasma membrane IPL chemistry adjustments. IMPORTANCE Microorganisms inadvertently introduced into the shale reservoir during fracturing face multiple stressors including brine-level salinities and starvation. However, some anaerobic halotolerant bacteria adapt and persist for long periods of time. They produce hydrogen sulfide, which sours the reservoir and corrodes engineering infrastructure. In addition, they form biofilms on rock matrices, which decrease shale permeability and clog fracture networks. These reduce well productivity and increase extraction costs. Under stress, microbes remodel their plasma membrane to optimize its roles in protection and mediating cellular processes such as signaling, transport, and energy metabolism. Hence, by observing changes in the membrane lipidome of model shale bacteria, Halanaerobium congolense WG10, and mixed consortia enriched from produced fluids under varying subsurface conditions and growth modes, we provide insight that advances our knowledge of the fractured shale biosystem. We also offer data-driven recommendations for improving biocontrol efficacy and the efficiency of energy recovery from unconventional formations.

03 NATURAL GAS↗

Field Experiments and Model Validation: The EGS Collab Project

Implementing enhanced geothermal systems (EGS) will require improvements in understanding stimulation of crystalline rock to create appropriate flow pathways, and the ability to effectively simulate both the stimulation and the flow and transport processes in the resulting fracture network. The US Department of Energy (DOE) is addressing these and other challenges at multiple scales. The EGS Collab project, addressed here, is performing tests and modeling at the 10 m scale. The FORGE project is performing tests at the full reservoir scale. The EGS Collab team created an underground testbed at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, at a depth of approximately 1.5 km to examine hydraulic fracturing (Experiment 1). We are currently building a second testbed at SURF at a depth of about 1.25 km aimed at investigating shear stimulation (Experiment 2). In Experiment 1, we drilled eight boreholes in a well-characterized phyllite and installed geophysical sensors in six of them to create a well-instrumented testbed to allow careful monitoring of stimulation events and flow tests. Numerical simulation was used to answer key experimental design questions, to forecast fracture propagation trajectories and extents, and to analyze and evaluate results both in near-real-time and in detailed process studies. Stimulations performed in this testbed allowed quantification of processes occurring during stimulation and the examination of dynamic flow occurrences. Long-term ambient temperature and chilled water flow tests were performed in addition to many tracer tests to examine system behavior. Our second testbed, targeted at shear stimulation, is currently being built at the SURF Facility at a depth of about 1.25 km in amphibolite under a different set of stress and fracture conditions than Experiment 1.

artificial intelligence↗

Sensitivity and history match analysis of a carbon dioxide “huff-and-puff” injection test in a horizontal shale gas well in Tennessee

Due to improvements in well development, shale gas production has gained importance recently, especially in the United States. To improve gas production and develop a better understanding of shale reservoirs, researchers are conducting field tests to monitor CO 2 storage and enhanced gas recovery. Reservoir simulations can then utilize these field results for sensitivity studies, uncertainty analysis, history matching, gas production forecasts, and CO 2 storage capacity estimations. One such field test was performed for the Chattanooga Shale formation in Morgan County, Tennessee. Approximately 463 tonnes (510 tons) of CO 2 was successfully injected into a hydraulically fractured horizontal well over a thirteen-day period in March 2014. The injection test was achieved in four steps: pre-injection, injection, soaking, and flowback. In this paper, those steps were modeled with a reservoir simulator to match the historic production and injection rates with gas component compositions and forecast the production for five years. The reservoir fluid was modeled as a multi-component gas, including CH 4 , C 2 H 6 , C 3 H 8 , N 2 , and CO 2 . Langmuir constants, reservoir pressure, and fracture network volume were adjusted to match simulation results with observed production rates and gas composition. Results showed that, under the same reservoir conditions, each gas component behaves differently by way of compositional changes in production. CH4 behaves like N2, while CO 2 behaves like heavier hydrocarbons such as C 2 H 6 and C 3 H 8 . CO 2 plume results showed that, after injection, the produced CO 2 is mostly derived from fractured limestone (i.e., Fort Payne Formation) because the injected CO 2 is not adsorbed in limestone but rather by shale formations.

03 NATURAL GAS↗

Geological activity shapes the microbiome in deep-subsurface aquifers by advection

Subsurface environments host diverse microorganisms in fluid-filled fractures; however, little is known about how geological and hydrological processes shape the subterranean biosphere. Here, we sampled three flowing boreholes weekly for 10 mo in a 1478-m-deep fractured rock aquifer to study the role of fracture activity (defined as seismically or aseismically induced fracture aperture change) and advection on fluid-associated microbial community composition. We found that despite a largely stable deep-subsurface fluid microbiome, drastic community-level shifts occurred after events signifying physical changes in the permeable fracture network. The community-level shifts include the emergence of microbial families from undetected to over 50% relative abundance, as well as the replacement of the community in one borehole by the earlier community from a different borehole. Null-model analysis indicates that the observed spatial and temporal community turnover was primarily driven by stochastic processes (as opposed to deterministic processes). We, therefore, conclude that the observed community-level shifts resulted from the physical transport of distinct microbial communities from other fracture(s) that outpaced environmental selection. Given that geological activity is a major cause of fracture activity and that geological activity is ubiquitous across space and time on Earth, our findings suggest that advection induced by geological activity is a general mechanism shaping the microbial biogeography and diversity in deep-subsurface habitats across the globe.

59 BASIC BIOLOGICAL SCIENCES↗

Wellbore Leakage Mitigation Using Advanced Mineral Precipitation Strategies (Final Scientific/Technical Report)

This research project, entitled Wellbore Leakage Mitigation using Advanced Mineral Precipitation Strategies, was directed toward advancing mineral precipitation technologies to seal wellbore leaks and other potential carbon dioxide (CO 2 ) leakage pathways, including compromised wellbore cement and fracture networks of varying geometries throughout the wellbore and surrounding formation. The advanced mineral sealing techniques were evaluated in the laboratory and the field to expand the range of temperature, pressure, and chemical conditions where mineral precipitation could be used. Rates of enzymatically or thermally induced calcium carbonate precipitation (EICP, TICP) were determined as well as rates of enzyme inactivation at elevated temperatures (>60 °C). Immobilization was shown to enhance the thermal stability of urease enzyme and provide protection from inhibition in low pH conditions. Mineral seals promoted by EICP and TICP were used to seal fractured composite (cement/sandstone) and shale cores in high pressure reactors operated at temperatures greater than 55 °C and 130 °C, respectively. A computational model was updated to model processes of EICP and TICP. The work resulted in a successful field test, which showed that EICP in the presence of low pH fluids (CO 2 -impacted brine) could promote permeability reduction and seal a channel in the near-wellbore environment.

54 ENVIRONMENTAL SCIENCES↗

Prediction and Analysis of Utah FORGE Injection Activities using a Coupled Thermo-hydro-mechanical and Earthquake (THM+E) Modeling Workflow

A coupled thermo-hydro-mechanical (THM) numerical workflow that is capable of modeling seismic slip is critical for the successful development of enhanced geothermal systems (EGS). By integrating key physical processes, this workflow enables accurate simulation of temperature and pressure diffusions, stress changes, and induced seismicity. As a result, it serves as a vital tool for predicting induced seismicity and optimizing reservoir stimulation strategies. The Utah FORGE (Frontier Observatory for Research in Geothermal Energy) project, located near Milford, Utah, is a U.S. Department of Energy initiative aimed at advancing EGS technology. In April 2024, eight new stimulation stages (Stages 3R-10) were conducted in well 16A (injection well) subsequent to the first series of stimulation (Stages 1-3) performed in April, 2022. To monitor the induced seismicity, geophones were deployed in wells 58-32, 56-32, and 78B-32, while fiber optic cables were also installed in wells 16B, 78-32, and 78B-32 to collect microseismic data and detect frac hits Preliminary analyses of microseismic catalogs and fiber optic data suggest that the stimulated fractures in Stages 3R–6 closely align with that generated during Stage 3, indicating that the new stimulations were likely reactivating the previously stimulated fracture. To better understand the underlying process, a comprehensive modeling approach that can accurately capture thermal, hydrological, mechanical, and seismic responses is essential. In this work, we propose and utilize a coupled thermo-hydro-mechanical and earthquake (THM+E) simulation workflow to numerically investigate the stimulation activities on well 16A. The specific objective is to confirm whether the new stimulation stages (Stages 3R–6) reactivated fractures previously stimulated during Stage 3. For this purpose, we perform THM+E simulations individually for Stages 3, 3R, 4, and 5, incorporating the discrete fracture networks (DFNs) created by the plane-fitting technique based on the microseismic catalogs. The simulation workflow consists of two separate models: a THM model and an earthquake model, coupled in a one-way manner. Detailed descriptions of the workflow are provided in Section 3. Simulation results are presented in terms of injection pressure, permeability evolution, and predicted seismic catalogs, which are then compared with field data for further analyses. This report is structured as follows. In Section 2, we present detailed analyses of the field data and propose the hypothesis that the new stimulation stages (Stages 3R–6) were probably reactivating the previously stimulated fractures in Stage 3. In Section 3, we introduce the coupled THM+E workflow and the problem setup to validate our hypothesis, followed by the simulation results for each stage in Section 4. Meanwhile, discussions are included to analyze the model predictions and their comparison with field data. Lastly, we conclude the report and outline future plans in Section 5.

15 GEOTHERMAL ENERGY↗

Utah FORGE Project 3-2417: Simulations for Distributed Acoustic Sensing Strain Signatures as an Indicator of Fracture Connectivity

This dataset encompasses simulations of strain signatures from both hydraulically connected and "near-miss" fractures in enhanced geothermal systems (EGS). The files and results are presented from the perspective of digital acoustic sensing's (DAS) potential to differentiate the two fracture types. This dataset was acquired by the FOGMORE R&D project (Fiber Optic Geophysical MOnitoring of Reservoir Evolution), under Utah FORGE R&D Project 3-2417. Included are simulation and results via MatLab and COMSOL files, as well as a thesis and paper summarizing the results. Some stimulated fractures may be incomplete, approaching but not intersecting the production well. These "near-miss" fractures can be addressed in future stimulation stages or re-stimulated to complete the connection. We propose the use of fiber optic distributed acoustic sensing (DAS) as a method by which near-miss stimulated fractures may be identified and distinguished from hydraulically connected fractures. The low-frequency sub-nanostrain signatures of both complete and near-miss fractures in DAS data are simulated in this study using a hydrogeomechanical discrete fracture network model. The spatial distribution of strain was found to be an accurate indicator. However, this indicator must be evaluated in the context of DAS gauge length and spatial sampling. These simulations are a precursor to tests conducted at FORGE in 2023.

15 GEOTHERMAL ENERGY↗

Deformation Precursors to Catastrophic Failure in Rocks

Forecasting the timing of catastrophic failure, such as crustal earthquakes, has been a central concern for centuries. Such forecasting requires identifying signals that evolve or accelerate in the precursory phase leading to failure, and the subset of signals that may be detected in the crust. We develop machine learning models to predict the proximity of catastrophic failure in synchrotron X-ray tomography triaxial compression experiments on rocks using characteristics of evolving fracture networks. We then examine the characteristics that most strongly influence the model results, and thus may be considered the best predictors of the proximity of macroscopic failure. Finally, the resulting suite of predictive parameters underscores the importance of dilation in the precursory phase leading to catastrophic failure. The results indicate that the evolution of the strain energy density field may provide more robust predictions of the proximity of failure than other existing metrics of rock deformation.

58 GEOSCIENCES↗

Utah FORGE 5-2565: Hydrothermal Evolution of Fracture Properties - Workshop Presentation

This is a presentation on the Evolution of Permeability and Strength Recovery of Shear Fractures Under Hydrothermal Conditions project by the U.S. Geological Survey, presented by Dr. David Lockner. The project's objective was to determine how thermal, hydraulic, mechanical, and chemical processes affect the sustainability of fracture networks in geothermal reservoirs and provide strategies for improved EGS techniques that maximize thermal coupling and increase reservoir longevity. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

New Fracture Diagnostic Tool for Unconventionals: High-Resolution Distributed Strain Sensing via Rayleigh Frequency Shift during Production in Hydraulic Fracture Test 2

Fiber Optic monitoring in unconventional reservoirs has proven to be an invaluable diagnostic tool for assessing both near-wellbore stimulation effectiveness and to help describe the far-field frac geometries created by hydraulic fracture stimulation. Unfortunately, gaining any detailed qualitative and quantitative understanding of the near-wellbore frac geometry or cluster/stage productivity during production via Fiber Optic (FO) has proven to be more difficult, particularly in wells producing liquids. A new FO diagnostic method, Distributed Strain Sensing based on Rayleigh Frequency Shift (DSS-RFS), first demonstrated for oil and gas applications in the Hydraulic Test Site 2 (HFTS2) provides new insights about the characteristics of near-wellbore-region (NWR) during production. DSS-RFS is different from other FO strain measurements because it relies on accurate measurement of frequency shifts of Rayleigh backscattered spectrum obtained by scanning the fiber with a coherent optical time-domain reflectometer with a range of laser frequencies using a tunable-wavelength laser system. Changes in strain are measured with an extremely high spatial resolution of 20 cm and with high signal-to-noise ratios over long distances. In HFTS2, strain changes for the entire wellbore have been measured twice during scheduled shut-in and reopening operations (February 2020 and September 2020). After removing temperature effects, consistent strain changes have been observed at the location of most perforation clusters. These are caused by near wellbore fracture aperture changes due to pressure increases during shut-in within the near-wellbore fracture network. The strain-change patterns from the DSS-RFS during shut-in correlate very well with the location of clusters and allow for the definition of extending intervals with positive strain signals at each cluster and slightly compressing intervals with negative strain signals between the clusters and in the non stimulated intervals. The locations of the measured positive strain peaks also show good correspondence to DAS acoustic intensity measurements acquired during the stimulation. The geometry and magnitude of the strain changes differ significantly between the two tested completion designs in the same well. During shut in and reopening each cluster exhibit its own strain-change / pressure path. In addition, the September 2020 dataset also revealed the existence of small but measurable strain changes as consequence of pressure decline during production. These strain changes also correlate well with the presence of producing clusters, but the strain-rate signals are opposite to that obtained during shut-in and reopening operations. Although Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/2-21URTC/D021S031R002/2477551/urtec-2021-5408-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5408 2 we are still in the early stages of exploring the potential of this novel FO technique, we believe that the highly detailed information contained in the measurement of strain changes using DSS-RFS during production can significantly improve our understanding of near-wellbore hydraulic fracture characteristics and the relationships between stimulation and production from unconventional oil and gas wells.

04 OIL SHALES AND TAR SANDS↗

A mineral precipitation model based on the volume of fluid method

A novel volume of fluid method is presented for mineral precipitation coupled with fluid flow and reactive transport. The approach describes the fluid-solid interface as a smooth transitional region, which is designed to provide the same precipitation rate and viscous drag force as a sharp interface. Specifically, the governing equation of mineral precipitation is discretized by an upwind scheme, and a rigorous effective viscosity model is derived around the interface. The model is validated against analytical solutions for mineral precipitation in channel and ring-shaped structures. It also compares well with interface tracking simulations of advection-diffusion-reaction problems. Here, the methodology is finally employed to model mineral precipitation in fracture networks, which is challenging due to the low porosity and complex geometry. Compared to other approaches, the proposed model has a concise algorithm and contains no free parameters. In the modeling, only the pore space requires meshing, which improves the computational effciency especially for low-porosity media.

58 GEOSCIENCES↗

Verification benchmarks for single-phase flow in three-dimensional fractured porous media

Flow in fractured porous media occurs in the earth’s subsurface, in biological tissues, and in man-made materials. Fractures have a dominating influence on flow processes, and the last decade has seen an extensive development of models and numerical methods that explicitly account for their presence. To support these developments, four benchmark cases for single-phase flow in three-dimensional fractured porous media are presented. Furthermore, the cases are specifically designed to test the methods’ capabilities in handling various complexities common to the geometrical structures of fracture networks. Based on an open call for participation, results obtained with 17 numerical methods were collected. This paper presents the underlying mathematical model, an overview of the features of the participating numerical methods, and their performance in solving the benchmark cases.

97 MATHEMATICS AND COMPUTING↗

The effects of in-situ emulsion formation and superficial velocity on foam performance in high-permeability porous media

Foam has been considered as a mobility control agent for Enhanced Oil Recovery (EOR) applications in heterogeneous and fractured reservoirs. Foam enhances sweep efficiency by enabling the injected gas to flow from high-permeability to low-permeability regions. The foam injection velocity is an essential factor affecting foam mobility control and flow behavior. Furthermore, the presence of remaining oil adversely impacts foam generation leading to a failure in governing mobility control. In this study, foam performance in establishing mobility control effect and favorable apparent viscosity was experimentally investigated under a range of total superficial velocities in the presence and absence of crude oil during foam propagation in high permeability sand packs representing a propped fracture network. In the absence of oil, a pronounced effect of total superficial velocity on the mobility control performance was observed at the transition foam quality regime. Co-injection of oil and foam led to noticeable foam destabilization, as expected. However, a further increase in oil fractional flow resulted in larger overall flow resistance. We found that the formation of in-situ surfactant/oil emulsion contributed to the high apparent viscosity exhibited at the steady-state condition. These findings suggest that the steady-state flow resistance established during foam flooding at high oil saturations should be interpreted as the mobility control effect resulting from emulsion formation rather than the development of strong foam.

02 PETROLEUM↗

Aperture size distribution, length, and preferential location of bed-parallel veins in shale

Bed-parallel, calcite-filled veins (BPVs) are common in shale formations, and although they have been widely described in other studies, little is known about their population aperture size distribution. To address this knowledge gap, we analyzed BPV sizes in outcrops and cores from the Vaca Muerta Formation, Neuquén Basin, Argentina; in two cores from the Marcellus Formation, Appalachian Basin, northeast Pennsylvania; and in one core from the Wolfcamp Shale, Delaware Basin, West Texas. Nine out of ten aperture size populations follow a negative exponential distribution, with one following a weak power law. Bed-parallel vein size distribution and intensity vary among formations and within the same shale. We define three groups of distributions: (1) Vaca Muerta outcrops, with the highest BPV intensity and the largest BPVs (cumulative frequency of 4.9 BPVs per meter [BPVs/m] for apertures 0.265 mm to 8.7 cm); (2) Vaca Muerta cores with a similar BPV intensity overall but with no apertures wider than 1.2 cm; and (3) Vaca Muerta, Wolfcamp, and Marcellus cores with the fewest BPVs (cumulative frequency up to 0.63 BPVs/m) and very few wider than 1 cm. Aperture and length in two outcrop data sets are weakly positively correlated and follow power laws with exponents of 0.44 and 0.49. Mechanical interfaces at boundaries between different lithologies exert a strong control on BPV location, with 65–75% of observed interfaces having BPVs along them. Only 25–30% of the BPVs occur at observed material interfaces, however, and unless subtle, unobserved mechanical layering is present, other factors must also control location. BPV intensity and organic richness (TOC) from Vaca Muerta well logs are correlated in some instances but not in others, indicating TOC is not always a good proxy for BPV location or intensity. Furthermore, these findings provide useful information for modeling of hydraulic fracture treatments where BPVs may influence development of the stimulated fracture network, for example by limiting height growth.

58 GEOSCIENCES↗

Volumetric and shear strain localization throughout triaxial compression experiments on rocks

Deformation localization is a widely observed, but rarely quantified process in the crust. Recent observations suggest that the localization of seismicity and fracture networks can help identify the approach to catastrophic failure. Here, we quantify the localization processes of the volumetric and deviatoric strain components in twelve triaxial compression experiments imaged with X-ray tomography. We capture three-dimensional images of the rock cores during triaxial compressing toward failure, and then calculate the local strain components using digital volume correlation. The divergence and curl of the incremental displacement vector field provide the volumetric and deviatoric components of the strain field. We quantify localization using the proportion of the rock occupied by high magnitudes of the volumetric and deviatoric strains, and the Gini coefficient of these high magnitude strains, which measures the deviation from a uniform process. We find that the vast majority, but not all, of the experiments experience strain localization toward failure. The rocks typically experience their maximum degree of strain localization not immediately preceding failure, but on average at 90% of the failure stress. The volumetric strain tends to localize more than the deviatoric strain. Finally, these observations support using the localization of the volumetric strain, along with the deviatoric strain, to identify the evolution of the precursory phase preceding earthquakes.

58 GEOSCIENCES↗