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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Generative network-based approaches to generate stochastic realizations

Generative Adversarial Network (GAN) – based models have been successfully applied in generating different geological models in the literature. However, it is still challenging to use GAN to generate geological realizations with extremely sparse conditioning data (e.g. several well data), which may be regarded as local noise by GAN during the training process. In this work, we propose a novel conditional Generative Adversarial Neural Operator (cGANO) to tackle this challenge. In cGANO, the mapping between conditioning data and output is established through the U-shaped neural operators (UNO), which better preserves local information. Another advantage of using UNO comes from its grid-independent property, which makes the generation of downscaling stochastic geologic realizations possible. We tested the model performance on the IBDP geostatistical dataset with 100 realizations.

58 GEOSCIENCES↗
DOE OSTI2017

Cathodoluminescence for the 21st century: Learning more from light

Cathodoluminescence (CL) is the emission of light from a material in response to excitation by incident electrons. The technique has had significant impact in the characterization of semiconductors, minerals, ceramics, and many nanostructured materials. Since 2010, there have been a number of innovative developments that have revolutionized and expanded the information that can be gained from CL and broadened the areas of application. While the primary historical application of CL was for spatial mapping of luminescence variations (e.g., imaging dark line defects in semiconductor lasers or providing high resolution imaging of compositional variations in geological materials), new ways to collect and analyze the emitted light have expanded the science impact of CL, particularly at the intersection of materials science and nanotechnology. Current developments include (1) angular and polarized CL, (2) advances in time resolved CL, (3) far-field and near-field transport imaging that enable drift and diffusion information to be obtained through real space imaging, (4) increasing use of statistical analyses for the study of grain boundaries and interfaces, (5) 3D CL including tomography and combined work utilizing dual beam systems with CL, and (6) combined STEM/CL measurements that are reaching new levels of resolution and advancing single photon spectroscopy. This focused review will first summarize the fundamentals and then briefly describe the state-of-the-art in conventional CL imaging and spectroscopy. We also review these recent novel experimental approaches that enable added insight and information, providing a range of examples from nanophotonics, photovoltaics, plasmonics, and studies of individual defects and grain boundaries.

14 SOLAR ENERGY↗
DOE OSTI2015

Testing Novel CR-39 Detector Deployment System for Identification of Subsurface Fractures, Soda Springs, ID

The Environmental Protection Agency (EPA) has teamed with Battelle Energy Alliance, LLC (BEA) at Idaho National Laboratory (INL) to facilitate further testing of geologic-fracture-identification methodology at a field site near the Monsanto Superfund Site located in Soda Springs, Idaho. INL has the necessary testing and technological expertise to perform this work. Battelle Memorial Institute (BMI) has engaged INL to perform this work through a Work for Others (WFO) Agreement. This study continues a multi-year collaborative effort between INL and EPA to test the efficacy of using field deployed Cr-39 radon in soil portals. This research enables identification of active fractures capable of transporting contaminants at sites where fractures are suspected pathways into the subsurface. Current state of the art methods for mapping fracture networks are exceedingly expensive and notoriously inaccurate. The proposed WFO will evaluate the applicability of using cheap, readily available, passive radon detectors to identify conductive geologic structures (i.e. fractures, and fracture networks) in the subsurface that control the transport of contaminants at fracture-dominated sites. The proposed WFO utilizes proven off-the-shelf technology in the form of CR-39 radon detectors, which have been widely deployed to detect radon levels in homes and businesses. In an existing collaborative EPA/INL study outside of this workscope, CR-39 detectors are being utilized to determine the location of active transport fractures in a fractured granitic upland adjacent to a landfill site at the Fort Devens, MA that EPA-designated as National Priorities List (NPL) site. The innovative concept of using an easily deployed port that allows the CR-39 to measure the Rn-222 in the soil or alluvium above the fractured rock, while restricting atmospheric Rn-222 and soil sourced Ra from contaminating the detector is unique to INL and EPA approach previously developed. By deploying a series of these inexpensive detector-casing combinations statistical samples of the Rn-222 flux can be measured, elucidating the most communicative fractures (i.e. fractures that are actively transporting water and gasses). The Rn-222 measurements can then be used as an input to create a more accurate conceptual model to be used for transport modeling and related cleanup activities. If the team’s approach is demonstrated to be applicable to a wide variety of rock types and soil conditions it might potentially offer significant cost saving without a reduction in data quality at Monsanto Superfund and other sites underlain by fracture-dominated bedrock.

58 GEOSCIENCES↗
DOE OSTI2024

Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analyses

This presentation demonstrates a spatial analysis workflow to assess data availability for the many components of geologic carbon storage technical viability. The workflow relies upon a knowledge-data framework that links the different components of GCS technical viability to the data types needed for evaluation. Using this contextual information, a combination of data science methods (e.g., natural language processing) and spatial analyses are applied to identify areas where sufficient data exists for a given component. The results are aggregated into maps illustrating data density and spatial gaps across all technical viability factors and data categories, as well as the individual component and category level for a more nuanced understanding. Presented at the Geological Society of America Connects 2024 Annual Meeting in Anaheim, California, 22-25 September 2024.

Creason, Christopher↗
DOE OSTI2014

3D mapping of water in oolithic limestone at atmospheric and vacuum saturation using X-ray micro-CT differential imaging

Determining the distribution of fluids in porous sedimentary rocks is of great importance in many geological fields. However, this is not straightforward, especially in the case of complex sedimentary rocks like limestone, where a multidisciplinary approach is often needed to capture its broad, multimodal pore size distribution and complex pore geometries. This paper focuses on the porosity and fluid distribution in two varieties of Massangis limestone, a widely used natural building stone from the southeast part of the Paris basin (France). The Massangis limestone shows locally varying post-depositional alterations, resulting in different types of pore networks and very different water distributions within the limestone. Traditional techniques for characterizing the porosity and pore size distribution are compared with state-of-the-art neutron radiography and X-ray computed microtomography to visualize the distribution of water inside the limestone at different imbibition conditions. X-ray computed microtomography images have the great advantage to non-destructively visualize and analyze the pore space inside of a rock, but are often limited to the larger macropores in the rock due to resolution limitations. In this paper, differential imaging is successfully applied to the X-ray computed microtomography images to obtain sub-resolution information about fluid occupancy and to map the fluid distribution in three dimensions inside the scanned limestone samples. The detailed study of the pore space with differential imaging allows understanding the difference in the water uptake behavior of the limestone, a primary factor that affects the weathering of the rock. - Highlights: • The water distribution in a limestone was visualized in 3D with micro-CT. • Differential imaging allowed to map both macro and microporous zones in the rock. • The 3D study of the pore space clarified the difference in water uptake behavior. • Trapped air is visualized in the moldic macropores at atmospheric saturation.

36 MATERIALS SCIENCE↗
DOE OSTI2015

State Geological Survey Contributions to the National Geothermal Data System (Final Technical Report)

The State Geological Survey Contributions to the National Geothermal Data System project is built on the work of the project managed by Boise State University to design and build the National Geothermal Data System, by deploying it nationwide and populating it with data principally from State Geological Surveys through collaboration with the Association of American State Geologists (AASG). This project subsequently incorporated the results of the design-build and other DOE-funded projects in support of the NGDS. The NGDS (www.geothermaldata.org) provides free open access to millions of data records, images, maps, and reports, sharing relevant geoscience, production, and land use data in 30+ categories to propel geothermal development and production in the U.S. NGDS currently serves information gathered from hundreds of the U.S. Department of Energy sponsored development and research projects and geologic data feeds from 60+ data providers throughout all 50 states. These data are relevant to geothermal energy exploration and development, but also have broad applicability in other areas including natural resources (e.g., energy, minerals, water), natural hazards, and land use and management.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

A deep learning-based direct forecasting of CO 2 plume migration

Accurate and timely forecasts of CO 2 plume evolution in geological reservoirs are crucial for CO 2 migration detection, leakage risk assessment, and operation decision support. Conventional forecasting usually adopts a two-step strategy, first calibrating reservoir model parameters against observations using iterative inverse modeling (or history matching) and then applying the calibrated model for predictions. This method impedes real-time forecasts due to the heavy computational demand in inverse modeling and may suffer from poor prediction accuracy because of the limited observation data. In this work, we propose a deep learning-based latent space mapping framework to forecast CO 2 plume migration directly by avoiding the inverse modeling. We first use the convolutional autoencoder to map the high-dimensional complex plume extents onto low-dimensional latent space. Next, we use neural networks to learn the relationship between the observation variables and the prediction latent variables. And then for given observation data, we infer the prediction values directly. This one-step direct forecasting is computationally efficient which requires a few number of parallelizable reservoir simulations and it can provide accurate predictions with limited observations by learning the observation-prediction relationship in the reduced dimension. Therefore, our proposed method enables an in-time forecast of dynamic CO 2 plume distributions. In this work, we demonstrate the effectiveness and accuracy of our method in predicting the CO 2 plume migration using four metrics such as plume area, centroid movement distance, and plume spreading in the primary and secondary directions. And the spatio-temporal evolution patterns of plume migration under diverse geological complexities are also accurately quantified.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Streamlining Stakeholder Data Accessibility Utilizing Web-Based GIS Capabilities - 18672

Environmental data is often complex, and it can be difficult to provide proper context to fully understand and comprehensively analyze the data. One tool identified to better present complicated data is the use of web-based Geographic Information Systems (GIS). Web-based GIS provides much-needed visual context to the complex data collected at Los Alamos National Laboratory (LANL). By overlaying environmental data atop relevant geographical features, such as topography, surface or subsurface geology, hydrogeological features, buildings, roads, and technical areas, LANL's diverse group of stakeholders are better able to understand environmental data collected at the LANL site within the framework of the surrounding geography. Since 2012, Los Alamos has utilized a web-based GIS module in the Intellus New Mexico data-sharing web site. This web site provides unfettered public access to LANL and New Mexico Environment Department (NMED) - Department of Energy (DOE) Oversight Bureau environmental data. Through the past five years of real world experience, LANL identified areas where questions and confusion arose, particularly for those not directly associated with the site's environmental cleanup mission. In order to query the millions of records in Intellus in a meaningful way, users had to have substantial knowledge of the data organization and nomenclature ahead of time. While this was not a challenge for LANL and NMED environmental scientists, it proved to be a substantial barrier for members of the general public to utilize Intellus. In 2017, LANL initiated an Intellus redesign with the goal of deconstructing the type of questions people asked and identifying the types of user personas accessing the site to engineer a simpler path to desired data sets. Greatly simplified click paths ('Quick Paths') were created that walk the user through the basics with a minimum of jargon and a strong reliance on mapping results for easy visualization. The improved mapping was enabled by an upgraded online GIS functionality that allowed LANL to easily integrate their own base-maps to provide users the most up to date views of their data. The integrated Intellus GIS was enhanced to assimilate with LANL's dynamic base maps and site information in relation to data collection activities, to avoid outdated presentations. A simplified user interface (UI) was added and easier data querying was designed. A more robust visual presentation was created that allowed better viewing of spatial data. All data queries in the new simplified 'Quick Path' give the users the option to map the results and save their results to their optional accounts. This brings the power of GIS visualization to all users without the need for GIS knowledge or extensive training. By integrating with Esri{sup R} technologies, base-map layers in ArcGIS Online{sup R} can be updated by LANL or other data providers at any time and reflected immediately in the Intellus mapping application called GIS+ 1. Users can even load additional map layers to GIS+ that contain their own spatial data or information shared from over a million users on ArcGIS Online{sup R}, such as ecological information from the Fish and Wildlife Service, or geology layers from the USGS. The results from the improved quick path search in Intellus can be viewed in GIS+ and analyzed using Esri's{sup R} Smart Mapping technology, which makes it easy to classify results with its visual representation of the results in an interactive histogram, where sliders can be dragged to look at various intervals for each color range for that query. With enhanced GIS+, Los Alamos National Laboratory is able to observe improve Stakeholder engagement and positive Stakeholder interactions within its public environmental database, Intellus New Mexico. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model

Environmental management of an area describes a policy for its systematic and sustainable environmental protection. In the present study, regional environmental vulnerability assessment in Hirakud command area of Odisha, India is envisaged based on Grey Analytic Hierarchy Process method (Grey–AHP) using integrated remote sensing (RS) and geographic information system (GIS) techniques. Grey–AHP combines the advantages of classical analytic hierarchy process (AHP) and grey clustering method for accurate estimation of weight coefficients. It is a new method for environmental vulnerability assessment. Environmental vulnerability index (EVI) uses natural, environmental and human impact related factors, e.g., soil, geology, elevation, slope, rainfall, temperature, wind speed, normalized difference vegetation index, drainage density, crop intensity, agricultural DRASTIC value, population density and road density. EVI map has been classified into four environmental vulnerability zones (EVZs) namely: ‘low’, ‘moderate’ ‘high’, and ‘extreme’ encompassing 17.87%, 44.44%, 27.81% and 9.88% of the study area, respectively. EVI map indicates that the northern part of the study area is more vulnerable from an environmental point of view. EVI map shows close correlation with elevation. Effectiveness of the zone classification is evaluated by using grey clustering method. General effectiveness is in between “better” and “common classes”. This analysis demonstrates the potential applicability of the methodology. - Highlights: • Environmental vulnerability zone identification based on Grey Analytic Hierarchy Process (AHP) • The effectiveness evaluation by means of a grey clustering method with support from AHP • Use of grey approach eliminates the excessive dependency on the experience of experts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Mathematical approaches in deriving hydrocarbons expressions from seismic data

Defining and understanding hydrocarbon expressions in seismic expression is main concern of geoscientists in oil and gas exploration and production. Over the last decades several mathematical approaches have been developed in this regard. Most of approaches have addressed information in amplitude of seismic data. Recently, more attention has been drawn towards frequency related information in order to extract frequency behaviors of hydrocarbons bearing sediments. Spectrally decomposing seismic data into individual frequencies found to be an excellent tool for investigating geological formations and their pore fluids. To accomplish this, several mathematical approaches have been invoked. Continuous wavelet transform and Short Time Window Fourier transform are widely used techniques for this purpose. This paper gives an overview of some widely used mathematical technique in hydrocarbon reservoir detection and mapping. This is followed by an application on real data from Boonsville field.

58 GEOSCIENCES↗
DOE OSTI2026

Uinta Basin CarbonSAFE II: Storage Complex Feasibility (Final Report)

The primary objective of this CarbonSAFE Phase II project was to establish the technical and commercial feasibility of a commercial-scale CO 2 geological storage complex for Deseret Power Electric Cooperative Bonanza Power Plant and other CO 2 sources in the northeast Uinta Basin, Utah, with the goal to securely store at least 50 million metric tons of captured CO 2 and accelerate CO 2 capture, utilization, and storage (CCUS) deployment. The project team established high-potential technical and commercial feasibility for a storage site within the east Uinta Basin (Utah), in the Cretaceous sandstones (Frontier, Dakota, and Buckhorn), Entrada Sandstone, Nugget Sandstone, and/or Weber Sandstone southwest of the Bonanza coal-fired power plant. This project collected and analyzed state-of-the-art data to characterize the storage complex consistent with Environmental Protection Agency (EPA) permitting standards. The team conducted extensive analog studies, outcrop mapping, and data sampling, which largely contributed to understanding the subsurface lithology and facies. Existing data were obtained and assessed from Utah Division of Oil, Gas, and Mining (DOGM), Utah Geological Survey (UGS), Colorado Geological Survey (CGS), U.S. Geological Survey (USGS), and EPA. These data were analyzed using state-of-the-art CCUS technologies for Societal Considerations, Site Characterization, Modeling and Simulations, Risk Assessment, Management and Monitoring, potential Underground Injection Control (UIC) Class VI Well Permitting, and Technical/Economic Feasibility. Through these high-resolution data collection and feasibility studies, this project was expected to provide a reference for initiating Underground Injection Control (UIC) and other commercial-scale geological storage permitting processes in the Western United States, ultimately contributing to the nation's decarbonization goals through low-risk, cost-effective commercial-scale carbon capture, utilization, and storage (CCUS) projects.

42 ENGINEERING↗
DOE OSTI2016

Space geodetic monitoring of engineered structures: The ongoing destabilization of the Mosul dam, Iraq

We present a detailed survey of the ongoing destabilization process of the Mosul dam. The dam is located on the Tigris river and is the biggest hydraulic structure in Iraq. From a geological point of view the dam foundation is poor due to a site geology formed by alternating strata of highly soluble materials including gypsum, anhydrite, marl and limestone. Here we present the first multi-sensor cumulative deformation map for the dam generated from space-based interferometric synthetic aperture radar measurements from the Italian constellation COSMO-SkyMed and the European sensor Sentinel-1a over the period 2014–2016 that we compare to an older dataset spanning 2004–2010 acquired with the European Envisat satellite. We found that deformation was rapid during 2004–2010, slowed in 2012–2014 and increased since August 2014 when grouting operations stopped due to the temporary capture of the dam by the self proclaimed Islamic State. We model the inferred deformation using a Markov chain Monte Carlo approach to solve for change in volume for simple tensile dislocations. Results from recent and historical geodetic datasets suggests that the volume dissolution rate remains constant when the equivalent volume of total concrete injected during re-grouting operations is included in the calculations.

42 ENGINEERING↗
DOE OSTI2018

Provisional Conceptual Model of the Camas Prairie (ID) Geothermal System from Play Fairway Analysis

Camas Prairie, Idaho, is an EW-trending structural graben that lies north of the Snake River Plain hotspot track. It is bounded on the north by the Idaho Batholith, and on the south by the Mount Bennett Hills. This region was investigated by the SRP Geothermal Play Fairway Analysis team, which included focused geologic, geochemical, and geophysical studies. The Camas Prairie geothermal system resource is indicated by warm springs and wells, geophysical analysis of buried faults and basins, mapped faults, structural analysis of all faults and lineaments, high 3He/4He, cation and multicomponent geothermometry, and the occurrence of young basalt vents and lava flows along the range front. Our provisional conceptual model includes the following components: (1) High permeability is indicated by the confluence of intersecting faults, including the major range front system and The Pothole fault system, with releasing bends as deduced from detailed field studies, and the presence of springs along mapped structural features; (2) High heat is inferred to result from mid- to shallow crustal sills, as evidenced by the location of vents along the range front; the youngest dated vent is 692 ka, but 2 ka vents lie to NW; (3) an effective seal is indicated by magnetotelluric studies, which suggest a clay seal over the prospective target area that is likely a result of hydrothermal alteration. This model is similar to that proposed for the western SRP but is less energetic due to the smaller volume of magma inferred. It is also similar to Basin-and-Range geothermal systems, but differs by including a distinct magmatic heat component.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

The ongoing destabilization of the mosul dam as observed by synthetic aperture radar interferometry

We present a detailed survey here on the ongoing destabilization process of the Mosul dam. The dam is located on the Tigris river and is the biggest hydraulic structure in Iraq. From a geological point of view the dam foundation is unstable due to the underlying geology that is formed by alternate and variable strata of highly soluble materials such as gypsum, anhydrite, marl and limestone. We present the first comprehensive multi-sensor cumulative deformation map for the dam generated from space-based synthetic aperture radar (SAR) measurements from the Italian constellation COSMO-SkyMed and the European Sentinel-1a satellite. We compared 2014-2016 data to an historic dataset spanning 2004-2010 acquired with the Envisat ASAR sensor. We found that deformation was rapid during 2004-2010, slowed down in 2012-2014, and restarted in August 2014 when grouting operations stopped due to the temporary capture of the dam by the self proclaimed Islamic State in Iraq and Syria (ISIS). We took advantage of the availability of data from multiple SAR satellites to infer the deformation at the dam in great spatial and temporal detail and shed new light on the processes of the ongoing destabilization. This study highlights how new constellations of SAR sensors together with the availability of historical datasets are leading to important advances in deformation monitoring of small scale geologic and manmade features.

58 GEOSCIENCES↗
DOE OSTI2026

A Play-Based Exploration of CO 2 Storage in the Illinois Basin: Development and Application of the Play-Based Exploration Workflow

This report documents the workflow developed and applied for a play-based exploration (PBE) of carbon capture and storage (CCS) potential in the Illinois Basin, conducted under U.S. Department of Energy Cooperative Agreement DE-FE0032366. The project was led by the Illinois State Geological Survey (ISGS) at the University of Illinois Urbana-Champaign in collaboration with Visage Energy. The goal of this workflow is to identify locations where subsurface, surface, and societal conditions align to support safe and effective geologic CO 2 storage. To achieve this, the project team developed a systematic, seven-step workflow for conducting play-based exploration: (1) defining play elements, (2) collecting data, (3) constructing a geodatabase, (4) defining suitability criteria, (5) conducting suitability mapping, (6) generating Common Risk Segment (CRS) maps, and (7) creating composite play maps. The workflow is designed to be repeatable and adaptable for CCS assessments in other regions or for alternative subsurface energy applications such as hydrogen or natural gas storage.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Subsurface Characterization of Hydraulic Fracture Test Site-2 (HFTS-2), Delaware Basin

Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp Formation of the Permian (Delaware) Basin. This paper focuses on integration, advanced geological characterization, and 3D subsurface modeling of the comprehensive HFTS-2 dataset. The study showcases a multidisciplinary reservoir characterization approach that incorporates geology, petrophysics, geochemistry, geomechanics, microseismic, and subsurface engineering analysis. Subsurface characterization of organic-rich mudstone formations requires understanding complex hydraulic fracture network growth in relation to inherent lithology, geomechanical properties, and interaction with pre-existing natural fractures. This paper presents a characterization workflow incorporating pre- and post-stimulation subsurface data, unique to the HFTS-2 dataset. The study integrated: (1) rock properties from logs, cores, and thin sections; (2) natural and hydraulic fracture descriptions from cores and image logs; (3) local and regional stresses; (4) geomechanics; (5) microseismic; (6) fiber optic (FO) and bottomhole pressure gauge (BHPG) response; and (7) produced fluids analysis. During a stimulation treatment, creation of the stimulated rock volume (SRV) is influenced by several subsurface factors. Key contributing factors include structural context, stress conditions, lithology, facies architecture, pre-existing natural fractures, and geomechanical properties. The HFTS-2 subsurface data integration indicates that the SRV is comprised of a complex juxtaposition of hydraulic fracture swarms, as evidenced by image logs analysis, core description, and microseismic monitoring. The HFTS-2 microseismic event density was used to generate 3D heat maps that serve as a representative SRV footprint, corroborated by secondary datasets. These maps were further integrated with petrophysical and geomechanical characteristics, as well as responses from FO and BHPG, to estimate the lateral and vertical dimensions of the effective fractures. The geological characterization for the HFTS-2 dataset combined with 3D modeling for petrophysical and geomechanical properties provides a strong foundation for subsurface simulation and optimization studies. Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S005R001/2477501/urtec-2021-5243-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5243 The workflow improved our understanding of HFTS-2 hydraulic fracture propagation and characteristics in relation to offset pressure depletion and interaction with pre-existing natural fractures. Analysis showed that fracture geometry varies by stage and by well, and a complex fracture network is generated with varying fracture density. The multidisciplinary workflow presented herein for integration and characterization serves as a foundation to evaluate completion efficiency and estimate areal and vertical stimulation and depletion extent for the project. Furthermore, the workflow and learnings can also be transferred to other unconventional plays.

58 GEOSCIENCES↗