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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Scaling Containment on a Large Centrifuge

Containment science concerns the trapping or leakage of radioactive cavity gases from underground nuclear explosions (UNEs). The most physically relevant data for validation of containment science comes from legacy UNE testing or large field-scale chemical explosions. Field-scale tests can inform on the degree of residual stress imparted to host geology and possible formation of an accompanying gas-containing “stress cage”, for example, as a function of chemical explosion yield. However, field testing can be expensive, difficult to conduct, and challenging to instrument with limitations on data coverage (i.e., the number of boreholes; difficult coring through damage zones). Small-scale laboratory tests are typically simpler to conduct and more thoroughly characterize, but may not include the right scale of containment processes for stress-cage or chimney formation. This report presents the theory and fundamentals of large centrifuge physical modeling, including a history of explosive or similar testing relevant to containment science investigations on centrifuges. Subscale models with embedded chemical explosives in the enhanced gravity of a large centrifuge can represent hundreds of meters of depth and large explosions not otherwise attainable in the laboratory as based on scaling of length, energy, and other processes by the g-factor of the centrifuge (i.e., the number of times larger the centrifugal force is than the gravitational force on the Earth’s surface). The centrifuge uniquely joins the simplicity and exhaustiveness of laboratory-scale characterization with the physics of field-scale processes. This report is part of Sandia National Laboratories’ (SNL’s) effort to prepare for physical modeling with approximately one-meter tall geologic models of stress cage and/or chimney formation on its 29-foot [8.84 m] radius centrifuge with a load capacity of 1.6 million 𝑔-pounds [726 𝑔-ton]. The scaling relationships herein will inform model design decisions and performance requirements for in-flight sensors.

42 ENGINEERING↗
DOE OSTI2014

Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO₂

Geomechanics Technologies has completed a detailed characterization study of the Wilmington Graben offshore Southern California area for large-scale CO₂ storage. This effort has included: an evaluation of existing wells in both State and Federal waters, field acquisition of about 175 km (109 mi) of new seismic data, new well drilling, development of integrated 3D geologic, geomechanics, and fluid flow models for the area. The geologic analysis indicates that more than 796 MMt of storage capacity is available within the Pliocene and Miocene formations in the Graben for midrange geologic estimates (P50). Geomechanical analyses indicate that injection can be conducted without significant risk for surface deformation, induced stresses or fault activation. Numerical analysis of fluid migration indicates that injection into the Pliocene Formation at depths of 1525 m (5000 ft) would lead to undesirable vertical migration of the CO₂ plume. Recent well drilling however, indicates that deeper sand is present at depths exceeding 2135 m (7000 ft), which could be viable for large volume storage. For vertical containment, injection would need to be limited to about 250,000 metric tons per year per well, would need to be placed at depths greater than 7000ft, and would need to be placed in new wells located at least 1 mile from any existing offset wells. As a practical matter, this would likely limit storage operations in the Wilmington Graben to about 1 million tons per year or less. A quantitative risk analysis for the Wilmington Graben indicate that such large scale CO₂ storage in the area would represent higher risk than other similar size projects in the US and overseas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deposition, Diagenesis, and Sequence Stratigraphy of the Pennsylvanian Morrowan and Atokan Intervals at Farnsworth Unit

Farnsworth Field Unit (FWU), a mature oilfield currently undergoing CO2-enhanced oil recovery (EOR) in the northeastern Texas panhandle, is the study area for an extensive project undertaken by the Southwest Regional Partnership on Carbon Sequestration (SWP). SWP is characterizing the field and monitoring and modeling injection and fluid flow processes with the intent of verifying storage of CO2 in a timeframe of 100–1000 years. Collection of a large set of data including logs, core, and 3D geophysical data has allowed us to build a detailed reservoir model that is well-grounded in observations from the field. This paper presents a geological description of the rocks comprising the reservoir that is a target for both oil production and CO2 storage, as well as the overlying units that make up the primary and secondary seals. Core descriptions and petrographic analyses were used to determine depositional setting, general lithofacies, and a diagenetic sequence for reservoir and caprock at FWU. The reservoir is in the Pennsylvanian-aged Morrow B sandstone, an incised valley fluvial deposit that is encased within marine shales. The Morrow B exhibits several lithofacies with distinct appearance as well as petrophysical characteristics. The lithofacies are typical of incised valley fluvial sequences and vary from a relatively coarse conglomerate base to an upper fine sandstone that grades into the overlying marine-dominated shales and mudstone/limestone cyclical sequences of the Thirteen Finger limestone. Observations ranging from field scale (seismic surveys, well logs) to microscopic (mercury porosimetry, petrographic microscopy, microprobe and isotope data) provide a rich set of data on which we have built our geological and reservoir models.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2022

NETL’s Techno-Economic Models for Assessing CO2 Pipeline Transport and Geologic Storage

Presentation at Society of Petroleum Engineers (SPE) Workshop: Future Energy Roadmap – Navigating Through the Energy Transition, held in Galveston, Texas, August 22-23, 2022. The presentation provides an overview of the techno-economic models NETL has developed for assessing performance characteristics and cost drivers for CO2 pipeline transport (FECM/NETL CO2 Transport Cost Model or CO2_T_COM), CO2 saline storage (FECM/NETL CO2 Saline Storage Cost Model or CO2_S_COM), and oil production and CO2 storage using CO2 enhanced oil recovery (EOR) (FE/NETL CO2 Prophet Model or CO2_Prophet and FE/NETL Onshore CO2 EOR Cost Model or CO2_E_COM). A high-level description of each model is presented along with useful outputs that can be generated with each model. These tools can be used individually to evaluate the economic opportunity for specific CCUS components, or they can be used in tandem to assess an integrated CCUS value chain.

Morgan, David↗
DOE OSTI2023

SMART CarbonSAFE Model

The modeling work for this project built upon previous work done for the CarbonSAFE Rocky Mountain Phase I. A geologic and dynamic model was built in Petrel version 2019.3 for the area of the Colorado Plateau near Price, Utah. It is located at the north end of the San Rafael Swell in a natural gas field called Drunkards Wash. The model is 61.5 km east-west and 53 km north to south with 123x106x21 cells, giving a cell dimension of 50x50 m2. The 21 layers in the Z direction are of varying thickness depending on the formation. The Carmel, the seal layer, has 3 layers and is about 200 meters thick around the injection well. The Navajo Sandstone, the principal reservoir, has 5 layers and is about 100 meters thick. The Kayenta has 5 layers and is roughly 50 meters thick and the Wingate, a secondary reservoir, has 5 layers and is 120 meters thick. The base of the model is the Chinle Formation with 3 layers and about 120 meters of thickness..

Carbon Dioxide↗
NASA NTRS1985

The geologic history of quartz-normative and olivine-normative basalts in the vicinity of Hadley Rille (Apollo 15)

The geologic history of the quartz normative (QNB) and olivine normative (ONB) basalt types at Hadley Rille are discussed. A model for the geology of the mare basalts was constructed from a combination of field observations, sample chemistry, sample petrology and personal bias from terrestrial experience. The model proposes that the QNBs are the only mare lava type that is present as outcrop in the area traversed by the astronauts during the Apollo 15 mission. The returned QNB samples formed during a single eruptive phase of the Hadley Rille lava tube system. The ONB lavas are an exotic component transported to the site by a cratering event, or the ONBs are samples excavated from older are bedrock that was partly covered by the QNB lavas.

Grove, T. L.↗
DOE OSTI2025

Deep Learning-based Surrogate Model for Efficient Reservoir Simulation in Large-scale Geological Carbon Storage: Application in IBDP Dataset

This project introduces an advanced deep learning (DL)-based surrogate modeling approach to enhance the efficiency and accuracy of large-scale geological carbon storage (GCS) simulations. Using the Illinois Basin Decatur Project (IBDP) dataset as training data, the study employs a residual U-Net architecture to predict critical state variables such as pressure and CO₂ saturation, as well as CO₂ plume migration. By incorporating key geological parameters (e.g., porosity, permeability, and rock facies) and physics-informed inputs like the diffusive time of flight and time step, the DL model effectively reduces computational complexity while maintaining robust physical constraints. Compared to traditional simulators like Eclipse, the DL model achieves remarkable accuracy, with a root mean square error (RMSE) of 1.57 psi for pressure and 0.007 for saturation, and dramatically reduces computational time from hours to just 69.9 seconds for 50-step simulations. These results demonstrate the potential of innovative DL methodologies to improve the predictivity and operational efficiency of GCS simulations, providing a reliable foundation for decision-making in CCS operations. Supported by the SMART initiative, this project underscores the success of leveraging computational innovations to advance CCS technologies.

advanced deep learning↗
DOE OSTI2019

Coupled Hydrodynamic-Geomechanical Modelling of CO2-WAG Field Development at Farnsworth Unit: A Case Study

Abstract The SWP project is located in a mature waterflood undergoing conversion to CO2-WAG operations at Farnsworth, Texas, USA. Utilized CO2 is anthropogenic, sourced from a fertilizer and an ethanol plant. Major project goals are optimizing the storage/production balance, ensuring storage permanence, and developing best practices for CCUS. This paper provides a review of work performed toward development of a 3D coupled Mechanical Earth Model (MEM) for use in assessment of caprock integrity, fault reactivation potential, and evaluation of stress dependent permeability in reservoir forecasting. Mechanical property estimates computed from geophysical logs at selected wellbores were integrated with 3D seismic elastic inversion products to create a 3D "static" mechanical property model sharing the same geological framework as the existing reservoir simulation model including 3 major faults. Stresses in the MEM were initialized from wellbore stress estimates and reservoir simulation pore pressures. One way and two way coupled simulations were performed using a compositional hydrodynamic flow model and geomechanical solvers. Coupled simulations were performed on history matched primary, secondary (waterflood), and tertiary (CO2 WAG) recovery periods, as well as an optimized WAG prediction period. These simulations suggest that the field has been operating at conditions which are not conducive to either caprock failure or fault reactivation. Two way coupled simulations were performed in which permeability was periodically updated as a function of volumetric strain using the Kozeny-Carmen porosity-permeability relationship. These simulations illustrate the importance of frequent permeability updating when recovery scenarios result in large pressure changes such as in field re-pressurization through waterflood after a long primary depletion recovery period. Conversely, production forecasting results are less sensitive to permeability update frequency when pressure cycles are short and shallow as in WAG cycles. This paper describes initial work on development of a mechanical earth model for use in assessment of geomechanical risks associated with CCUS operations at FWU. The emphasis of this work is on integration of available geomechanical data for creation of the static mechanical property model. Preliminary coupled hydro-mechanical simulations are presented to illustrate some of the key diagnostic output from coupled simulations which will be used in later work for in depth evaluation of specific risk factors such as induced seismicity and caprock integrity.

02 PETROLEUM↗
DOE OSTI2021

Skin factor and potential formation damage from chemical and mechanical processes in a naturally fractured carbonate aquifer with implications to CO 2 sequestration

Here, in this study, we investigate formation damage due to acidization and water injection tests into the naturally fractured carbonate Middle Duperow Formation at Kevin Dome, Montana, potentially diminishing the chance of a future successful Geological Carbon Sequestration (GCS) project. Multiple well-test analytical models, correlated with core description and lithology data, are used to determine flow behavior and communication between the water injection interval and surrounding formations. An improved three-dimensional (3D) geologic model with dual-continuum matrix and fracture properties is constructed based on most recent seismic, core, and water sample measurements. Brine injection is simulated to verify the interpretation from the analytical models, followed by CO 2 injection simulation. Geochemical calculations are performed to understand the in-situ processes that led to formation damage. Our findings suggest: (1) there are two possible scenarios that could lead to a positive total effective skin factor and permeability decline: partial penetration and formation damage; (2) analytical models indicate a positive total skin factor, contradicting results of a previous study suggesting that the well was mildly stimulated; (3) numerical simulation supports the formation damage hypothesis by matching the pressure buildup observed during the latter two brine injection tests; (4) several mechanical and chemical processes may have occurred during injection to clog the matrix/fracture system: anhydrite fines migration and/or calcite precipitation. We then make preventative suggestions for future GCS projects into carbonate reservoirs and remediation recommendations for GCS operation at the Kevin Dome.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Effect of medium permeability anisotropy on the morphological evolution of two non-uniformities in a geochemical dissolution system

The morphological evolutions of chemical dissolution fronts have attracted increasing interest in the field of the geological sciences and in industrial applications. Extensive research based on numerical simulations has been conducted to understand how various mechanisms and processes influence the morphological evolution of chemical dissolution fronts within geological media. Most researchers in previous studies have assumed the medium permeability to be isotropic for developing numerical models, despite isotropic geological media being uncommon in the real world. This study investigates the effect of medium permeability anisotropy on the morphological evolutions of two non-uniformities with higher permeability in a geochemical dissolution system. A series of numerical simulations are performed to evaluate the effect of medium permeability anisotropy on the morphological evolution of a chemical dissolution front. The simulation results indicate that the patterns of the dissolution reaction front are substantially affected by medium permeability anisotropy. An increase in the permeability anisotropy ratio, which is defined as the ratio of the permeability in the transverse direction to that in the longitudinal direction, enhances the dominance of the flow-focusing effect over the stabilizing or merging effect induced by diffusion/dispersion mechanism. Therefore, an increase in the permeability anisotropy ratio can increase the fingering length of the dissolution front or cause the dissolution front to have a more unstable pattern. By contrast, a reduction in the permeability anisotropy ratio will weaken the flow-focusing effect, thereby reducing the fingering length of the dissolution front or changing the front morphology such that it has a more stable status. The effect of the permeability anisotropy ratio on the morphological evolution tends to decrease when the Zhao number (negative dimensionless upstream pressure gradient) of the system increases. The consideration of medium permeability anisotropy in the geochemical dissolution model renders the simulation of the morphological evolutions of dissolution reaction fronts more realistic.

58 GEOSCIENCES↗
DOE OSTI2026

Denudation, solute export, landscape evolution modeling, and geographic information system data for the East River watershed, Colorado, USA (2020-2024)

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of lithologic controls on denudation, solute export, carbon-scaling relationships, and transient landscape evolution in the East River watershed near Crested Butte, Colorado, USA. The package includes GIS layers used to produce the Figure 2 map, including drainage, hillshade, lithology, sample locations, and basin polygons, together with comma-separated value (CSV) tables and matching CSV data dictionaries. One group of tables reports sample-level and catchment-level information for river-sediment samples analyzed for in situ-produced cosmogenic beryllium-10 (10Be), including sample names, outlet elevations, geographic coordinates, upstream drainage area, rock-type classes, production-rate scaling scheme, analyzed nuclide, catchment-averaged denudation rates, and associated lower and upper analytical uncertainties. Sample and catchment attributes provide the basis for comparing denudation rates across intrusive, shale, sedimentary, and mixed-lithology settings. A second group of tables reports supporting information for landscape-evolution modeling and the mapped geologic framework of the study area. Included files list parameter values and definitions for the two-phase landscape-evolution simulations, summarize full-domain model erosion fluxes and topographic metrics for different simulation configurations, provide a fixed-area carbon-model scaling table, and summarize mapped geologic units within the East River study domain, including geologic code, formation name, lithologic description, mapped area, and lithologic class grouping. Model outputs and geologic summaries support interpretation of transient landscape behavior and its relation to the mapped distribution of shale, intrusive, sedimentary, and surficial units. A third group of tables reports hydrologic and hydrochemical information used to quantify dissolved export from the watershed. Included files provide site-level values for drainage area, mean annual solute export, standard error of annual export, area-normalized solute yield, and equivalent weathering rate for five East River monitoring sites, along with metadata describing the number, sampling cadence, and date range of discharge records and partial and full total dissolved solids observations used in the solute-yield analyses. The package also contains a supplementary daily ion-load time series with daily mean discharge, discharge observation counts, dissolved concentrations, and daily loads for calcium, magnesium, sodium, potassium, chloride, sulfate, nitrate, fluoride, dissolved silica, charge-balance bicarbonate, and total dissolved solids. The package contains GIS files, comma-separated value files (.csv), CSV data dictionaries, a file-level metadata table, a package-tree text file, and a readme text file.

10Be↗
DOE OSTI2015

sRecovery Act: Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO 2 Storage

This study focuses on evaluating the feasibility and suitability of using the Jurassic/Triassic (J/TR) sediments of the South Georgia Rift basin (SGR) for CO 2 storage in southern South Carolina and southern Georgia The SGR basin in South Carolina (SC), prior to this project, was one of the least understood rift basin along the east coast of the U.S. In the SC part of the basin there was only one well (Norris Lightsey #1) the penetrated into J/TR. Because of the scarcity of data, a scaled approach used to evaluate the feasibility of storing CO 2 in the SGR basin. In the SGR basin, 240 km (~149 mi) of 2-D seismic and 2.6 km2 3-D (1 mi2) seismic data was collected, process, and interpreted in SC. In southern Georgia 81.3 km (~50.5 mi) consisting of two 2-D seismic lines were acquired, process, and interpreted. Seismic analysis revealed that the SGR basin in SC has had a very complex structural history resulting the J/TR section being highly faulted. The seismic data is southern Georgia suggest SGR basin has not gone through a complex structural history as the study area in SC. The project drilled one characterization borehole (Rizer # 1) in SC. The Rizer #1 was drilled but due to geologic problems, the project team was only able to drill to 1890 meters (6200 feet) instead of the proposed final depth 2744 meters (9002 feet). The drilling goals outlined in the original scope of work were not met. The project was only able to obtain 18 meters (59 feet) of conventional core and 106 rotary sidewall cores. All the conventional core and sidewall cores were in sandstone. We were unable to core any potential igneous caprock. Petrographic analysis of the conventional core and sidewall cores determined that the average porosity of the sedimentary material was 3.4% and the average permeability was 0.065 millidarcy. Compaction and diagenetic studies of the samples determined there would not be any porosity or permeability at depth in SC. In Georgia there appears to be porosity in the J/TR section based on neutron log porosity values. The only zones in Rizer #1 that appear to be porous were fractured diabase units where saline formation water was flowing into the borehole. Two geocellular models were created for the SC and GA study area. Flow simulation modeling was performed on the SC data set. The injection simulation used the newly acquired basin data as well as the Petrel 3-D geologic model that included geologic structure. Due to the new basin findings as a result of the newly acquired data, during phase two of the modeling the diabase unit was used as reservoir and the sandstone units were used as caprock. Conclusion are: 1) the SGR basin is composed of numerous sub-basins, 2) this study only looked at portions of two sub-basins, 3) in SC, 30 million tonnes of CO 2 can be injected into the diabase units if the fracture network is continuous through the units, 4) due to the severity of the faulting there is no way of assuring the injected CO 2 will not migrate upward into the overlying Coastal Plain aquifers, 5) in Georgia there appears to porous zones in the J/TR sandstones, 6) as in SC there is faulting in the sub-basin and the seismic suggest the faulting extends upward into the Coastal Plain making that area not suitable for CO 2 sequestration, 7) the complex faulting observed at both study areas appear to be associated with transfer fault zones (Heffner 2013), if sub-basins in the Georgia portion of the SGR basin can be located that are far away from the transfer fault zones there is a strong possibility of sequestering CO 2 in these areas, and 9) the SGR basin covers area in three states and this project only studied two small areas so there is enormous potential for CO 2 sequestration in other portions the basin and further research needs to be done to find these areas.

58 GEOSCIENCES↗
DOE OSTI2015

Experimental determination of lead carbonate solubility at high ionic strengths: A Pitzer model description

In this article, solubility measurements of lead carbonate, PbCO 3 (cr), cerussite, as a function of total ionic strengths are conducted in the mixtures of NaCl and NaHCO 3 up to I = 1.2 mol•kg –1 and in the mixtures of NaHCO 3 and Na 2 CO 3 up to I = 5.2 mol•kg –1 , at room temperature (22.5 ± 0.5 °C). The solubility constant (log K sp ) for cerussite, PbCO 3 (cr) = Pb 2+ + CO 3 2- was determined as –13.76 ± 0.15 (2σ) with a set of Pitzer parameters describing the specific interactions of PbCO 3 (aq), Pb(CO 3 ) 2 2- , and Pb(CO 3 )Cl – with the bulk-supporting electrolytes, based on the Pitzer model. The model developed in this work can reproduce the experimental results including model-independent solubility values from the literature over a wide range of ionic strengths with satisfactory accuracy. The model is expected to find applications in numerous fields, including the accurate description of chemical behavior of lead in geological repositories, the modeling of formation of oxidized Pb–Zn ore deposits, and the environmental remediation of lead contamination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Combining multiple lower-fidelity models for emulating complex model responses for CCS environmental risk assessment

Numerical modeling is essential to support natural resource management and environmental policy-making. In the context of CO 2 geological sequestration, these models are indispensible parts of risk assessment tools. However, because of increasing complexity, modern numerical models require a great computational effort, which in some cases may be infeasible. An increasingly popular approach to overcome computational limitations is the use of surrogate models. This paper presents a new surrogate modeling approach to reduce the computational cost of running a complex, high-fidelity model. The approach is based on the simplification the high-fidelity model into computationally efficient, lower-fidelity models and on linking them with a mathematical function (linking function) that addresses the discrepancies between outputs from models with different levels of fidelity. The resulting linking function model, which can be developed with small computational effort, can be efficiently used in numerical applications where multiple runs of the original high-fidelity model are required, such as for uncertainty quantification or sensitivity analysis. The proposed approach was then applied to the development of a reduced order model for the prediction of groundwater quality impacts from CO 2 and brine leakage for the National Risk Assessment Partnership (NRAP) project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Real-time deep-learning inversion of seismic full waveform data for CO 2 saturation and uncertainty in geological carbon storage monitoring

Deep-learning inversion has recently drawn attention in geological carbon storage research due to its potential of imaging and monitoring carbon storage in real time, significantly improving efficiency and safety of carbon storage operations. We present a deep-learning full waveform inversion method that after the neural network has been trained can image CO 2 saturation and its uncertainty in real time. Our deep-learning inversion method is based on the U-Net architecture with the neural network trained on pairs of synthetic seismic data and CO 2 saturation models. Accordingly, our training establishes a mapping relationship between seismic data and CO 2 saturation models and once fully trained directly estimates CO 2 saturation as a function of subsurface location. We further quantify uncertainties of CO 2 saturation estimates using the Monte Carlo dropout method and a bootstrap aggregating method. For this proof-of-concept study, the CO 2 training models and data are derived from the Kimberlina 1.2 model, a hypothetical 3D geological carbon storage model that is constructed based on various geological and hydrological data from the Southern San Joaquin Basin, California. We perform deep-learning inversion experiments using noise-free and noisy training and test data sets and compare the results. Our modelling experiments show that (1) the deep-learning inversion can estimate 2D distributions of CO 2 fairly well even in the presence of Gaussian random noise and (2) both CO 2 saturation imaging and uncertainty quantification can be done in real time. Our results suggest that the deep-learning inversion method can serve as a robust real-time monitoring tool for geological carbon storage and/or other time-varying reservoir/aquifer properties that result from injection, extraction, and/or other subsurface transport phenomena.

58 GEOSCIENCES↗
NASA NTRS2003

Results of the Workshop on Impact Cratering: Bridging the Gap Between Modeling and Observations

On February 7-9,2003, approximately 60 scientists gathered at the Lunar and Planetary Institute in Houston, Texas, for a workshop devoted to improving knowledge of the impact cratering process. We (co-conveners Elisabetta Pierazzo and Robert Herrick) both focus research efforts on studying the impact cratering process, but the former specializes in numerical modeling while the latter draws inferences from observations of planetary craters. Significant work has been done in several key areas of impact studies over the past several years, but in many respects there seem to be a disconnect between the groups employing different approaches, in particular modeling versus observations. The goal in convening this workshop was to bring together these disparate groups to have an open dialogue for the purposes of answering outstanding questions about the impact process and setting future research directions. We were successful in getting participation from most of the major research groups studying the impact process. Participants gathered from five continents with research specialties ranging from numerical modeling to field geology, and from small-scale experimentation and geochemical sample analysis to seismology and remote sensing.With the assistance of the scientific advisory committee (Bevan French, Kevin Housen, Bill McKinnon, Jay Melosh, and Mike Zolensky), the workshop was divided into a series of sessions devoted to different aspects of the cratering process. Each session was opened by two invited t a b , one given by a specialist in numerical or experimental modeling approaches, and the other by a specialist in geological, geophysical, or geochemical observations. Shorter invited and contributed talks filled out the sessions, which were then concluded with an open discussion time. All modelers were requested to address the question of what observations would better constrain their models, and all observationists were requested to discuss how their observations can constrain modeling efforts.

Herrick, Robert↗
DOE OSTI2024

Curating Carbon Storage Data for Reuse: Enabling Research and Modeling from Earth’s Surface to Subsurface

The volume of public geologic carbon storage (GCS) data resources has continued to increase in recent years as the result of an increase in funding from government, industry, and academia towards national, basin, regional and field scale studies to ensure carbon capture and storage becomes a commercially viable operation. Despite the increasing volume of data, GCS data applied towards analyses such as geologic, cost, and risk modeling continues to be multi-sourced and often disparate in nature, published across government agencies, websites, data repositories and buried in derivative reports and documents. Much of the time preparing for an analysis and derivative product development is spent collecting, aggregating, transforming and preparing input data. There have been significant efforts within the DOE National Energy Technology Laboratory’s Carbon Storage Program to optimize multi-source, multi-scale subsurface geologic data curation and aggregation to support data discovery, interoperability, and reuse. Methods include the use of artificial intelligence, machine learning, and data science techniques. This talk will discuss the workflows, best practices, and processes developed to support the aggregation and curation of data through the whole system – surface to subsurface data - that support multi-scale, multi-purpose analysis for carbon storage research.

Morkner, Paige↗