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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A thermomechanical anisotropic continuum model for geological materials with multiple joint sets

Joints in geological materials introduce elastic compliance and weak planes on which sliding can occur. Although these materials can have multiple joint sets, they often have preferred orientations that cause both elastic and inelastic anisotropic response even when the unjointed material is isotropic. Azimuthal variations in radial velocity and polarity of tangential motion have been observed in experimental data for wave propagation caused by an initially spherical source in a geological material with multiple joint sets. This observed tangential ground motion was found to be related to mechanical anisotropy caused by preferred orientations of joints in the rock. This paper describes thermomechanical continuum constitutive equations, which model the effects of multiple persistent joint sets. A number of quasi–static examples are considered, which show that the proposed model predicts anisotropic effects of sliding on multiple joint sets similar to those exhibited by computationally expensive mesoscale calculations, which model joint sets explicitly.

58 GEOSCIENCES↗
DOE OSTI2020

Time-Lapse Gravity Monitoring of CO2 Migration Based on Numerical Modeling of a Faulted Storage Complex

In this study, the performance of both surface and borehole time-lapse gravity monitoring to detect CO2 leakage from a carbon storage site is evaluated. Several hypothetical scenarios of CO2 migration in a leaky fault, and thief zones at different depths at the Kimberlina site (California, USA) constitute the basis of the approach. The CO2 displacement is simulated using the TOUGH2 simulator applied to a detailed geological model of the site. The gravity responses to these CO2 plumes are simulated using forward modeling with sensors at ground surface and in vertical boreholes. Results of inversion on one scenario are also presented. The surface-based gravity responses obtained for the different leakage scenarios demonstrate that leakage can be detected at the surface in all the scenarios but the time to detection is highly variable (10 to 40 years) and dependent on the detection threshold considered. Borehole measurements of the vertical component of gravity provide excellent constrains in depth when they are located in proximity of the density anomaly associated with the presence of CO2, thus discriminating multiple leaks in different thief zones. Joint inversion of surface and borehole data can bring valuable information of the occurrence of leakages and their importance by providing a reasonable estimate of mass of displaced fluids. This study demonstrates the importance of combining multiphase flow simulations with gravity modeling in order to define if and when gravity monitoring would be applicable at a given storage site.

Time-lapse gravity monitoring, leak detection, CCS↗
DOE OSTI2014

Bell Creek Test Site: 3-D Seismic and Characterization Report

The Plains CO 2 Reduction (PCOR) Partnership, led by the Energy & Environmental Research Center (EERC), is working with Denbury Onshore (Denbury) to evaluate the effectiveness of large-scale injection of carbon dioxide (CO 2 ) into the Bell Creek oil field for CO 2 enhanced oil recovery (EOR) and to study long-term incidental CO 2 storage. A technical team that includes Denbury, the EERC, and others are conducting activities to determine the baseline reservoir characteristics for development of a geologic model for predictive simulations and to serve as a comparison to time-lapse data as they are acquired. One of the activities was the acquisition and interpretation of a baseline three-dimensional (3-D) surface seismic survey acquired over a major portion of the field which is the subject of this report. The interpretation will be used to advance the field characterization effort. The geophysical data will be integrated with the EERC’s geologic model to improve its accuracy. In the future, when paired with at least one subsequent 3-D surface seismic survey, the data difference will provide a direct indication of where the CO 2 has migrated within the reservoir and aid in monitoring, verification, and accounting goals.

02 PETROLEUM↗
DOE OSTI2018

Improved Characterization and Modeling of Tight Oil Formations for CO 2 Enhanced Oil Recovery Potential and Storage Capacity Estimation

Tight oil formations such as those in the Bakken petroleum system are known to hold hundreds of billions of barrels of oil in place; however, the primary recovery factor for these plays is typically less than 10%. Tight oil formations, including the Bakken Formation, therefore, may be attractive candidates for enhanced oil recovery (EOR) using CO 2 . Multiphase fluid behavior and flow in fluid-rich shales can vary substantially depending on the size of pore throats, and properties such as fluid viscosity and density are much different in nanoscale pores than in macroscale pores. Thus it is critical to understand the nature and distribution of nano-, micro-, and macroscale pores and fracture networks. To address these issues, the Energy & Environmental Research Center (EERC) has been conducting a research program entitled “Improved Characterization and Modeling of Tight Oil Formations for CO 2 Enhanced Oil Recovery Potential and Storage Capacity Estimation.” The objectives of the project are 1) the use of advanced characterization methods to better understand and quantify the petrophysical and geomechanical factors that control CO 2 and oil mobility within tight oil formation samples, 2) the determination of CO 2 permeation and oil extraction rates in tight reservoir rocks and organic-rich shales of the Bakken, and 3) the integration of the laboratory-based CO 2 permeation and oil extraction data and the characterization data into geologic models and dynamic simulations to develop predictions of CO 2 storage resource and EOR in the Bakken tight oil formation. A combination of standard and advanced petrophysical characterization techniques were applied to characterize samples of Bakken Formation tight reservoir rock and shales from multiple wells. Techniques included advanced computer tomography (CT) imaging, scanning electron microscopy (SEM) techniques, whole-core and micro x-ray CT imaging, field emission (FE) SEM, and focused ion beam (FIB) SEM. Selected samples were also analyzed for geomechanical properties. X-ray CT imaging yielded information on the occurrence of fractures, bedding planes, fossils, and bioturbation in core, as well as data on bulk density and photoelectric factor logs, which were used to interpret porosity, organic content, and mineralogy. FESEM was used for characterization of nano- and microscale features, including nanoscale pore visualization and micropore and pore throat mineralogy. FIBSEM yielded micro- to nanoscale visualization of fracture networks, porosity and pore-size distribution, connected versus isolated porosity, and distribution of organics. Results from the characterization activities provide insight on nanoscale fracture properties, pore throat mineralogy and connectivity, rock matrix characteristics, mineralogy, and organic content. Laboratory experiments demonstrated that CO 2 can permeate the tight matrix of Bakken shale and nonshale reservoir samples and mobilize oil from those samples. Geologic models were created at scales ranging from the core plug to the reservoir, and dynamic simulations were conducted. The data from the characterization and laboratory-based activities were integrated into modeling research activities to determine the fundamental mechanisms controlling fluid transport in the Bakken, which support EOR scheme design and estimation of CO 2 storage potential in tight oil formations. Simulation results suggest a CO 2 storage resource estimate range of 169 million to 1.5 billion tonnes for the Bakken in North Dakota, possibly resulting in 1.8 billion to 16 billion barrels of incremental oil.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2023

Evaluation of a preliminary regional Earth model through comparison of synthetic and observed waveform data

In this report, we document the process related to developing a regional geologic model of a 605 x 1334 km area centered around Utah and encompassing surrounding states. This model is developed to test the effect that composition of a model has on the generation of synthetic data with the intent of using this information to improve upon full waveform moment tensor inversions. We compare observed data from three seismic events and five stations to the synthetic data generated by a preliminary model derived from a geologic framework model (GFM) developed by the USGS. The synthetic data and observed data comparisons indicate that our preliminary model performs well at smaller offset distances in the northern and central sections of the model. However, the southern stations consistently display synthetic data P- and S-wave arrival times that do not match the observed data arrival times, indicating that the velocity structure of the southern part of the model especially is inaccurate.

58 GEOSCIENCES↗
DOE OSTI2014

Southeast Carbon Sequestration Partnership (SECARB) Phase III Anthropogenic Test at Citronelle Field, Mobile Co., AL: Project Assessment Report

The Southeast Carbon Sequestration Partnership Phase III Anthropogenic Test at Citronelle Field is the United States’ largest CO 2 capture and transportation, injection, storage and monitoring project using CO 2 derived from a coal-fired power station. The project represents a U.S. Department of Energy research and development initiative designed to demonstrate deep underground injection and containment of 100,000 tonnes or more of anthropogenic-source CO 2 . This report provides an assessment of the CO 2 injection at the Citronelle Anthropogenic Test site for the period August 23, 2012 to August 31, 2013. The purpose of the project assessment is to re-evaluate the AoR for the injection well. The AoR is defined as the region surrounding the geological sequestration project that may be impacted by the injection activity. The AoR is further defined as the farthest reach of the tangible CO 2 plume and/or the region of ‘significant’ reservoir pressure increase. An updated geologic model of the injection zones and storage reservoir sandstones incorporates geologic data obtained from the injection well and characterization wells drilled at the Phase III Anthropogenic Test site. The numerical modeling of the injection was conducted using the updated geologic model, plus the monitoring results obtained to August 31, 2013. The simulation demonstrates effective containment of CO 2 by the reservoir architecture of the upper Paluxy Formation, consisting of multiple, stacked, highly porous and permeable sandstones, separated by low permeability flow barriers. The CO 2 containment demonstrated in this report requires an AoR with a radius of 440 ft from the injection well. This revision reduces the radius of the AoR from the preinjection determination of 1,700 ft. With the revised AoR, the only well within the AoR is the injection well itself, the D 9-7 #2. The nearest well to the injector is the D 9-8 #2. The surface location is 870 ft away from the D 9-7 #2, placing the D 9-8 #2 outside the revised AoR.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Application of Machine Learning and Artificial Intelligence in Proxy Modeling for Fluid Flow in Porous Media

Reservoir simulation models are the major tools for studying fluid flow behavior in hydrocarbon reservoirs. These models are constructed based on geological models, which are developed by integrating data from geology, geophysics, and petro-physics. As the complexity of a reservoir simulation model increases, so does the computation time. Therefore, to perform any comprehensive study which involves thousands of simulation runs, a very long period of time is required. Several efforts have been made to develop proxy models that can be used as a substitute for complex reservoir simulation models. These proxy models aim at generating the outputs of the numerical fluid flow models in a very short period of time. This research is focused on developing a proxy fluid flow model using artificial intelligence and machine learning techniques. In this work, the proxy model is developed for a real case CO2 sequestration project in which the objective is to evaluate the dynamic reservoir parameters (pressure, saturation, and CO2 mole fraction) under various CO2 injection scenarios. The data-driven model that is developed is able to generate pressure, saturation, and CO2 mole fraction throughout the reservoir with significantly less computational effort and considerably shorter period of time compared to the numerical reservoir simulation model.

Amini, Shohreh↗
DOE OSTI2021

Risk-based area of review estimation in overpressured reservoirs to support injection well storage facility permit requirements for CO 2 storage projects

This paper by the Energy & Environmental Research Center presents a workflow and modeling approach for delineating a risk-based area of review (AOR) to support a U.S. Environmental Protection Agency (EPA) Class VI permit for a carbon dioxide (CO 2 ) storage project. The approach combines semianalytical solutions for estimating formation fluid leakage through a hypothetical leaky wellbore with the results of numerical reservoir simulations to define the AOR. The modeling utilizes 1) semianalytical solutions from the peer-reviewed literature for formation fluid leakage through abandoned wellbores by Raven (1990) and Avci (1994), 2) a FORTRAN model compiled and described in Cihan et al. (2011, 2012) called ASLMA (Analytical Solution for Leakage in Multilayered Aquifers), and 3) a computational framework for estimating a risk-based AOR first proposed by Oldenburg et al. (2014, 2016). Therefore, the approach builds upon well-established research and underlying hydrogeological principles that have been upheld for nearly three decades. Moreover, the ASLMA model has been broadly applied to an array of storage projects. The work presented herein extends these earlier works using a custom wrapper written in the software environment, R (R Core Team, 2020), which was developed to perform multiple runs of the ASLMA model using given ranges for one or more input parameters. In addition, the current work simulates the pressure buildup within the storage reservoir in response to CO 2 injection using a compositional simulator to better accommodate the temporospatial evolution of pressure buildup within the storage reservoir that is more accurately modeled using a heterogeneous geologic model and a compositional simulator that accounts for the multiphase interactions. The workflow is demonstrated using a case study for a 180,000-metric-ton-per-year storage project located in the PCOR (Plains CO 2 Reduction) Partnership region. For the storage project evaluated here, under the scenario where the leaky wellbore is open to a saline aquifer (thief zone) between the overlying seal (cap rock) and the underground sources of drinking water (USDW), the risk-based AOR essentially collapses to the areal extent of the CO 2 plume in the storage reservoir because the pressure buildup in the storage reservoir beyond the CO 2 plume is insufficient to drive formation fluids up a hypothetical leaky wellbore into the USDW. However, even under the conservative assumption that the leaky wellbore is not open to a thief zone, beyond the areal extent of the CO 2 plume, the incremental leakage is less than 400 m 3 over 20 years, which represents ~0.0001% or less of the total volume of water contained within the USDW rock volume. As discussed in the text, the threshold criterion for defining the risk-based AOR is site-specific and should be informed by the results of the sensitivity analysis and available site characterization data. The approach outlined in this paper is designed to be protective of USDWs and, therefore, comply with the Safe Drinking Water Act requirements and provisions for the U.S. EPA Class VI Underground Injection Control (UIC) Program (Class VI Rule) and North Dakota Administrative Code Chapter 43-05-01.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration

Geologic carbon sequestration (GCS) is a safety-critical technology that aims to reduce the amount of carbon dioxide in the atmosphere, which also places high demands on reliability. Multiphase flow in porous media is essential to understand CO 2 migration and pressure fields in the subsurface associated with GCS. However, numerical simulation for such problems in 4D is computationally challenging and expensive, due to the multiphysics and multiscale nature of the highly nonlinear governing partial differential equations (PDEs). It prevents us from considering multiple subsurface scenarios and conducting real-time optimization. Here, we develop a Fourier-enhanced multiple-input neural operator (Fourier-MIONet) to learn the solution operator of the problem of multiphase flow in porous media. Fourier-MIONet utilizes the recently developed framework of the multiple-input deep neural operators (MIONet) and incorporates the Fourier neural operator (FNO) in the network architecture. Once Fourier-MIONet is trained, it can predict the evolution of saturation and pressure of the multiphase flow under various reservoir conditions, such as permeability and porosity heterogeneity, anisotropy, injection configurations, and multiphase flow properties. Compared to the enhanced FNO (U-FNO), the proposed Fourier-MIONet has 90% fewer unknown parameters, and it can be trained in significantly less time (about 3.5 times faster) with much lower CPU memory (<15%) and GPU memory (<35%) requirements, to achieve similar prediction accuracy. In addition to the lower computational cost, Fourier-MIONet can be trained with only 6 snapshots of time to predict the PDE solutions for 30 years. Furthermore, we observed that Fourier-MIONet can maintain good accuracy when predicting out-of-distribution (OOD) data. The excellent generalizability of Fourier-MIONet is enabled by its adherence to the physical principle that the solution to a PDE is continuous over time. Furthermore, the developed Fourier-MIONet makes it possible to solve the long-time evolution of geological carbon sequestration in a large-scale three-dimensional space accurately and efficiently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Intermountain West Energy Sustainability & Transitions Initiative: CO 2 Transport and Geologic Storage Modeling Results

This report and its associated Excel spreadsheet file provide the results of technoeconomic modeling of carbon dioxide (CO 2 ) pipeline transport modeling, CO 2 storage in deep saline subsurface formations, and CO 2 enhanced oil recovery (EOR). This report provides the methodology, describes the models and summarizes results for the three aspects of the analysis done for the Intermountain West Energy Sustainability and Transition (I-WEST) Initiative.

42 ENGINEERING↗
NASA NTRS1992

The polar layered deposits on Mars: Inference from thermal inertia modeling and geologic studies

It is widely believed that the Martian polar layered deposits record climate variations over at least the last 10 to 100 m.y., but the details of the processes involved and their relative roles in layer formation and evolution remain obscure. Weathering of the Martian layered deposits by sublimation of water ice can account for the thermal inertias, water vapor abundances, and geologic relationships observed in the Martian polar regions. The nonvolatile components of the layered deposits appears to consist mainly of bright red dust, with small amounts of dark dust. Dark dust, perhaps similar to the magnetic material found at the Viking Lander sites, may preferentially form filamentary residue particles upon weathering of the deposits. Once eroded, these particles may saltate to form the dark dunes found in both polar regions. This scenario for the origin and evolution of the dark material within the polar layered deposits is consistent with the available imaging and thermal data. Further experimental measurements of the thermophysical properties of magnetite and maghemite under Martian conditions are needed to better test this hypothesis.

Herkenhoff, K. E.↗