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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Changes in rock matrix compressibility during deep CO 2 storage

Geologic carbon storage projects aim to permanently trap large volumes of CO 2 in reservoir rock sealed with low permeability layers. As high-pressure supercritical or liquid CO 2 is injected, hydromechanical and chemical processes caused by the reaction between the rock and acidic mixture of brine and CO 2 are initiated. The compressibility of reservoir rock needs to be properly characterized in order to assess the deformation and stability of the host formations, and there are a number of factors to be considered, including the matrix structure, solid, pores, and fluid. Here this study triggers from a fundamental question whether CO 2 treatment affects the compressibility of the rock matrix and its dominant composing solid minerals. Three different reservoir representatives are selected: Berea sandstone for silica-rich rock, and Apulian limestone and Indiana limestone for calcite-rich rock. Quartz and calcite are the main composing minerals of the reservoir rock, and their crystals are separately examined. Experimental methods are introduced for high-pressure CO 2 treatment of water-saturated materials, and measurements of the unjacketed and solid compressibilities are conducted. No change in the solid compressibility of the sandstone and quartz after CO 2 treatment is observed, whereas it increases by 18–21% for the limestones and by 15% for calcite. The latter observation is inconsistent with the ultrasonic wave velocities measurements and is believed to be due to the local dissolution of the calcite crystal surface. Our results show that only the solid matrix of the limestones becomes more compressible after CO 2 treatment. Consequent microimaging and mercury intrusion porosimetry analyses allowed observations of dissolution and precipitation of calcite, and creation of new connected and non-connected pores. Finally, the changes in limestone solid compressibilities and pore structure could significantly affect the rock properties and behavior during and after CO 2 injection and should be accounted for in the reservoir models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Seismic Characterization of the Blue Mountain Geothermal Field

Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.

58 GEOSCIENCES↗
DOE OSTI2021

Modeling Contact Angle vs. Temperature for the Quartz-Water-Decane System

Innovative approaches are needed to improve the efficiency of oil recovery technologies to meet the growing demands of fossil-fuel based energy consumption. Enhanced oil recovery (EOR) methods such as low-salinity waterflooding and chemically tuned waterflooding aim to optimize the reservoir’s wetting properties, detaching oil globules from rock surfaces and allowing easier oil flow through pore throats. This wetting behavior is commonly quantified by contact angle measurements of the rock-oil-brine interface, which have been thoroughly investigated and theorized for many systems at ambient temperatures and pressures. However, few studies exist for extending contact angle theories away from ambient conditions. In this paper, we model the contact angles of a quartz-water-decane system at elevated temperatures using the surface tension component (STC) approach. Temperature-dependent van der Waals [Lifshitz-van der Waals (LW)] interactions and hydrogen-bonding (acid-base) interactions were calculated and are incorporated into the model for the quartz-water-decane interface. Additionally, the Hough and White procedure was used to create temperature-dependent dielectric functions of quartz, water, and normal decane for calculations of Hamaker coefficients. Hamaker coefficients calculated this way are highly linear with temperature and agree well with Israelachvili’s approximation. The acid-base interactions likely contribute the most to system wettability changes. Resulting contact angles of the quartz-water-decane system shift from water-wet (16°) to slightly water-wet (57.4°) as temperature increases. The model was also successfully verified for the quartz-air-water system. Our results can be used in future studies to determine optimal injected water compositions for specific rock-oil-brine and other systems with consideration of reservoir temperature.

02 PETROLEUM↗
DOE OSTI2022

Joint physics-based and data-driven time-lapse seismic inversion: Mitigating data scarcity

In carbon capture and sequestration (CCS), developing rapid and effective imaging techniques is crucial for real-time monitoring of the spatial and temporal dynamics of CO 2 propagation during/after injection. With continuing improvements in computational power and data storage, data-driven techniques based on machine learning (ML) have been effectively applied to seismic inverse problems. In particular, ML helps alleviate the ill-posedness and high computational cost of full-waveform inversion (FWI). However, such data-driven inversion techniques require massive high-quality training data sets to ensure prediction accuracy, which hinders their application to time-lapse monitoring of CO 2 sequestration. We propose an efficient “hybrid” time-lapse workflow that combines physics-based FWI and data-driven ML inversion. The scarcity of the available training data is addressed by developing a new data-generation technique with physics constraints. The method is vali dated on a synthetic CO 2 -sequestration model based on the Kimberlina storage reservoir in California. The proposed approach is shown to synthesize a large volume of high-quality, physically realistic training data, which is critically important in accurately characterizing the CO 2 movement in the reservoir. In conclusion, the developed hybrid methodology can also simultaneously predict the variations in velocity and saturation and achieve high spatial resolution in the presence of realistic noise in the data.

58 GEOSCIENCES↗
DOE OSTI2024

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the “black-box” nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having “no change” (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the “black-box” nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having “no change” (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

58 GEOSCIENCES↗
DOE OSTI2024

Identification of equine mares as reservoir hosts for pathogenic species of Leptospira

Equine leptospirosis can result in abortion, stillbirth, neonatal death, placentitis, and uveitis. Horses can also act as subclinical reservoir hosts of infection, which are characterized as asymptomatic carriers that persistently excrete leptospires and transmit disease. In this study, PCR and culture were used to assess urinary shedding of pathogenic Leptospira from 37 asymptomatic mares. Three asymptomatic mares, designated as H2, H8, and H9, were PCR-positive for lipL32, a gene specific for pathogenic species of Leptospira. One asymptomatic mare, H9, was culture-positive, and the recovered isolate was classified as L. kirschneri serogroup Australis serovar Rushan. DNA capture and enrichment of Leptospira genomic DNA from PCR-positive, culture-negative samples determined that asymptomatic mare H8 was also shedding L. kirschneri serogroup Australis, whereas asymptomatic mare H2 was shedding L. interrogans serogroup Icterohaemorrhagiae. Sera from all asymptomatic mares were tested by the microscopic agglutination test (MAT) and 35 of 37 (94.6%) were seropositive with titers ranging from 1:100 to 1:3200. In contrast to asymptomatic mares, mare H44 presented with acute spontaneous abortion and a serum MAT titer of 1:102,400 to L. interrogans serogroup Pomona serovar Pomona. Comparison of L. kirschneri serogroup Australis strain H9 with that of L. interrogans serogroup Pomona strain H44 in the hamster model of leptospirosis corroborated differences in virulence of strains. Since lipopolysaccharide (LPS) is a protective antigen in bacterin vaccines, the LPS of strain H9 (associated with subclinical carriage) was compared with strain H44 (associated with spontaneous abortion). This revealed different LPS profiles and immunoreactivity with reference antisera. It is essential to know what species and serovars of Leptospira are circulating in equine populations to design efficacious vaccines and diagnostic tests. Our results demonstrate that horses in the US can act as reservoir hosts of leptospirosis and shed diverse pathogenic Leptospira species via urine. This report also details the detection of L. kirschneri serogroup Australis serovar Rushan, a species and serotype of Leptospira, not previously reported in the US.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Spatial heterogeneity analyses of pore structure and mineral composition of Barnett Shale using X-ray scattering techniques

The spatial heterogeneity of pore structure and mineral composition at mu m to mm scales in mm to cm-sized shale samples complicates the laboratory measurements of porosity & pore size distribution and consequently reservoir quality evaluation. Traditional fluid invasion characterization methods typically take hours to days to get data and can only test relatively small samples (usually 2.54 cm diameter core plugs and mm-sized rock chips). Furthermore, the Xray scattering techniques at the Advanced Photon Source of the Argonne National Laboratory have the capability to non-destructively determine the pore structure and mineral composition of mm x mm area in a short time of seconds and to hold several to hundreds of mm 2 sized sample to conduct large area heterogeneity analysis in the short duration of hours. With the use of ultra-small angle X-ray scattering (USAXS), small-angle X-ray scattering (SAXS), and wide-angle X-ray scattering (WAXS), the porosity, surface area and pore size distribution of two Barnett Shale samples have been mapped out and the mineral compositions are determined qualitatively. Overall, the porosity and pore surface area of the Barnett Shale Sample A over a 36 cm2 area ranges from 1.70 % to 8.13 % and 8.87 m 2 /g to 40.2 m 2 /g respectively. The porosity and surface area of Sample B over a 24 cm 2 area varies from 3.15 % to 11.7 % and 18.3 m 2 /g to 60.2 m 2 /g. In Sample A, the mineral composition shows a shift from carbonate-rich to siliciclastic-rich over a distance of several millimeters. For Sample B, the mineral compositions are mainly siliciclastic and do not show an obvious lithological change. The direct observations of high spatial heterogeneity of pore structure and mineral composition in shale illustrate the utility of integrated X-ray scattering techniques to provide valuable insights into shale studies and reservoir evaluation.

58 GEOSCIENCES↗
DOE OSTI2025

High-Resolution Computed Tomography Dataset of Mount Simon Sandstone

The Illinois Basin is a critical structure for subsurface energy related activities and their implementation in the United States. The Mount Simon Sandstone has been identified as a storage target for permanent and transient storage of fluids in the basin. Known for its exceptional thickness, depth, porosity, and sealing properties of overlying formations, this saline reservoir is crucial for long-term subsurface energy efforts. We present an extensive Computed Tomography (CT) dataset on a high porosity and permeability zone in the lower Mount Simon Sandstone available on the Energy Data eXchange® (EDX). This publicly accessible database comprises over 500 GB of high-resolution CT scans of six core samples, with resolutions ranging from 14.8 µm to 0.7 µm per pixel. The scans include both dry sandstone samples and those saturated with multiple fluids, allowing for comparative analyses across different conditions and resolutions. Coarser scans capture the bedding structure of the sandstone, while finer resolutions reveal detailed pore infill and throat characteristics. Metadata on location, depth, and saturation state enhance usability, enabling quick identification and cross-sample comparisons. By providing a robust resource for research and collaboration, the database contributes to domestic energy advancement by supporting continued progress in the use of the subsurface for energy solutions.

characterization↗
DOE OSTI2024

Geothermal Reservoir Simulation Analysis in Support of Electricity Co-Production Feasibility Study at the Blackburn Oil Field, Nevada: Preprint

Geothermal electricity co-production is a viable option for oil reservoirs producing large water cuts with elevated wellhead-observed temperatures. Repurposing existing oil wells significantly reduces initial investment costs historically associated with geothermal resource utilization. The National Renewable Energy Laboratory (NREL), partnering with Gradient Geothermal, Inc. (formerly known as Transitional Energy) and Grant Canyon Oil and Gas, has been tasked to evaluate the feasibility of geothermal electricity co-production at the Blackburn Oil Field with Organic Rankine Cycle (ORC) generators. The Devonian steady-state reservoir has historically been producing high water cuts of 240 degrees F (115.6 degrees C) observed at the wellhead without documented pressure drawdown or thermal breakthrough. An estimated initial reservoir temperature of approx. 260degreesF (126.7 degrees C) has been observed in the field and history-matched in a wellbore production analysis and reservoir simulation. Our objective was to develop a conceptual geological model of the subsurface, simulate a natural-state reservoir, model production scenarios, and complete a technical feasibility analysis to accomplish this task. Through extensive modeling and the use of available proprietary and public data, it was possible simulate three scenarios that indicated minimal thermal decline over the duration of a simulated ten-year production and re-injection scheme.

Blackburn Nevada↗
DOE OSTI2025

Geothermal Reservoir Simulation Analysis in Support of Electricity Co-Production Feasibility Study at the Blackburn Oil Field, Nevada

Geothermal electricity co-production is a viable option for oil reservoirs producing large water cuts with elevated wellhead temperatures. Repurposing existing oil wells significantly reduces initial investment costs historically associated with geothermal resource utilization. The National Renewable Energy Laboratory (NREL), partnering with Gradient Geothermal, Inc. (formerly known as Transitional Energy) and Grant Canyon Oil and Gas, has been tasked to evaluate the feasibility of geothermal electricity co-production at the Blackburn Oil Field with Organic Rankine Cycle (ORC) generators. The Devonian steady-state reservoir has historically been producing high water cuts of 240 degrees F (115.6 degrees C) observed at the wellhead without documented pressure drawdown or thermal breakthrough. An estimated initial reservoir temperature of approx. 260 degrees F (126.7 degrees C) has been observed in the field and history-matched in a wellbore production analysis and reservoir simulation. Our objective was to develop a conceptual geological model of the subsurface, simulate a natural-state reservoir, model production scenarios, and complete a technical feasibility analysis to accomplish this task. Through extensive modeling and the use of available proprietary and public data, it was possible simulate three scenarios that indicated minimal thermal decline over the duration of a simulated ten-year production and re-injection scheme.

Blackburn Nevada↗
DOE OSTI2021

Mechanical Properties of Nominally Ductile and Brittle Zones within the Caney Shale Formation

We present a case study from the Caney Shale, which is an emerging hydrocarbon-bearing formation in Oklahoma. Open hole logs lead to a nominal distinction of five zones in an exploration well, two of which are designated “ductile” and three of which are designated as less ductile “reservoir” zones. Subsequently, a detailed mechanical characterization was carried out on core plugs taken from each of these zones. Results show nominally “ductile” zones are weaker in terms of UCS, tensile strength, fracture toughness, and confined compressive strength. However, by a variety of brittleness indices, it is found the nominal “ductile” regions do not behave as expected. They are weaker, but not consistently more ductile. Furthermore, some brittleness indices lead to contradictory conclusions. For example, zones which would be considered the most brittle according to the proportion of nonlinear stress-strain behavior prior to failure and/or by indices based on elastic properties would be considered the least brittle according to their internal friction angle.

Benge, Margaret↗
DOE OSTI2022

Proxy-Based Bayesian Inversion Of Poroelastic Simulations To Interpret Strain Tensor Data Measured During Well Testing

The long runtimes of 3D poroelastic numerical simulators makes it impractical to interpret deformation datasets using many inversion schemes. Recent advances in instrumentation have made it possible to measure the strain tensor during well testing, but the lack of robust inversion methods is limiting the ability to interpret these data. We have developed an inversion workflow that reduces the number of computations required to complete a Bayesian inversion using DREAMzs. The workflow trains a KNN model using output from the poroelastic simulator, and then uses the KNN model as a proxy for the simulator during inversion. The workflow also includes a strategy for ensuring the results from the proxy model converge to the results from the simulator, ensuring the accuracy of the final results. An idealized example configured to represent a well test in a deep aquifer is used to verify that the workflow correctly identifies parameters and characterizes noise. Field data measured using strainmeters during an injection test at an oil reservoir in Oklahoma are used to evaluate performance with a real dataset. The workflow identified 265 history matching solutions out of 1240 total simulation runs (21% acceptance ratio), and the results are used to characterize posterior parameter distribution and evaluate the prediction uncertainty. This approach makes it feasible to invert strain data measured during well testing and this has the potential to improve the characterization of aquifers and reservoirs.

Roudini, Soheil↗
NASA NTRS2002

Tracking Avian Reservoirs of Arboviruses using Remote Sensing and Radiotelemetry

Encephalitis is caused by a virus that is transmitted by mosquitoes between mammalian hosts. The virus is closely related to the West Nile virus (WNV), which started in New York in 1999, and has since spread to 25 states. Like encephalitis, WNV is vectored by mosquitoes, and the primary hosts are birds; humans are accidental, or'dead-end' hosts. Very little is understood about the behavior of these bird populations, and how they intersect - both in time and in space - with mosquito populations. Exploring these relationships is the first step in developing models for encephalitis and WNV transmission risk. This project combines remotely sensed data with radiotelemetry to create a spatiotemporal map of encephalitis viral activity in bird and mosquito populations in the Sacramento Valley of California. Specifically, remote sensing (RS) and geographic information system (GIS) technologies were used to characterize habitats utilized by both avian viral reservoirs and the mosquitoes that vector encephalitis. Radiotelemetry and serosurveys (blood) were then used to spatially and temporally track the patterns of infection. The project uses Landsat ETM+ multitemporal satellite data to characterize habitats utilized by both birds and the mosquito vectors. Mist nets were used to sample members of individual flocks of blackbirds and cowbirds over a period of several months; these birds were then bled to assess their viral status, banded, and fitted with transmitters. Radiotelemetry was used to spatially and temporally track the distribution of banded birds and their associated flocks. The movement of these indicator flocks were compared with the location of remotely sensed (adult and larval) mosquito habitats to determine the intersection of bird's and vectors; this is key in understanding where and when transmission occurs from bird to bird, as well as from bird to mammal, via mosquito. The relationships found during the project are being used to generate a model of encephalitis transmission risk in California.

Beck, L.↗
DOE OSTI2023

Field Laboratory for Emerging Stacked Unconventional Plays in Central Appalachia

The goal of the Field Laboratory for Emerging Stacked Unconventional Plays (ESUP) in Central Appalachia project was to investigate and characterize the resource potential for multi-play production of emerging unconventional reservoirs in Central Appalachia. Project activities included drilling, logging and coring of a vertical characterization well drilled to basement to approximately 15,000 feet in depth. The data from drilling and well logs as well recovered core samples were used by the research team to support characterization of the geology and potential pay zones within the Nora Gas Field of southwestern Virginia and the greater Central Appalachian Basin. This project was led by Dr. Nino Ripepi of the Virginia Center for Coal and Energy Research (VCCER) in close collaboration with EnerVest Operating LLC (EnerVest). VCCER is housed in the Department of Mining and Minerals Engineering at Virginia Tech and was created by an Act of the Virginia General Assembly on March 30, 1977, as an interdisciplinary study, research, information, and resource facility for the Commonwealth of Virginia. EnerVest is a top tier, low-cost oil and natural gas company with a long history of traditional operating relationships with institutional investors as well as public and private companies. This report summarizes two major research activities: 1) Log and Core Analysis and 2) Numerical Modeling. Core analysis comprises the characterization efforts of the ESUP Field Laboratory and includes a discussion of the well logs run in the deep characterization wells, an initial analysis of those, the number, size and location of cores recovered, core testing and analysis done to date as well as plans for future analysis. Numerical modeling is comprised of seven major modeling efforts, including (1) Multiphysics shale transport modeling work, (2) the developed in-house compositional simulator studies, (3) reservoir modeling studies using GEM software, (4) fracture modeling work using EFRAC3D software and (5) numerical modeling efforts with ABAQUS software, (6) Numerical modeling efforts using FLAC3D and PFC3D, and (7) Automatic Machine Learning (AutoML) Studies.

02 PETROLEUM↗
DOE OSTI2020

Assessment of Enhanced Oil Recovery Using Carbon Dioxide in Michigan Basin Silurian Pinnacle Reefs

The Midwest Regional Carbon Sequestration Partnership (MRCSP) has incorporated the work of geologic research teams (Geoteams) in its regional characterization, project planning and carbon dioxide (CO 2 ) injection implementation work since the partnership was established by the U.S. Department of Energy (DOE) in 2003. Over this 16-year period, the cohort of Geoteams has grown from five to ten states and has contributed to the characterization of geologic sequestration opportunities, refinement of reservoir and seal data, and supported injection efforts through both predictive and post-injection assessments. The Michigan team at Western Michigan University has provided technical analysis and support of the enhanced oil recovery (EOR) using carbon dioxide (CO 2 ) in the Northern Michigan Silurian Pinnacle reefs. With Core Energy, LLC as the industry partner, this project has assessed the potential for EOR in known fields in the Michigan Pinnacle reefs and the capacity for CO2 storage in the reef reservoirs as they are depleted and after reservoir abandonment. This project managed by Core Energy, LLC, involves the only commercial CO 2 Enhanced Oil Recovery floods within the MRCSP region. The Silurian pinnacle reef trend shows significant potential for CO 2 -EOR: this play is relatively new, with approximately 60% of the wells in the largest Niagaran fields still accessible. Most wells have modern logs and there are many cores, core analyses, pressure tests and produced water analyses available for study from these fields. These carbonate reservoirs in Michigan have produced sufficient oil to warrant evaluation for additional recovery efforts. The role of the Michigan team was to collect and analyze all relevant data about reservoir properties, including lithologic and depositional characteristics of the reservoir formations and porosity and fluid flow properties through different compartments in the reservoir. The team has also developed models that represent the geological and physical characteristics of the reservoir and seal system.

01 COAL, LIGNITE, AND PEAT↗