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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Risk Assessment of Carbon Sequestration into A Naturally Fractured Reservoir at Kevin Dome, Montana

In this report, we describe risk assessment work done using the National Risk Assessment Partnership (NRAP) applied to CO 2 storage at Kevin Dome, Montana. Geologic CO 2 sequestration in saline aquifers poses certain risks including CO 2 /brine leakage through wells or non-sealing faults into groundwater or to the land surface. These risks are difficult to quantify due to data availability and uncertainty. One solution is to explore the consequences of these limitations by running large numbers of numerical simulations on the primary CO2 injection reservoir, shallow reservoirs/aquifers, faults, and wells to assess leakage risks and uncertainties. However, a large number of full-physics simulations is usually too computationally expensive. The NRAP integrated assessment model (NRAP-IAM) uses reduced order models (ROMs) developed from full-physics simulations to address this issue. A powerful stochastic framework allows NRAPIAM to explore complex interactions among many uncertain variables and evaluate the likely performance of potential sequestration sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Model Advancements to Enable Impact Analysis of Climate Change on Streamflow Temperature

With support from the Department of Energy’s Water Power Technologies Office, Pacific Northwest National Laboratory (PNNL) has developed new tools that incorporate cutting-edge climate and hydrological science capabilities to assess the potential long-term impacts of future climate conditions on unregulated streamflow and water temperature within watershed-river-reservoir systems. The objectives of this project were achieved by enhancing key hydrologic and hydrodynamic models and transferring them to a high-performance computing environment to provide a high-spatiotemporal resolution, multi-scale modeling framework. The new modeling framework has the potential to quantify risks related climate change impacts on runoff, unregulated streamflow, and water temperature. Initial development and demonstration of the modeling framework was conducted under historical and future climate conditions in the Columbia River Basin in the Pacific Northwest and the Connecticut River Basin in New England.

13 HYDRO ENERGY↗
DOE OSTI2021

Simulation of Hurricane Harvey flood event through coupled hydrologic-hydraulic models: Challenges and next steps

Using the 2017 Hurricane Harvey flood event as a test case, this study set up a series of sensitivity analyses to highlight three challenges associated with large-scale flood inundation modeling, including (a) model parameterization, (b) errors in digital elevation models, and (c) effects of reservoir retention. Driven by radar-based hourly rainfall data, a series of hydrologic-hydraulic models including the VIC hydrologic model, RAPID routing model, and Flood2D-GPU hydrodynamic model are set up over Harris County, Texas, to simulate flood inundation and hazards. The results demonstrate the importance of hydrologic parameters in improving flood modeling. For a large flood event such as Hurricane Harvey, the effect of the initial water depths is insignificant. The Manning's n values may increase the peak water depth by ~1%, the flood extents by 65km 2 , and the high danger zone by ~6%. On the contrary, the bathymetry correction factors may reduce the flood extent by ~1.4% and the high-danger zone by ~4%. Reducing the reservoir storage capacity to 1% may increase the flood extent by ~4% and the high-danger zone by ~17%. This study may provide supporting information to guide and prioritize the development of future high-performance computing hydrodynamic large-scale flood simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Fracture-matrix fluid exchange in oil-bearing unconventional mudstones

The poromechanical properties of unconventional reservoir materials are in large part dictated by their mineralogy. Since these properties govern the response to stress experienced during hydraulic fracturing, fluid production, and fluid injection, they play a central role in the formation of microcracks or bedding delaminations which ultimately dominate mass transport. In this work we study access to the porosity of end member unconventional reservoir materials, where the end members are predominantly dictated by carbonate content. Access to the porosity is quantified using state of the art 3D x-ray computed tomography coupled with physics informed data analytics. Xenon gas, which attenuates x-rays, provides a spatiotemporal map of access to the porosity. The accessible porosity is quantified over a range of net confining stress relevant to the manmade disturbances listed above. These experiments demonstrate that heavily carbonated mudstones are nearly impermeable at the core (~ cm) scale, while carbonate free analogues afford better access to the microstructure. Consistent with previous qualitative 2D radiographs, access to the interior of the clastic mudstones is first observed along planar microcracks, followed by slow penetration into the surrounding matrix. Physics informed data analytics of the 3D tomography measurements presented here show that these microcracks do not permit uniform access to the adjacent rock matrix. In addition, variation of the effective pressure elucidates the mechanisms that govern fracture/matrix fluid exchange. Under conditions consistent with hydrocarbon production fluid accumulates in the immediate vicinity of the nearest microcrack. While there is clear evidence that, as intended, part of this accumulation is from the more distant matrix, fluid is also squeezed out of the microcrack. The fluid build-up at the microcrack indicates that migration out of the rock is hindered by the coupled poroelastic response of the microcrack and adjacent rock matrix. We show that these mechanisms ultimately account for the meager oil recovery factors realized in practice. These insights have implications for making reservoir scale predictions based on core scale observations, and provide a basis for devising new asset development techniques to access more porosity, and enhance fluid extraction. Finally, these findings shed light on key features and mechanisms that govern shale storage capacity, with relevance to other important industrial processes, such as geologic CO 2 storage.

58 GEOSCIENCES↗
DOE OSTI2021

Sealing of fractures in a representative CO 2 reservoir caprock by migration of fines

The impact of fines migration on fracture transmissivity reduction was investigated by injecting a brine solution containing a suspension of 0.1 wt. % kaolinite particles with a mean particle size distribution of 9.6 µm through fractured shale core samples. The fractures had apertures estimated to be approximately 100 µm. A mass balance approach was used to determine the quantity of kaolinite that was deposited within the fractures (influent – effluent = amount deposited in fractures). Large fractions (44 to 90%) of the suspended kaolinite pumped through the fractures were deposited within the fractures. Based on fracture volumes estimated with X-ray computed tomography, it was determined that approximately 10 to 17% of the fracture volume was filled with kaolinite at the point when flow was completely restricted. These results indicate that 100 µm fractures in CO 2 reservoir caprocks could be sealed within hours if the brines passing through the fractures contain a proportional volume of particulates to the tests performed in this laboratory study.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2018

Competitive Adsorption of H 2 O and CO 2 in 2-Dimensional Nanoconfinement: GCMD Simulations of Cs- and Ca-Hectorites

The intercalation of H 2 O, CO 2 , and other fluid species in expandable clay minerals (smectites) may play a significant role in controlling the behavior of these species in geological carbon sequestration and enhanced petroleum production and has been the subject of intensive study in recent years. This paper reports the results of a computational study of the effects of the properties of the charge-balancing, exchangeable cations on H 2 O and CO 2 intercalation in the smectite mineral, hectorite, in equilibrium with an H 2 O-saturated supercritical CO 2 fluid under reservoir conditions using grand canonical molecular dynamics methods. The results show that the intercalation behavior is greatly different for the cations with relatively low hydration energies and high affinities for CO 2 (here Cs + ) than for cations with higher hydration energies (here Ca 2+ ). With Cs + , CO 2 intercalation occurs in a 1-layer structure and does not require H 2 O intercalation, whereas with Ca 2+ , the presence of a sub-monolayer of H 2 O is required for CO 2 intercalation. The computational results provide a detailed structural, dynamical, and energetic insight into the differences in the intercalation behavior and are in excellent agreement with in situ experimental X-ray diffraction, infrared, quartz crystal microbalance, and nuclear magnetic resonance results for smectite materials obtained under reservoir conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Integrated Experimental and Modeling Study of Geochemical Reactions of Simple Fracturing Fluids with Caney Shale

Interactions between rock minerals and hydraulic fluids directly impact the geochemical and geomechanical properties of shale formations. However, the mechanisms of geochemical reactions in shale unconventional reservoirs remain poorly understood. Here, to investigate the geochemical reactions between shale and hydraulic fracturing fluids, a series of batch reactor experiments were undertaken. Three rock samples with different mineralogical compositions and three fluid samples of different compositions (deionized water, deionized water + 2% potassium chloride (KCl), and deionized water + 0.5% choline chloride (C 5 H 14 ClNO) were used. Experiments were undertaken at reservoir temperature and atmospheric pressure. Elemental compositions of effluents after 1, 3, 7, 14, 28 days were analyzed using Inductively Couple Plasma Mass Spectrometry (ICP-MS). Medical Computed Tomography (CT) scan and X-ray Fluorescence (XRF) were conducted on the entire core run to help upscale results obtained from rock-fluid interaction experiments. Geochemical modeling using a reactive simulator, TOUGHREACT, was undertaken to corroborate experimental results. Results show that lower pH triggered high dissolution rates in the rock samples, especially the carbonate components. As pH increased, the rate of dissolution declined significantly, though for most cases dissolution still continued. Observed dissolved silica concentrations were much higher than the quartz solubility, suggesting that much of the silica originates from more soluble silica polymorphs and possibly desorption from clay mineral exchange sites. Concentration of most elemental species in solution increased but aluminium and magnesium concentrations declined rapidly following initial entry into solution. Geochemical modeling corroborated the conclusions regarding mineral dissolution and precipitation observed from experiments, notably; the dissolution of calcite and oxidation of pyrite in reacted shale samples, the likely presence of silica polymorphs such as opal, chalcedony or amorphous silica in these samples, and the reduction of Al and Mg concentrations in solution by precipitation of secondary aluminosilicate phases. The de-flocculation of clay minerals during reaction implies fines migration after hydraulic fracturing. This is detrimental to reservoir productivity as clay fines are displaces and lodged within the micro and nano-fractures created during fracturing. The immediate consumption of aluminium and magnesium also has implications on blockage of hydrocarbon pathways due to precipitation of new minerals in these locations.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2020

Multi-Size Proppant Pumping Schedule of Hydraulic Fracturing: Application to a MP-PIC Model of Unconventional Reservoir for Enhanced Gas Production

Slickwater hydraulic fracturing is becoming a prevalent approach to economically recovering shale hydrocarbon. It is very important to understand the proppant’s transport behavior during slickwater hydraulic fracturing treatment for effective creation of a desired propped fracture geometry. The currently available models are either oversimplified or have been performed at limited length scales to avoid high computational requirements. Another limitation is that the currently available hydraulic fracturing simulators are developed using only single-sized proppant particles. Motivated by this, in this work, a computationally efficient, three-dimensional, multiphase particle-in-cell (MP-PIC) model was employed to simulate the multi-size proppant transport in a field-scale geometry using the Eulerian–Lagrangian framework. Instead of tracking each particle, groups of particles (called parcels) are tracked, which allows one to simulate the proppant transport in field-scale geometries at an affordable computational cost. Then, we found from our sensitivity study that pumping schedules significantly affect propped fracture surface area and average fracture conductivity, thereby influencing shale gas production. Motivated by these results, we propose an optimization framework using the MP-PIC model to design the multi-size proppant pumping schedule that maximizes shale gas production from unconventional reservoirs for given fracturing resources.

42 ENGINEERING↗
DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗
DOE OSTI2020

Inversion of Time-Lapse Seismic Reservoir Monitoring Data Using CycleGAN: A Deep Learning-Based Approach for Estimating Dynamic Reservoir Property Changes

Carbon capture and storage is being pursued globally as a geoengineering measure for reducing the emission of anthropogenic CO 2 the atmosphere. Comprehensive monitoring, verification, and accounting programs must be established for demonstrating the safe storage of injected CO 2 . One of the most commonly deployed monitoring techniques is time-lapse seismic reservoir monitoring (also known as 4-D seismic), which involves comparing 3-D seismic survey data taken at the same study site but over different times. Analyses of 4-D seismic data volumes can help improve the quality of storage reservoir characterization, track the movement of injected CO 2 plume, and identify potential CO 2 spillover/leakage from the storage reservoirblue. However, the derivation of high-resolution CO 2 saturation maps from 4-D seismic data is a highly nonlinear and ill-posed inverse problem, often requiring significant computational effort. In this research, we apply a physics-based deep learning method to facilitate the solution of both the forward and inverse problems in seismic inversion while honoring physical constraints. A cycle generative adversarial neural network (CycleGAN) model is trained to learn the bidirectional functional mappings between the reservoir dynamic property changes and seismic attribute changes, such that both forward and inverse solutions can be obtained efficiently from the trained model. We show that our CycleGAN-based approach not only improves the reliability of 4-D seismic inversion but also expedites the quantitative interpretation. Our deep learning-based workflow is generic and can be readily used for reservoir characterization and reservoir model updates involving the use of 4-D seismic data.

58 GEOSCIENCES↗
DOE OSTI2018

A learning-based data-driven forecast approach for predicting future reservoir performance

Quantification of the predictive uncertainty of subsurface models has long been investigated. The traditional workflow is to calibrate prior models to match observed data, and then use the posterior models to simulate future system performance. Not only are these procedures computationally expensive, but they also have issues in maintaining geological model constraints during the calibration step. Data space inversion (DSI) was introduced recently to predict future system performance without the iterative history matching or model calibration step. In general, DSI approaches seek to establish a statistical relationship between the observed and forecast variables, as well as to quantify the predictive uncertainty of the forecast variables, by using an ensemble of uncalibrated prior models. Existing DSI approaches all require a number of complex transformation and mapping operations, which may deter their widespread use. Here in this study, we introduce a new and simpler DSI approach, the learning-based, data-driven forecast approach (LDFA), by combining dimension reduction and machine learning techniques to quickly provide accurate forecast results and reliably quantify corresponding uncertainty in the results. Our LDFA framework is demonstrated using two supervised learning algorithms, artificial neural network (ANN) and support vector regression (SVR), on two representative examples from reservoir engineering and geological carbon storage. Results suggest that our approach provides accurate forecast results (e.g., future oil production rate or cumulative injected CO 2 ) and reasonable predictive uncertainty intervals. Our framework is generic and may be applied to other surface and subsurface problems.

42 ENGINEERING↗
DOE OSTI2018

Fluorescence Correlation Spectroscopy with Photobleaching Correction in Slowly Diffusing Systems

Fluorescence correlation spectroscopy (FCS) is a powerful tool to quantitatively study the diffusion of fluorescently labeled molecules. It allows in principle important questions of macromolecular transport and supramolecular aggregation in living cells to be addressed. However, the crowded environment inside the cells slows diffusion and limits the reservoir of labeled molecules, causing artifacts that arise especially from photobleaching and limit the utility of FCS in these applications. We present a method to compute the time correlation function from weighted photon arrival times, which compensates computationally during the data analysis for the effect of photobleaching. We demonstrate the performance of this method using numerical simulations and experimental data from model solutions. Using this technique, we obtain correlation functions in which the effect of photobleaching has been removed and in turn recover quantitatively accurate mean-square displacements of the fluorophores, especially when deviations from an ideal Gaussian excitation volume are accounted for by using a reference calibration correlation function. This allows quantitative FCS studies of transport processes in challenging environments with substantial photobleaching like in living cells in the future.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

A computational fluid dynamics modeling study of guide walls for downstream fish passage

A partial-depth, impermeable guidance structure (or guide wall) for downstream fish passage is typically constructed as a series of panels attached to a floating boom and anchored across a water body (e.g. river channel, reservoir, or power canal). The downstream terminus of the wall is generally located nearby to a fish bypass structure. If guidance is successful, the fish will avoid entrainment in a dangerous intake structure (i.e. turbine intakes) while passing from the headpond to the tailwater of a hydroelectric facility through a safer passage route (i.e. the bypass). The goal of this study is to determine the combination of guide wall design parameters that will most likely increase the chance of surface-oriented fish being successfully guided to the bypass. To evaluate the flow field immediately upstream of a guide wall, a parameterized computational fluid dynamics model of an idealized power canal was constructed in © ANSYS Fluent v 14.5 (ANSYS Inc., 2012). The design parameters investigated were the angle and depth of the guide wall and the average approach velocity in the power canal. Results call attention to the importance of the downward to sweeping flow ratio and demonstrate how a change in guide wall depth and angle can affect this important hydraulic cue to out-migrating fish. The key findings indicate that a guide wall set at a small angle (15° is the minimum in this study) and deep enough such that sweeping flow dominant conditions prevail within the expected vertical distribution of fish approaching the structure will produce hydraulic conditions that are more likely to result in effective passage.

42 ENGINEERING↗
DOE OSTI2022

Mechanisms of shape transfer and preheating in indirect-drive double shell collisions

Implosions of Hohlraum-driven double shell targets as an alternative inertial confinement fusion concept are underway at the National Ignition Facility. The double shell system relies on a series of energy transfer processes starting from thermal x-ray absorption by the outer shell, followed by collisional transfer of kinetic energy to a heavy metal inner shell, and finally, conversion to the internal energy of the deuterium-tritium fuel. During each of these energy transfer stages, low-mode asymmetries can act to reduce the ideal transfer efficiency degrading double shell performance. Mechanisms, such as hard x-ray preheat from the Hohlraum, not only decrease the efficiency of kinetic energy transfer but may also be a source of low-mode asymmetry. In this article, we evaluate the shape transfer processes through the time of shell collision using two-dimensional integrated Hohlraum and capsule computations. We find that the dominant mode of the shape transfer is well described using a “radial impulse” model from the shape of the foam pressure reservoir. To evaluate the importance of preheat on inner shell shape, we also report on first measurements of Au L-shell preheat asymmetry in a double shell with a tungsten pusher. These measurements showed a 65% higher preheat velocity at the pole of the capsule relative to the equator. We also found that the experiments provided rigorous constraints by which to test the Hohlraum model settings that impact the amount and symmetry of Au L-shell preheat via the plasma conditions inside the outer cone Au bubble.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Hydrogen Fracture Toughness Tester Completion

The Hydrogen Fracture Toughness Tester (HFTT) is a mechanical testing machine designed for conducting fracture mechanics tests on materials in high-pressure hydrogen gas. The tester is needed for evaluating the effects of hydrogen on the cracking properties of tritium reservoir materials. It consists of an Instron Model 8862 Electromechanical Test Frame; an Autoclave Engineering Pressure Vessel, an Electric Potential Drop Crack Length Measurement System, associated computer control and data acquisition systems, and a high-pressure hydrogen gas manifold and handling system.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Time-dependent quasi-one-dimensional simulations of high enthalpy pulse facilities

A numerical methodology is presented for simulating the time-dependent reacting flow inside the entire length of high enthalpy pulse facilities. The methodology is based on a finite-volume TVD scheme for the quasi-1D Euler equations coupled with finite-rate chemistry. A moving mesh and tracking of gas interfaces are used to overcome certain numerical difficulties associated with these types of flows. Simulation results of a helium driven shock tube show that computations can be used to predict the off-tailored behavior of shock tubes and tunnels. Particular attention is given to computations of the flow through the NASA Ames 16-inch combustion driven shock tunnel which show the influence of nonuniformities in the driver section on the reservoir conditions; and the effect of finite secondary diaphragm opening times on the chemical composition of the test flow in the HYPULSE expansion tube.

Wilson, Gregory J.↗
DOE OSTI2020

Contact Angle Measurements Using Sessile Drop and Micro-CT Data from Six Sandstones

Numerous sessile drop and micro-computed tomography (micro-CT) studies have been conducted to quantify Geologic Carbon Storage formation wettability by measuring static contact angles (θ); however, the influence of pore geometry remains unknown. In this work, six sandstones (Bandera Brown, Berea, Bentheimer, Mt. Simon, Navajo, and Nugget) are used to measure θ using the two aforementioned experimental methods at identical testing conditions (45°C and 12.41 MPa). The range of θ measured at in situ conditions (micro-CT) exceeds those the range at ex situ (sessile drop method) conditions for all sandstones. However, when droplets with more representative in situ diameters are analyzed, θ averages show ex situ θ exceed those of in situ θ. Pore geometry does influence local θ, but the size of ex situ droplets relative to pore size appears to influence θ. This is an important to consider for future sessile drop studies used for analysis of CO 2 behavior in carbon storage reservoirs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Control of Cement Timing, Mineralogy, and Texture on Hydro-chemo-mechanical Coupling from CO2 Injection into Sandstone: A Synthesis

Carbon capture, utilization, and storage (CCUS) has been widely applied to enhance oil recovery (CO2-EOR). A thorough investigation of the impact of injecting CO2 into a heterogeneous reservoir is critical to understanding the overall reservoir robustness and storage performance. We conducted fifteen flow-through tests on Morrow B sandstone that allowed for chemical reactions between a CO2-rich brackish solution and the sandstones, and four creep/flow-through tests that simultaneously allowed for chemical reactions and stress monitoring. From fluid chemistry and X-ray computed tomography, we found that the dissolution of disseminated cements and the precipitation of iron-rich clays did not significantly affect the permeability and geomechanical properties. Minor changes in mechanical properties from Brazilian and creep tests indicated that the matrix structure was well-supported by early diagenetic quartz overgrowth cement and the reservoir’s compaction history at deep burial depths. However, one sample experienced a dissolution of poikilotopic calcite, leading to a permeability increase and significant tensile strength degradation due to pore opening, which overcame the effect of the early diagenetic cements. We concluded that the Morrow B sandstone reservoir is robust for CO2 injection. Most importantly, cement timing, the abundance and texture of reactive minerals, and the reservoir’s burial history are critical in predicting reservoir robustness and storage capacity for CO2 injection.

Wu, Zhidi (ORCID:0000000338869492)↗