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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An integrated approach to derive relative permeability from capillary pressure

Surface tension affects all aspects of fluid flow in porous media. Through measurements of surface tension interaction under multiphase conditions, a relative permeability curve can be determined. Relative permeability is a numerical description of the interaction between two or more fluids and the porous media. It is a critical parameter for various tools that characterize subsurface multiphase flow systems, such as numerical simulation for carbon sequestration, oil and gas development, and groundwater contamination remediation. Therefore, it is critical to get a good statistical distribution of relative permeability in the porous media under study. Empirical formula for determining relative permeability from capillary pressure are already well established but do not provide the needed flexibility that is required to match laboratory-derived relative permeability curves. By expanding the existing methods for calculating relative permeability from capillary pressure data, it is possible to create both two and three-phase relative permeability curves. Mercury intrusion capillary pressure (MICP) data from the Morrow 'B' Sandstone coupled with interfacial tension and contact angle measurements were used to create a suite of relative permeability curves. Furthermore, these curves were then calibrated to a small sample of existing laboratory curves to elucidate common fitting parameters for the formation that were then used to create relative permeability curves from MICP data that does not have an associated laboratory-measured relative permeability curve.

58 GEOSCIENCES↗
DOE OSTI2017

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. It relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.

58 GEOSCIENCES↗
DOE OSTI2014

Krypton-81 in groundwater of the Culebra Dolomite near the Waste Isolation Pilot Plant, New Mexico

TheWaste Isolation Pilot Plant (WIPP) in New Mexico is the first geologic repository for disposal of transuranic nuclear waste fromdefense-related programs of the US Department of Energy. It is constructed within halite beds of the Permian-age Salado Formation. The Culebra Dolomite, confined within Rustler Formation evaporites overlying the Salado Formation, is a potential pathway for radionuclide transport from the repository to the accessible environment in the human-disturbed repository scenario. Although extensive subsurface characterization and numerical flow modeling of groundwater has been done in the vicinity of theWIPP, few studies have used natural isotopic tracers to validate the flow models and to better understand solute transport at this site. The advent of Atom-Trap Trace Analysis (ATTA) has enabled routine measurement of cosmogenic 81Kr (half-life 229,000 yr), a near-ideal tracer for long-term groundwater transport. We measured 81Kr in saline groundwater sampled from two Culebra Dolomite monitoring wells near the WIPP site, and compared 81Kr model ages with reverse particle-tracking results of well-calibrated flow models. The 81Kr model ages are ~130,000 and ~330,000 yr for high-transmissivity and low-transmissivity portions of the formation, respectively. Compared with flow model results which indicate a relatively young mean hydraulic age (~32,000 yr), the 81Kr model ages imply substantial physical attenuation of conservative solutes in the Culebra Dolomite and provide limits on the effective diffusivity of contaminants into the confining aquitards.

Sturchio, Neil C.↗
DOE OSTI2022

Photothermal Atomic Force Microscopy Coupled with Infrared Spectroscopy (AFM-IR) Analysis of High Extinction Coefficient Materials: A Case Study with Silica and Silicate Glasses

Photothermal atomic force microscopy coupled with infrared spectroscopy (AFM-IR) brings significant value as a spatially resolved surface analysis technique for disordered oxide materials such as glasses, but additional development and fundamental understanding of governing principles is needed to interpret AFM-IR spectra, since the existing theory described for organic materials does not work for materials with high extinction coefficients for infrared (IR) absorption. This paper describes theoretical calculation of a transient temperature profile inside the IR-absorbing material considering IR refraction at the interface as well as IR adsorption and heat transfer inside the sample. Furthermore, this calculation explains the differences in peak positions and amplitudes of AFM-IR spectra from those of specular reflectance and extinction coefficient spectra. It also addresses the information depth of the AFM-IR characterization of bulk materials. AFM-IR applied to silica and silicate glass surfaces has demonstrated novel capability of characterizing subsurface structural changes and surface heterogeneity due to mechanical stresses from physical contacts, as well as chemical alterations manifested in surface layers through aqueous corrosion.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site

Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering

58 GEOSCIENCES↗
DOE OSTI2020

The emergence of small-scale self-affine surface roughness from deformation

Most natural and man-made surfaces appear to be rough on many length scales. There is presently no unifying theory of the origin of roughness or the self-affine nature of surface topography. One likely contributor to the formation of roughness is deformation, which underlies many processes that shape surfaces such as machining, fracture, and wear. Using molecular dynamics, we simulate the biaxial compression of single-crystal Au, the high-entropy alloy Ni 36.67 Co 30 Fe 16.67 Ti 16.67 , and amorphous Cu 50 Zr 50 and show that even surfaces of homogeneous materials develop a self-affine structure. By characterizing subsurface deformation, we connect the self-affinity of the surface to the spatial correlation of deformation events occurring within the bulk and present scaling relations for the evolution of roughness with strain. These results open routes toward interpreting and engineering roughness profiles.

42 ENGINEERING↗
DOE OSTI2016

The direct-current response of electrically conducting fractures excited by a grounded current source

Hydraulic fracture stimulation of low permeability reservoir rocks is an established and cross–cutting technology for enhancing hydrocarbon production in sedimentary formations and increasing heat exchange in crystalline geothermal systems. Whereas the primary measure of success is the ability to keep the newly generated fractures sufficiently open, long–term reservoir management requires a knowledge of the spatial extent, morphology, and distribution of the fractures — knowledge primarily informed by microseismic and ground deformation monitoring. To minimize the uncertainty associated with interpreting such data, we investigate through numerical simulation the usefulness of direct-current (DC) resistivity data for characterizing subsurface fractures with elevated electrical conductivity by considering a geophysical experiment consisting of a grounded current source deployed in a steel cased borehole. In doing so, the casing efficiently energizes the fractures with steady current. Finite element simulations of this experiment for a horizontal well intersecting a small set of vertical fractures indicate that the fractures manifest electrically in (at least) two ways: (1) a local perturbation in electric potential proximal to the fracture set, with limited farfield expression and (2) an overall reduction in the electric potential along the borehole casing due to enhanced current flow through the fractures into the surrounding formation. The change in casing potential results in a measurable effect that can be observed far from fractures themselves. Under these conditions, our results suggest that farfield, timelapse measurements of DC potentials can be interpreted by simple, linear inversion for a Coulomb charge distribution along the borehole path, including a local charge perturbation due to the fractures. As a result, this approach offers an inexpensive method for detecting and monitoring the time-evolution of electrically conducting fractures while ultimately providing an estimate of their effective conductivity — the latter providing an important measure independent of seismic methods on fracture shape, size, and hydraulic connectivity.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Observing and modeling the effects of production infrastructure in electromagnetic surveys

Electromagnetic (EM) methods are among the original techniques for subsurface characterization in exploration geophysics because of their particular sensitivity to the earth electrical conductivity, a physical property of rocks distinct yet complementary to density, magnetization, and strength. However, this unique ability also makes them sensitive to metallic artifacts — infrastructure such as pipes, cables, and other forms of cultural clutter — the EM footprint of which often far exceeds their diminutive stature when compared to that of bulk rock itself. In the hunt for buried treasure or unexploded ordnance, this is an advantage; in the long-term monitoring of mature oil fields after decades of production, it is quite troublesome indeed. In this study we consider the latter through the lens of an evolving energy industry landscape in which the traditional methods of EM characterization for the exploration geophysicist are applied toward emergent problems in well-casing integrity, carbon capture and storage, and overall situational awareness in the oil field. We introduce case studies from these exemplars, showing how signals from metallic artifacts can dominate those from the target itself and impose significant burdens on the requisite simulation complexity. Furthermore, we show how recent advances in numerical methods mitigate the computational explosivity of infrastructure modeling, providing feasible and real-time analysis tools for the desktop geophysicist. Lastly, we demonstrate through comparison of field data and simulation results that incorporation of infrastructure into the analysis of such geophysical data is, in a growing number of cases, a requisite but now manageable step.

58 GEOSCIENCES↗
DOE OSTI2020

GBCGE Subsurface Database Explorer and APIs

This submission defines a DOI for the Great Basin Center for Geothermal Energy's (GBCGE) Subsurface Database Explorer web application and underlying data services, and acknowledges the INGENIOUS project as a major source of funding for data compilation and quality assurance. The GBCGE Subsurface Database Explorer is an interactive web mapping application that provides public access to the GBCGE Subsurface Database, and its collection of datasets pertinent to geothermal exploration, oil and gas exploration, critical mineral exploration, and other subsurface characterization for the Great Basin Region, western US. This is a living database, and will be continuously updated with new data and datasets as funding and motivations allow. The underlying database views that populate the web application are on an automated refresh schedule. Data sources and acknowledgements: We thank our partners with the Nevada Division of Minerals (NDOM), the Southern Methodist University (SMU), and Great Basin State Geological Surveys for their active efforts in data curation, schema design, and quality assurance. We also thank contributors among the USGS, Oregon Institute of Technology, State Divisions of Water Resources, State Divisions of Oil, Gas, and Minerals, and State Geological Surveys for open data availability and direct contributions made under the National Geothermal Data System (NGDS).

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Inverse problems in heterogeneous and fractured media using peridynamics

The following work presents an adjoint-based methodology for solving inverse problems in heterogeneous and fractured media using state-based peridynamics. We show that the inner product involving the peridynamic operators is self-adjoint. The proposed method is illustrated for several numerical examples with constant and spatially varying material parameters as well as in the context of fractures. We also present a framework for obtaining material parameters by integrating digital image correlation (DIC) with inverse analysis. This framework is demonstrated by evaluating the bulk and shear moduli for a sample of nuclear graphite using digital photographs taken during the experiment. The resulting measured values correspond well with other results reported in the literature. Lastly, we show that this framework can be used to determine the load state given observed measurements of a crack opening. Furthermore, this type of analysis has many applications in characterizing subsurface stress-state conditions given fracture patterns in cores of geologic material.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Summary of a Gas Transport Tracer Test in the Deep Cerros Del Rio Basalts, Mesita del Buey, Los Alamos NM.

Here we describe results from a tracer test in the Cerros del Rio basalt beneath Mesita del Buey, Technical Area 54 (TA-54) at Los Alamos National Laboratory (LANL or the Laboratory). This report follows from plans outlined in our previous Tracer Test Work Plan (LANL 2016). These activities were conducted by LANL to further characterize subsurface properties of the Cerros del Rio basalts at Material Disposal Area (MDA) L (Figure 1.1-1). The work presented follows from the “Interim Measures Work Plan for Soil-Vapor Extraction of Volatile Organic Compounds from Material Disposal Area L, Technical Area 54, Revision 1,” submitted to the New Mexico Environment Department (NMED) in September 2014 (LANL 2014). Remediation of the MDA L vapor plume by soil-vapor extraction (SVE) is recommended as part of the final remedy in the “Corrective Measures Evaluation Report for Material Disposal Area L, Solid Waste Management Unit 54-006, at Technical Area 54, Revision 2” to meet a remedial action objective of preventing groundwater from being impacted above a regulatory standard by the transport of volatile organic compounds (VOCs) to groundwater through soil vapor (LANL 2011).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Carbon Storage Assurance Facility Enterprise (CarbonSAFE): Integrated CCS Pre-Feasibility CarbonSAFE Illinois East Sub-Basin (Final Report)

Purpose of the project was to conduct a pre-feasibility assessment for commercial-scale CO 2 geological storage complexes in the East Sub-Basin of the Illinois Basin. This work will be used to advance the experience and knowledge about scaling up from demonstration to commercial-scale storage (CCS), and eventually readying sites for more than 50 million tonnes injection from one or more industrial sources. To accomplish this, the project formed a CCS coordination team with varied backgrounds to evaluate aspects of developing an integrated CCS project, including regulatory, legislative, technical, public policy, commercial and financial requirements. We developed a plan and strategy to address the technical and non-technical challenges to enable an economically feasible and publicly acceptable integrated CCS project. A significant output of this high-level technical evaluation of the East Sub-Basin was to identify suitable site(s) within the storage complex(es) that include detailed subsurface characterization and risk identification, along with evaluation of potential industrial CO 2 sources for sequestration.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Geo Thermal Cloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The project is motivated by the challenges, risks, and costs associated with geothermal exploration and production. Many processes and parameters impacting geothermal conditions are poorly understood. Diverse datasets are available to help characterize subsurface geothermal conditions (public and proprietary; satellite, airborne surveys, vegetation/water sampling, geological, geophysical, etc.). Yet, it is not clear how to properly leverage these datasets for geothermal exploration due to an incomplete understanding of how physical processes impacting subsurface geothermal conditions are represented in these observations. Recent advancements in machine learning (ML) provide great promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. Our goals and work under Phases 1 and 2 (as proposed) of this project address all these needs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2014

Final Report on Reservoir Modeling (SECARB Phase III Work Product 4.2.4.c)

The SECARB Partnership Anthropogenic Test, located in the Southeast Unit of the Citronelle oilfield will inject CO 2 into the saline waters of the Cretaceous Paluxy sandstone formation for three years. In order to accurately model the injection, migration, and long-term fate of CO 2 in the subsurface, GEM, a Computer Modeling Group software program for transport and geochemical modeling, was selected for the simulation. GEM is a very robust compositional reservoir simulator, with all the necessary options available for modeling CO 2 trapping mechanisms (including solubility, residual gas and mineralization). This simulation tool is widely known and used in the petroleum and sequestration industries. A reservoir model was built, based on a previously developed comprehensive picture of the subsurface geology at the site (Work Product 4.2.1.d - Report on Subsurface Characterization for the Anthropogenic Test Project Site). This report describes in details the different inputs that were used to create the model as well as the results of the injection scenario in terms of achievable injection rates, plume extent and pressure response.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

HFTS-2 (Final Report)

This report delves into the research program, identified tasks, various studies, observations, results, and conclusions under the Hydraulic Fracturing Test Site (HFTS-2) project. This test site is located in Loving County close to the Texas, New Mexico border. The program targeted the Wolfcamp formation in Delaware Basin. The aim of the project was to improve our understanding of hydraulic fracturing processes to not only optimize unconventional resource development in US Basins but to minimize environmental footprint as well. Various new diagnostic technologies were demonstrated at this site, including distributed acoustic microseismic, high resolution strain using Rayleigh frequency band (DSS-RFS), and in-fill proppant logging tool. Significant conclusions from this study include: 1) lateral and vertical fracture growth mapping as well as proppant transport behavior, 2) Use of DSS-RFS as a diagnostic tool to understand cluster level behavior, 3) Validation of proppant log, both at core scale as well as in-fill well implementation, and 4) New modeling tools to map far-field strain response using distributed strain sensing data. Specifically, far-field fracture distribution is influenced by linear fracture corridors defined by the stress-state as well as clustering behavior influenced by spatio-temporal effects. Depletion impacts on new stimulation was demonstrated and technically quantified. Significant vertical fracture height growth was observed. However, our understanding is limited by available gauge data availability. Numerical strain modeling techniques have been developed and demonstrated to help understand observed strain response behavior. Finally, proppant log has been further validated as a useful tool to map propped zones within the SRV. It has also shown very strong correlation with observed drawdown behavior at this test site. This report will detail many of these studies as well as technical results and conclusions from said studies. These include general subsurface characterization work, completion designs as implemented, studies looking at fracture geometry, high resolution microseismic study including source mechanisms, advanced DSS-RFS studies including drainage characterization, core characterization results, proppant analysis (core and in-fill child well), geochemistry, etc.

02 PETROLEUM↗
DOE OSTI2023

HFTS-1 (Final Report)

Despite the long history of hydraulic fracturing, the optimal number of fracturing stages during multi-stage fracture stimulation in horizontal wells can be a complex subject. In addition to the increased expense of multistage fracturing in horizontal wells, increasing the number of fracturing stages does not always correlate with a commensurate increase in production. The problem is the application of a uniform fracture stimulation design to all stages with no consideration for geological variations along the wellbore. The result is an inefficient use and costly waste of energy and water. Optimization of the fracturing process requires an understanding of the cause-and-effect relationship between fracturing parameters and local geological properties at a given location along the wellbore. Realizing that the generalized rock mechanics theories and hypotheses are not truly applicable to fractured and laminated shales, quantifiable impacts of a shale’s geomechanical and depositional features are a prerequisite for design and implementation of optimized hydraulic fractures. The overarching goal of this project is to understand and define the relationships of shale geology and fracture dynamics using detailed field data that includes coring of the fracture domain. Finally, resource recovery from shale formations is estimated to be less than fifteen percent. Research proposed in this project will establish the foundations for investigating enhanced recovery techniques for increased resource recovery in existing fracture treated wells. Natural gas as an EOR fluid is in the initial stages of being used broadly in the oil and gas industry and as such, many aspects of the process need to be researched and addressed prior to widespread acceptance. In addition, re-fracturing techniques, particularly using cemented liners also need to be further investigated. This project explores several of these EOR techniques in greater detail, not just at the theoretical level, but through actual field test sites. This report delves into the research program, identified tasks, several studies, observations, results, and conclusions under the Hydraulic Fracturing Test Site (HFTS) project. This test project is subdivided into three distinct phases and each phase is discussed in detail under separate sections. The original test site for Phase 1 as well as the Phase 2 site are in Midland Basin in Texas and operated by Laredo Petroleum. In the first two phases, the program targeted the Wolfcamp formation in Midland Basin. Phase 3 of the study targeted the EagleFord play in South Texas with Devon Energy as the operator. Significant conclusions from this study include: 1) lateral and vertical fracture growth mapping as well as proppant transport behavior, 2) Use of field gas and its applicability for huff n puff EOR injection in the Midland Basin, 3) Development and validation of proppant log, both at core scale as well as in-fill well implementation by analyzing drilling mud return samples, 4) Applicability of liner refracturing including best practices for enhanced unit level productivity. This report will detail all these studies as well as technical results and conclusions from said studies. These include general subsurface characterization work, completion designs as implemented, studies looking at fracture geometry, high resolution microseismic study, advanced crosswell strain mapping studies including drainage characterization, core characterization results, proppant analysis (core and observation wells), geochemistry, etc. to name a few.

02 PETROLEUM↗
DOE OSTI2022

Capillary Pressure to Relative Permeability: Task 7.3.4 Relative Permeability Analysis Final Report

Surface tension affects all aspects of fluid flow in porous media. Through measurements of surface tension interaction under multiphase conditions, a relative permeability relationship can be determined. Relative permeability is a numerical description of the interplay between two or more fluids and the porous media they flow through. It is a critical parameter for various tools used to characterized subsurface multiphase flow systems, such as numerical simulation for oil and gas development, carbon sequestration, and groundwater contamination remediation. Therefore, it is critical to get a good statistic distribution of relative permeability in the porous media under study. Empirical relationships for determining relative permeability from capillary pressure are already well established but do not provide the needed flexibility required to match laboratory derive relative permeability relationships. By expanding the existing methods for calculating relative permeability from capillary pressure data, it is possible to create both two and three-phase relative permeability relationships. Existing laboratory-measured relative permeability data along with mercury intrusion capillary (MICP) data coupled with interfacial tension and contact angle measurements were used to determine the efficacy of this approach to relative permeability curve creation. The relative permeability relationships determined with this method were fit to existing laboratory data to elucidate common fitting parameters that were then used to create relative permeability relationships from MICP data that does not have an associated laboratory-measured relative permeability relationship.

58 GEOSCIENCES↗
DOE OSTI2024

New Matrix Framework to Determine Carbon Storage Technical Viability

Carbon storage is an integral component of reducing CO2 emissions. Research over the past two decades has developed workflows for volume assessments and economic project feasibility, providing necessary and useful tools to progress geologic carbon storage (GCS) projects. These workflows and assessments have focused primarily on determining the in-situ storage resource based on geologic and engineering parameters and do not integrate subsurface characterization with surface conditions, social factors, and environmental factors that may pose a benefit or impediment to the implementation of GCS. Furthermore, the data required to assess the technical viability of GCS are myriad and disparate. There is no current methodology that identifies technical viability criteria and systematically informs how to aggregate these factors for spatial assessments. To address this gap, the National Energy Technology Laboratory has developed a Carbon Storage Technical Viability Approach (CS TVA) Matrix that incorporates a wide variety of factors to inform and accelerate screening for GCS site selection in the United States.

Mulhern, Julia↗