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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 OSTI2022

Assessment of chemo-mechanical impacts of CO 2 sequestration on the caprock formation in Farnsworth oil field, Texas

This study evaluates the chemo-mechanical influence of injected CO 2 on the Morrow B sandstone reservoir and the upper Morrow shale caprock utilizing data from the inverted 5-spot pattern centered on Well 13-10A within the Farnsworth unit (FWU). This study also seeks to evaluate the integrity of the caprock and the long-term CO 2 storage capability of the FWU. The inverted 5-spot pattern was extracted from the field-scale model and tuned with the available field observed data before the modeling work. Two coupled numerical simulation models were utilized to continue the study. First, a coupled hydro-geochemical model was constructed to simulate the dissolution and precipitation of formation minerals by modeling three intra-aqueous and six mineral reactions. In addition, a coupled hydro-geomechanical model was constructed and employed to study the effects of stress changes on the caprock’s porosity, permeability, and ground displacement. The Mohr–Coulomb circle and failure envelope were used to determine caprock failure. In this work, the CO 2 -WAG injection is followed by the historical field-observed strategy. During the forecasting period, a Water Alternating Gas (WAG) injection ratio of 1:3 was utilized with a baseline bottom-hole pressure constraint of 5500 psi for 20 years. A post-injection period of 1000 years was simulated to monitor the CO 2 plume and its effects on the CO 2 storage reservoir and caprock integrity. The simulation results indicated that the impacts of the geochemical reactions on the porosity of the caprock were insignificant as it experienced a decrease of about 0.0003% at the end of the 1000-year post-injection monitoring. On the other hand, the maximum stress-induced porosity change was about a 1.4% increase, resulting in about 4% in permeability change. It was estimated that about 3.3% of the sequestered CO 2 in the formation interacted with the caprock. Despite these petrophysical property alterations and CO 2 interactions in the caprock, the caprock still maintained its elastic properties and was determined to be far from its failure.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2021

Geometrical-Based Generative Adversarial Network to Enhance Digital Rock Image Quality

X-ray microcomputed tomography (micro-CT) is a common tool for the study of porous media structures and properties. High-quality micro-CT data are required to accurately capture pore structures. Acquiring high-quality micro-CT data, however, is not always possible, owing to application limitations and experimental constraints. Therefore, we propose a geometrical-based generative adversarial network (GAN) to rapidly restore noisy micro-CT images to their clean counterparts. The training data and related ground-truth (GT) data are scanned for 7 min and 9.5 h, respectively. To evaluate the performance of the geometrical-based GAN, a 6003 voxel image that has never been used for training is reconstructed and compared with the corresponding GT image. Histogram matching and linear normalization are implemented to adjust the histogram of the reconstructed image to that of the GT image. A watershed-based segmentation method is then applied to delineate pore and solid phases. Lastly, we measure the Minkowski functionals and petrophysical properties, including absolute permeability, pore size distribution, drainage capillary pressure-saturation curve, and imbibition relative permeability, to estimate the physical accuracy of the denoised image. The results show that the proposed geometrical-based GAN can accurately restore noisy micro-CT data. By reducing the scanning time from 9.5 h to 7 min, the expenditure of collecting micro-CT can be decreased significantly. This is particularly important for applications where time-lapse images of a dynamic process are required, high-throughput imaging is necessary for real-time data analysis, or where the quantification of large sample volumes is required.

58 GEOSCIENCES↗
DOE OSTI2024

Jackson, L., Johnson, M.B., Latrach, A., Grimes, D., Martinez, C., and Mclaughlin, J.F., 2024, Multidisciplinary geotechnical data collection, curation, and analysis for conformity with the regulatory framework for geologic carbon storage in Wyoming, USA: Geological Society of America Abstracts with Programs. Vol. 56, No. 5, 2024, doi: 10.1130/abs/2024AM-405024

Title: Multidisciplinary Geotechnical Data Collection, Curation, and Analysis for Conformity with the Regulatory Framework for Geologic Carbon Storage in Wyoming, USA. Text: Construction and operation of wells for geologic sequestration of carbon dioxide necessitate that they are permitted under the Environmental Protection Agency’s Underground Injection Control Class VI requirements. Class VI wells conform to stringent requirements to ensure long-term safety and integrity of the storage site and the protection of Underground Sources of Drinking Water. Entities pursuing Class VI permitting must provide comprehensive geologic site characterization, including regional geologic structure and stratigraphy, aquifer information, reservoir and confining unit geomechanical properties, geochemical analyses, assessment of trapping capacity and mechanisms, and a variety of other of multidisciplinary geotechnical data. The Wyoming Class VI Site Characterization Database Project is focused on developing a geologic site characterization database of geotechnical information, which has been compiled and verified from established, public databases/entities and scientific literature to expedite Class VI permitting in Sweetwater County within the Greater Green River Basin of southern Wyoming. The preliminary suite of compiled data from 14,000 wells includes 8,000 wells with logs and 7,250 wells with formation tops, ~70 wells with core data (e.g., X-Ray diffraction, petrographic, and petrophysical data), ~2,500 water analyses, ~740 seismic events data, and ~520 bottom-hole temperature measurements. Future work on—and stemming from—this project will include new core analyses, calculation and interpolation of subsurface temperature gradients, mechanical earth models, geochemical simulations, storage capacity estimation, stratigraphic column generation and correlation, and construction of subsurface maps. Finally, this work will help to inspire and facilitate subsurface data compilation and curation beyond Sweetwater County, Wyoming.

42 ENGINEERING↗
DOE OSTI2022

A New Model for Simulating the Imbibition of a Wetting-Phase Fluid in a Matrix-Fracture Dual Connectivity System

The imbibition experiment is an effective approach for measuring petrophysical properties of porous media, with many such experiments performed over the past decade. Quite some empirical, analytical, and numerical models have been developed to simulate spontaneous imbibition of the wetting phase fluid into porous media, but limitations still exist. In previous studies, the imbibition process has been considered to give a piston-like displacement or the porous medium modeled as multiply-sized pores linked with bonds; both approaches fail to yield comprehensive results due to their neglect of the presence of irregular fractures or nonuniform flow paths through the matrix. By building a numerical model for simulating laboratory-scale experimental data, we performed imbibition tests on several fractured Barnett Shale samples having fractures either parallel ( P ) or transverse ( T ) to the bedding plane and used MATLAB to build a new numerical model by combining the imbibition process in fractures and the matrix using concepts from percolation theory. The experimental data show that the rocks with P -direction fractures have a more steady increase of imbibition rates than the case of T -direction one. As the shale matrix with low pore connectivity hampers the upward water movement, the imbibition rate of shales with T -direction fractures will decrease suddenly after the bottom layer in contact with water is saturated during the initial period. This wetting phase movement (WPM) model can simulate 3D porous media with 2D fractures. The rate of imbibition by fractured porous media is associated with physical parameters such as porosity and fracture distribution (e.g., the number and angle of fractures). Using Monte Carlo methods, we examined fracture parameters and predicted elapsed time and cumulative water imbibition, for the Barnett Shale samples. The results show that the rate of imbibed water mass is sensitive to the number of fractures directly connected to water source, and the connectivity between two neighboring grid cells is a key parameter for the wetting-front progression. The findings of this study can help to better understand the imbibition process with multiple influencing processes and factors in fractured-matrix rocks. Although the experiments, data simulation, and prediction results are based only on Barnett Shale samples, the model is readily applicable to imbibition tests of other fractured rocks to show the spatial and temporal behavior during a dynamic imbibition process that are not easily captured experimentally.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Numerical Simulations of Carbon Dioxide Storage Efficiency in Heterogeneous Reservoir Models

The U.S. Department of Energy’s National Energy Technology Laboratory (DOE-NETL) has been developing methods and tools (the online Carbon Dioxide Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN) tool) to estimate carbon dioxide (CO2) storage potential in subsurface reservoirs. The CO2 storage efficiency terms are input in the tool to calculate storage potential in targeted reservoirs. In this effort, two CO2 storage efficiency terms were evaluated: volumetric displacement ( E V ) and microscopic displacement ( E d ). The first term deals with efficiency of CO2 propagation into an accessible reservoir volume, while the second term evaluates effectiveness of native fluid displacement with CO2. The interpreted well logs and core sample measurements were applied to create the heterogeneous reservoir models including geostatistical realizations of porosity and intrinsic permeability fields. Supercritical CO2 was injected over the course of 30 years into brine-saturated reservoir models for clastics, limestone, and dolomite lithologies and deltaic fluvial, aeolian, shallow marine, and reef depositional environments by means of varying reservoir parameters and injection scenarios. The reservoir models providing vertically heterogeneous petrophysical properties and designated as “layered reservoir models” (with homogeneous parameters along each layer of the model) were not determined to be a transition between the homogeneous and heterogeneous models in respect to storage efficiency. Another finding shows that high-efficiency factors do not necessarily mean increased CO2 storage; they rather indicate that the available volume and pore space are more fully utilized. The CO2 storage efficiency factors were evaluated dynamically at the select time points using P 10 ‐ P 50 ‐ P 90 percentiles. The results of this study show that the P 10 ‐ P 90 distribution for volumetric efficiency is wider when compared to the microscopic efficiency. It was found that where dominant buoyancy forces drive the plume to the top of a target formation, the volumetric efficiency is low. Tighter sandstone and carbonate formations show prevalence of capillary forces and better utilization of reservoir volume.

Myshakin, Evgeniy M.↗
DOE OSTI2020

Machine learning for geophysical characterization of brittleness: Tuscaloosa Marine Shale case study

Brittleness is one of the most important reservoir properties for unconventional reservoir exploration and production. Better knowledge about the brittleness distribution can help to optimize the hydraulic fracturing operation and lower costs. However, there are very few reliable and effective physical models to predict the spatial distribution of brittleness. We have developed a machine learning-based method to predict subsurface brittleness by using multidiscipline data sets, such as seismic attributes, rock physics, and petrophysics information, which allows us to implement the prediction without using a physical model. The method is applied on a data set from Tuscaloosa Marine Shale, and the predicted rock physics template is close to the calculated value from conventional inverted elastic parameters. Therefore, the proposed method helps determine areas of the reservoir that have optimal geomechanical properties for successful hydraulic fracturing.

Geochemistry & Geophysics↗
DOE OSTI2021

Pore characterization of the Marcellus Shale by nitrogen adsorption and prediction of its gas storage capacity

In a shale gas reservoir, pore characterization is an important factor used to determine gas storage capacity. However, the nanometer (nm)-scale pore system in shale is difficult to explore by traditional optical, scanning electron microscopy, or even nuclear magnetic resonance well logging. We have investigated the pore structure and storage capacity of the Marcellus Shale through integration of petrophysical analysis from laboratory and well-logging data and nitrogen adsorption. The isotherm of Marcellus Shale is a composite isotherm, which has features of type I, type II, and type IV isotherms with type H4 of the hysteresis loop, suggesting slit-like pores developed in the Marcellus Shale. Quantitative analysis of pore volumes from the nitrogen adsorption indicates that density porosity may be more properly used to approximate the shale porosity and estimate the shale gas volume. In addition, the specific surface area, micropore, and mesopore volumes have a positive relationship with the kerogen volume and total organic content (TOC). By using the Langmuir and Brunauer-Emmet-Teller models, the simulated result indicates that the higher adsorbed quantity of the Marcellus Shale could be the result of the increase of micropore volume contributed, by the increase of kerogen or TOC content. The proposed equations rapidly compute TOC, a key parameter to predict gas storage capacity in overmature shale such as the Marcellus Shale.

Geochemistry & Geophysics↗
DOE OSTI2023

Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)

Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy. Objective and Purpose: - Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS system: i) Achieving sufficient injectivity to support high cross-well flow rates ii) Distributing flow evenly across the wellbore and reservoir to maximize heat mining efficiency, ensure sustained heat transfer, and mitigate thermal breakthrough iii) Overcoming the effects of stress heterogeneity, stress shadowing, and variations in natural fracture properties during the stimulation treatment, leading to a more predictable stimulated reservoir volume and offset well placement - The following activities will be performed: i) Design, plan, and execute a multistage plug-and-perf stimulation treatment at a Fervo site with data acquisition and well testing activities aimed at addressing key technical aspects of the issues above ii) Perform data processing and interpretation of field results to translate the results form the Fervo site to a site-specific design at the Utah FORGE site iii) Design, plan, and execute a multistage plug-and-perf stimulation treatment design at the Utah FORGE site Methods and Approach: - Design a detailed data acquisition plan to maximize learning around: i) DFIT testing ii) Petrophysical logging, image logging iii) Permanent DAS/DTS fiber optic monitoring iv) Deep borehole microseismic monitoring v) Shallow borehole induced seismicity monitoring vi) Injection/production testing (RTA analysis, tracer testing) vii) Integrated numerical modeling and production forecasting

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Geophysical and Environmental Monitoring Data, and Subsurface Flow Modelling Results for Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO

This dataset includes geoelectrical monitoring data acquired between October 2021 and November 2022, soil moisture and temperature data, groundwater data obtained from borehole SNIB covering the period from June 2021 to September 2022, and hydrological modelling results. The data were acquired to investigate how variations in bedrock type and topography, and vegetation cover control subsurface flow dynamics. To provide insights into the subsurface flow dynamics and their controls, a monitoring transect was installed at the Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO, measuring the spatio-temporal variations of soil moisture, soil and snow temperature, subsurface electrical resistivity variations, and groundwater dynamics. Field data are organized in a folder structure, with Electrical Resistivity Tomography (ERT) data being provided as one file per measurement, and data of the soil moisture and temperature sensors being provided as text files covering the entire monitoring period. The ‘Locations.csv’ file contains the location of all sensors, given in NAD83 – UTM Zone 13N. ERT monitoring data has been processed to filter data based on reciprocal errors (data with errors > 30% were removed), a linear error model was fitted to each survey, and to ensure a constant set of measurements for time-lapse inversion, filtered data were interpolated and assigned a 100% measurement error. Soil moisture and temperature data were acquired at 15 min intervals, and averaged to provide 1h data. Weather data and borehole data (groundwater depth, conductivity and temperature) were acquired at 30 min intervals, and are provided as daily measurements; all measurements are averaged, except of precipitation values, which are given as daily accumulation. The hydrological model was set up along the ERT monitoring transect, and net infiltration was used as surface boundary condition and derived from the weather data. Four different results are provided, (1) results for a parameterization using hydraulic permeability and porosity as derived from the ERT data through petrophysical relationships, and (2) three simplified model results, using 1 to 3 geological layers above the bedrock. Modelling was performed using PFLOTRAN, and for each model the PFLOTRAN input files are provided. The result files include weekly hydrological modelling results (e.g., saturation, velocities, pressures), as well as the model parameterization. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Multi-Scale Lithofacies and Chemostratigraphic Analysis of Two Middle Devonian Marcellus Shale Wells in Northern West Virginia, USA

The Marcellus Shale Energy and Environmental Laboratory (MSEEL) consists of two project areas within the dry gas producing region of the Marcellus shale play in Monongalia County, West Virginia. MSEEL is a collaborative field project led by West Virginia University, with Northeast Natural Energy LLC, several industrial partners, and sponsored by the US Department of Energy National Energy Technology Laboratory. The study areas are drilled approximately 8.5 miles apart to better understand the vertical and lateral changes in stratigraphy over a short distance. Two vertical pilot wells, MIP-3H and Boggess 17H were drilled in the fall of 2015 and spring of 2019, respectively. Core was recovered from the MIP-3H (API: 47-061-01707-00-00) 112 feet (34m) between depths of 7445 to 7557 feet, and from the Boggess 17H (API: 47-061-01812-00-00) 139 feet (42m) between depths of 7908 and 8012 ft. A full suite of triple combo (gamma ray, neutron, density logs), image logs, and advanced logging tools were run in both wells and calibrated to core analysis. Core analysis includes medical computed tomography (CT) scans, mineralogy and chemostratigraphy determined from handheld X-Ray fluorescence (hhXRF) and X-Ray powder diffraction (XRD) measurements, and determination of total organic content (TOC). Lithofacies were determined at core-scale using traditional core description techniques and medical CT-scan images. Log-scale facies are based on mineralogy and TOC data and developed using petrophysical logging data calibrated to core data (XRD and pyrolysis data). Chemostratigraphic analysis utilized hhXRF data to determine the major and trace element trends in the cores. In the two wells six shale lithofacies were recognized at the core and log scale. Both wells show organic-rich facies (TOC > 6.5%) primarily in the middle and lower Marcellus, with a slight decrease in thickness of this interval in the Boggess 17H. This interval is interpreted as an increase in paleo-productivity (increased Ni, Zn, and V), decreased sedimentation (decreased detrital proxies), and anoxic to euxinic conditions (increased Mo and chalcophile elements). Paleo-redox conditions in both wells are dynamic throughout deposition transitioning between euxinic/anoxic to dysoxic/oxic. This trend is seen through elemental proxies and calcite/pyrite concretion distributions.

03 NATURAL GAS↗
DOE OSTI2020

Offshore CO2 Saline Storage Calculator

The Offshore CO2 Saline Storage Calculator is a data-driven tool that applies the adapted DOE CO2 Methodology to calculate all potential distributions of offshore storage efficiency and resource potential at multiple spatial scales for saline formations. The tailored methodology include accounting for changing CO2 density with the overlying water column and sediment differences in unlithified, porous, and permeable offshore saline formations. The latest release of the tool and a tutorial are available in the tools public GitHub repository. We recommend testing out this application using data from the Petrophysical Well Log Interpretation Dataset, which spans the northern Gulf of Mexico and is available on EDX here: https://edx.netl.doe.gov/dataset/petrophysical-well-log-interpretation-dataset

calculator↗
DOE OSTI2022

Wellington2-32-core

Data from the Wellington 2-32 well described in Schmitt, R.; Paronish, T.; Crandall, D.; Moore, J.; Hasiuk, F.; Potter, N.; Holubnyak, Y. E. Computed Tomography Scanning and Petrophysical Measurements of the Wellington KGS 2-32 Core; DOE/NETL-2022/2874; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2022; p 61. DOI: 10.2172/182XXX99

Carbon Storage↗
DOE OSTI2023

ISGS CarbonSAFE Lively Grove Core

Computed tomography and core logging data from the Lively Grove #1 Well core drilled by the Illinois State Geological Survey in 2021 under DE-FE0031892. Data description can be found in: Crandall, D.; Paronish, T.; Mitchell, N.; Jarvis, K.; Brown, S.; Moore, J.; Gill, M.; Blakley, C.; Okwen, R.; Korose, C.; Carman, C. Computed Tomography Scanning and Petrophysical Measurements of the Lively Grove #1 Well Core; DOE/NETL-2023/3877; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2023; p 61.

CarbonSafe↗
DOE OSTI2024

Illinois Basin Coal Wells

Data described of the Illinois Basin Coal Wells from the Technical Report: Paronish, T.; Crandall, D.; Jarvis, K.; Workman, S.; Pohl, M.; Drosche, J.; Mckisic, T.; McLaughlin P.; Freidberg, J.; Delpomdor F. Computed Tomography Scanning and Petrophysical Measurements of Illinois Basin Coal Wells; DOE/NETL-2024/XXX; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2024; p 59.

Coal↗
DOE OSTI2024

Herren Well - Ohio

CT Data that compliments the Technical Report Series document: Pohl, M.; Paronish, T.; Mitchell, N.; Jarvis, K.; Sharma, M.; Moore, J.; Crandall, D.; Danielsen, E. M.; McDonald, J. Computed Tomography Scanning and Petrophysical Measurements of Oriskany Core Across Eastern Ohio, U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2024

Carbon Storage↗
DOE OSTI2024

Garvin-King Well - Ohio

CT Data that compliments the Technical Report Series Document: Pohl, M.; Paronish, T.; Mitchell, N.; Jarvis, K.; Sharma, M.; Moore, J.; Crandall, D.; Danielsen, E. M.; McDonald, J. Computed Tomography Scanning and Petrophysical Measurements of Oriskany Cores Across Eastern Ohio, US Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2024

Computed Tomography↗
DOE OSTI2024

NY Central System 1 Well - Ohio

CT Data that compliments the Technical Report Series document: Pohl, M.; Paronish, T.; Mitchell, N.; Jarvis, K.; Sharma, M.; Moore, J.; Crandall, D.; Danielsen, E. M.; McDonald, J. Computed Tomography Scanning and Petrophysical Measurements of Oriskany Core Across Eastern Ohio, U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2024

Computed Tomography↗
DOE OSTI2024

Subsurface Energy Systems Mapping Inquiry Tool (MapIT)

The Subsurface Energy Systems Mapping Inquiry Tool (MapIT) is an online web mapping tool designed to help users discover available public-sourced data to facilitate data exploration for subsurface energy exploration and characterization efforts for resource identification (e.g. critical minerals, hydrocarbons, geothermal) as well as injection of geologic sequestration of carbon dioxide (e.g. enhanced oil recovery, saline storage, etc.). Modules within the tool curate data related to geology, faults, fractures, injection and confining zones, hydrologic information, groundwater, groundwater wells, geomechanical and petrophysical data, and geochemical data. User documentation on how to use the tool is also provided. Data have been collected from authoritative national, state, and local sources and made available in this tool. The data is also available as a data catalog and Esri Geodatabase at: https://edx.netl.doe.gov/dataset/mapit-database Disclaimer: There is no guarantee of completeness or appropriateness for individual user’s requirements. Use of this tool is solely at the discretion of the user. See full Federal Disclaimer for further information (https://netl.doe.gov/home/disclaimer). This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. https://www.netl.doe.gov/home/disclaimer

Carbon Sequestration↗