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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Seismoacoustic Data Fusion for Ground Coupled Airwaves: a FACT Case Study for Calibration and Array Processing

This report covers an inquiry into seismoacoustic array processing using infrasound arrivals combined with resulting Ground Coupled Airwaves (GCA) that are present on collocated seismic sensors. In preparation, data calibration and denoising is completed for a seismoacoustic sensor array that was deployed at the Facility for Acceptance, Calibration, and Testing on Kirtland Airforce Base from August through September of 2021. The events of interest for this study are small, local explosive sources that lead to short duration, impulsive signals on the instruments. The goal is to determine if combining infrasound signals with the corresponding GCAs on collocated seismic sensors can be used to improve the results returned by automated signal detection and characterization (e.g., back azimuth estimates). Preparation for seismic and infrasound data involves removing the instrument response so that sensors have flat power spectra over the frequency range 0.1-10 Hz, where signal from events of interest may be detected. After instrument response removal, deployment conditions specific to this array require a retrospective noise analysis to determine station emplacement characteristics. Once all data is calibrated, a manual search is performed for possible GCA arrivals across the seismoacoustic network. These arrivals are then processed through beamforming and subsequent event identification, resulting in a catalogue of seismoacoustic GCA arrivals with corresponding back azimuth and trace velocity estimations.

47 OTHER INSTRUMENTATION↗
NASA NTRS2011

NLSI Focus Group on Missing ALSEP Data Recovery: Progress and Plans

On the six Apollo landed missions, the Astronauts deployed the Apollo Lunar Surface Experiments Package (ALSEP) science stations which measured active and passive seismic events, magnetic fields, charged particles, solar wind, heat flow, the diffuse atmosphere, meteorites and their ejecta, lunar dust, etc. Today's scientists are able to extract new information and make new discoveries from the old ALSEP data utilizing recent advances in computer capabilities and new analysis techniques. However, current-day investigators are encountering problems trying to use the ALSEP data. In 2007 archivists from NASA Goddard Space Flight Center (GSFC) National Space Science Data Center (NSSDC) estimated only about 50 percent of the processed ALSEP lunar surface data-of-interest to current lunar science investigators were in the NSSDC archives. The current-day lunar science investigators found most of the ALSEP data, then in the NSSDC archives. were extremely difficult to use. The data were in forms often not well described in the published reports and rerecording anomalies existed in the data which could only be resolved by tape experts. To resolve this problem, the DPS Lunar Data Node was established in 2008 at NSSDC and is in the process of successfully making the existing archived ALSEP data available to current-day investigators in easily useable forms. In July of 2010 the NASA Lunar Science Institute (NLSI) at Ames Research Center established the Recovery of Missing ALSEP Data Focus Group in recognition of the importance of the current activities to find the raw and processed ALSEP data missing from the NSSDC archives.

Lewis, L. R.↗
NASA NTRS2012

NLSI Focus Group on Recovery of Missing ALSEP Data: Status Update for 2012 NLSI Science Forum

On the six Apollo lunar landed missions, the Astronauts deployed the Apollo Lunar Surface Experiments Package (ALSEP) science stations which measured active and passive seismic events, magnetic fields, charged particles, solar wind, heat flow, the diffuse atmosphere, meteorites and their ejecta, lunar dust, etc. Today s investigators are able to extract new information and make new discoveries from the old ALSEP data utilizing recent advances in computer capabilities and new analysis techniques. However, current-day investigators are encountering problems in trying to use the ALSEP data. The data were in formats often not well described in the published reports and contained rerecording anomalies which required tape experts to resolve. To solve these problems the DPS Lunar Data Node was established at NASA Goddard Space Flight Center (GSFC) NASA Space Science Data Center (NSSDC) in 2008 and is currently in the process of making the existing archived ALSEP data available to current-day investigators in easily useable forms. However, current estimates by NSSDC archivists are that only about 60 percent of the PI processed ALSEP data and less than 30 percent of the raw experiment ALSEP data-of-interest to current lunar science investigators are currently in the NSSDC archives.

Lewis, Lyach R.↗
DOE OSTI2024

Mapping Permafrost Variability and Degradation Using Seismic Surface Waves, Electrical Resistivity, and Temperature Sensing: A Case Study in Arctic Alaska

Subsurface processes significantly influence surface dynamics in permafrost regions, necessitating utilizing diverse geophysical methods to reliably constrain permafrost characteristics. This research uses multiple geophysical techniques to explore the spatial variability of permafrost in undisturbed tundra and its degradation in disturbed tundra in Utqiagvik, Alaska. Here, we integrate multiple quantitative techniques, including multichannel analysis of surface waves (MASW), electrical resistivity tomography (ERT), and ground temperature sensing, to study heterogeneity in permafrost’s geophysical characteristics. MASW results reveal active layer shear wave velocities (V s ) between 240 and 370 m/s, and permafrost V s between 450 and 1,700 m/s, typically showing a low-high-low velocity pattern. Additionally, we find an inverse relationship between in situ V s and ground temperature measurements. The V s profiles along with electrical resistivity profiles reveal cryostructures such as cryopeg and ice-rich zones in the permafrost layer. The integrated results of MASW and ERT provide valuable information for characterizing permafrost heterogeneity and cryostructure. Corroboration of these geophysical observations with permafrost core samples’ stratigraphies and salinity measurements further validates these findings. This combination of geophysical and temperature sensing methods along with permafrost core sampling confirms a robust approach for assessing permafrost’s spatial variability in coastal environments. Our results also indicate that civil infrastructure systems such as gravel roads and pile foundations affect permafrost by thickening the active layer, lowering the V s , and reducing heterogeneity. We show how the resulting V s profiles can be used to estimate key parameters for designing buildings in permafrost regions and maintaining existing infrastructure in polar regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository

The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.

access↗
DOE OSTI2023

Building an EPA Class VI Permit Application

Summary To accelerate the commercialization of carbon capture and storage (CCS), the US Department of Energy (US DOE) is building on decades of characterization efforts and pilot-scale projects through their CarbonSAFE program. Administered through their National Energy Technology Laboratory, this program seeks to bring fully integrated projects to the sector that can store more than 50 million tonnes of CO2 over a 30-year period. The program, which was enacted before the enhancement of Internal Revenue Code Section 45Q, is in the capture assessment, characterization, and permitting phase. The objectives of this paper are to discuss (a) the injection permitting requirements of the CarbonSAFE projects; (b) information gathering in support of the permit; (c) the timelines of field development and permit-related activities; (d) the major technical components of the field development plan; and (e) early feedback from the regulators toward acceptance of the permit. In Mississippi, more than 30,000 acres have been characterized by six deep characterization wells, a deep groundwater well, and 92 line miles of 2D seismic as part of the CarbonSAFE Project ECO2S. During the acquisition of seismic data, all receiver lines were live, which resulted in the generation of a pseudo-3D seismic design. The incorporation of a 3D seismic survey was not included as part of this project due to logistical difficulties presented by the undulating, wooded surface terrain. A suite of openhole geophysical logs was taken from each well, allowing for a detailed interpretation of prospective storage reservoirs and confining intervals to complement the analysis carried out on the 290 ft of a whole core that was cut through the prospective confining zone and storage reservoir. The detailed geologic and reservoir data were assembled and entered into a 3D model to assess the injection capacity and the area of review (AoR). This information fed into the detailed corrective action, monitoring, testing, and postinjection site care (PISC) modeling. The results have been exceptional. The geologic assessment has revealed three primary storage targets, ranging in depth from 3,500 ft to 6,000 ft. These storage reservoirs net 1,300 ft of sandstone, with mean porosity and permeability of 29% and 3.6 darcies, respectively. Together, these reservoirs have storage capacities that may exceed 20 million tonnes per square mile, making this a gigatonne prospect. Forward modeling of the project resulted in an AoR of 16 sq miles, injecting about 8000 t/d, for 30 years, via two deep injection wells. The excellent confining characteristics of the caprock, relatively simple geologic structure, and lack of historical well drilling activity in this area provide excellent containment of the injected CO2. Based on this work, the project has proposed 20 years of PISC. To date, only two US CO2 injection permits have been granted. These projects relied on a singular capture point feeding a singular sequestration point (source to sink), and considerations have not been made to garner CO2 emissions from other industrial sources. The Kemper County Storage Complex is a first-of-its-kind storage hub concept that looks to develop an area capable of storing significant quantities of CO2 from the region. Also, this work will show how characterization efforts, geological and numerical modeling efforts, and plan development were constructed in support of permit and incentives acceptance.

Energy & Fuels↗
DOE OSTI2020

Beirut Explosion Yield and Mushroom Cloud Height - Effects of the Source Environment

I use crater dimensions to estimate the yield of the August 4th, 2020 Beirut explosion to be equivalent to approximately 1.4 kilotons of TNT with a lower bound of about 0.7 kilotons. Based on the amount of ammonium nitrate reported to have been stored at the Beirut harbor, I assume an upper bound for the yield of 2.75 kilotons. However, it is highly likely that the yield was less than 2.75 kilotons, since reported values for TNT equivalence of ammonium nitrate are typically much less than one hundred percent. The crater-size based yield estimates are based on crater radius estimates from satellite imagery and empirical curves and data for scaled crater radius from past chemical and nuclear explosions. I present evidence that suggests that the relatively large crater radius is due to a high degree of coupling of shock wave energy to the surrounding medium and a reduction of the effective stress because of a high level of saturation of the geologic media beneath the explosion. I provide yield estimates based on seismic body-wave magnitude and crater depth as corroborating evidence. I compare preliminary estimates for the maximum debris cloud height, based on cell phone videos/images, with predicted maximum heights for this yield range from empirical formulas and numerical cloud-rise models. Based on a preliminary analysis of cell phone footage, the observed maximum cloud height appears to be approximately 1600 m. This is much lower than that predicted using standard empirical formulas and buoyant cloud rise models. I present results from a modified buoyant cloud rise model that more accurately predicts the maximum cloud height by allowing for the inclusion of a fixed amount of air and/or water into the fireball at the start of cloud rise. The amount of mass that needs to be added at the start, to reproduce the observed maximum cloud height, is relatively small compared to the total mass entrained during cloud rise. A much greater amount of dry air or debris is required, relative to water, for an equivalent reduction in maximum cloud height. The ammonium nitrate is one possible source for water in the fireball since it was being stored in a very humid environment and ammonium nitrate is known to be hygroscopic. The ground beneath the explosion, especially if it were saturated, and the nearby harbor could also have been sources for water or debris in the fireball.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Signal Decomposition for Intrusion Detection in Reliability Assessment in Cyber Resilience (Summary Report)

The complexity of assuring cyber resilience for physical process interactions in connected systems such as energy grids increases dramatically as the coupling between processes becomes more direct and responsive. An example of this growing complexity is provided by Integrated Energy Systems (IES), in which various processes such as nuclear heat generation and commodity production are being directly coupled for increased responsiveness to highly variable signals such as market pricing or electricity demand. As such, the potential attack surface of the coupled processes is larger than the two processes independently. Securing these complex systems requires two-fold monitoring: cybersecure monitoring for potential malicious incursion, and physics monitoring for system tampering. Physics monitoring includes analyzing the behavior of the signals within the system for anomalous behavior. This analysis has been shown to be insufficient if approached by only data-driven machine learning and artificial intelligence (MLAI) techniques or only low-level model comparison. Previous efforts at Purdue University suggested combining high-fidelity models with MLAI algorithms as a basis for a software tool for detecting anomalies in physical processes. This work built on that suggestion, developing an advanced library for signal decomposition and analysis using both MLAI and high-fidelity physics algorithms for greatly improved anomaly detection, especially false data injection. This software can be used as part of a secure imbedded intelligence (SEI) system designed under Consequence-driven Cyber-informed Engineering (CCE) for complex coupled systems. This library established a foundation for online and posteriori analysis of digital signals for the purpose of detecting potential malicious tampering in digital signals representing physical processes. Demonstrations carried out throughout the development highlight the effective use of characterization algorithms to detect signal perturbations, particularly triangle attack-style perturbations, in three wide-ranging applications: seismic monitoring, nuclear thermal hydraulics system simulation, and custom manufacturing.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Statistical description of tectonic motions

The behavior of stochastic processes was studied whose power spectra are described by power-law behavior. The details of the analysis and the conclusions that were reached are presented. This analysis was extended to compare detection capabilities of different measurement techniques (e.g., gravimetry and GPS for the vertical, and seismometers and GPS for horizontal), both in general and for the specific case of the deformations produced by a dislocation in a half-space (which applies to seismic of preseismic sources). The time-domain behavior of power-law noises is also investigated.

Agnew, Duncan Carr↗
DOE OSTI2023

The influence of physical and algorithmic factors on simulated far-field waveforms and source–time functions of underground explosions using unsupervised machine learning

SUMMARY Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.

58 GEOSCIENCES↗
DOE OSTI2025

Symmetrization of Strong Hydrogen Bond under High Pressure in Bihydroxide-Ion-Containing NaCu 2 (SO 4 ) 2 ·H 3 O 2 Revealed by Experimental Charge Density, Single-Crystal Electron Diffraction, and Neutron Diffraction Studies

In minerals and inorganic compounds, strong hydrogen bonding can lead to the formation of complex ionic species such as the H 3 O 2 – bihydroxide anion and Zundel cation H 5 O 2 + . We studied [NaCu 2 (SO 4 ) 2 ·H 3 O 2 ] natrochalcite, which contains bihydroxide anions and undergoes hydrogen bond symmetrization at the lowest pressure reported so far among inorganic compounds. Hydrogen bond symmetrization leads to changes in the bulk modulus, seismic wave velocities, and proton mobility and plays a primary role in high-temperature superconductivity, but its characteristics are not well understood due to a lack of systematic studies and limitations of experimental methods sensitive to this subtle change. In this work, we applied experimental charge density analysis based on in situ single-crystal X-ray diffraction data, along with the single-crystal neutron and electron diffraction experiments, to probe the behavior of hydrogen atoms during the hydrogen bond symmetrization process under high-pressure conditions. On the way to the symmetrical H-bonding, natrochalcite undergoes a series of complex redistributions of electron density, which we trace with multipole refinement and detailed analysis of changes in the Laplacian of electron density values. Additionally, we deconvoluted the equation of state (volume of the unit cell vs pressure relation) into the atomic equation of states describing dependencies of atomic charges or volumes vs pressure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Connect the Dots: In Situ 4-D Seismic Monitoring of CO 2 Storage With Spatio-Temporal CNNs

4-D seismic imaging has been widely used in CO 2 sequestration projects to monitor the fluid flow in the volumetric subsurface region that is not sampled by wells. Ideally, real-time monitoring and near-future forecasting would provide site operators with great insights to understand the dynamics of the subsurface reservoir and assess any potential risks. However, due to obstacles such as high deployment cost, availability of acquisition equipment, exclusion zones around surface structures, only very sparse seismic imaging data can be obtained during monitoring. That leads to an unavoidable and growing knowledge gap over time. The operator needs to understand the fluid flow throughout the project lifetime and the seismic data are only available at a limited number of times. This is insufficient for understanding reservoir behavior. To overcome those challenges, we have developed spatio-temporal neural-network-based models that can produce high-fidelity interpolated or extrapolated images effectively and efficiently. Specifically, our models are built on an autoencoder, and incorporate the long short-term memory (LSTM) structure with a new loss function regularized by optical flow. We validate the performance of our models using real 4-D post-stack seismic imaging data acquired at the Sleipner CO 2 sequestration field. We employ two different strategies in evaluating our models. Numerically, we compare our models with different baseline approaches using classic pixel-based metrics. We also conduct a blind survey and collect a total of 20 responses from domain experts to evaluate the quality of data generated by our models. Finally, via both numerical and expert evaluation, we conclude that our models can produce high-quality 2-D/3-D seismic imaging data at a reasonable cost, offering the possibility of real-time monitoring or even near-future forecasting of the CO 2 storage reservoir.

4-D seismic imaging↗
NASA NTRS1982

Inverting travel times with a triplication

A method based on the use of constrained spline fits is used to overcome the difficulties arising when body-wave data in the form of T-delta are reduced to the tau-p form in the presence of cusps. In comparison with unconstrained spline fits, the method proposed here tends to produce much smoother models which lie approximately in the middle of the bounds produced by the extremal method. The method is noniterative and, therefore, computationally efficient. The method is applied to the lunar seismic data, where at least one triplication is presumed to occur in the P-wave travel-time curve. It is shown, however, that because of an insufficient number of data points for events close to the antipode of the center of the lunar network, the present analysis is not accurate enough to resolve the problem of a possible lunar core.

Jarosch, H. S.↗
NASA NTRS2003

GPS lessons learned

Global geodesy has improved dramatically over the past decade starting with the GPS for IERS and Geodynamics demonstration campaign in 1991 (GIG 91). At the time it took over a week of CPU time to process a network solution based on 21 global receivers and orbit overlaps were in the 40 cm range. Today it is possible to process a network solution based on 80 global receivers in less then one day of CPU time and orbit overlaps are in the 4 cm range. Special methods are under development for efficient processing of increasingly large regional networks which may contain hundreds or thousands of GPS receivers. Along the way there have been many lessons learned about GPS satellites, receivers, monuments, antennas, radomes, analysis, reference frames, error sources, and interpretation. A wide range of scientific disciplines have been impacted including studies of plate motion, post-glacial rebound, seasonal loading, deformation in plate boundary zones, coseismic displacements due to major earthquakes, postseiemic relaxation, and interseismic strain accumulation related to assessment of seismic hazards. Lessons learned will be presented in the context of new dense networks such as the Plate Boundary Observation (PBO).

GPS satellites↗
NASA NTRS2019

Observational Constraint on the Radius and Oblateness of the Lunar Core‐Mantle Boundary

Lunar laser ranging (LLR) data and Apollo seismic data analyses, revealed independent evidence for the presence of a fluid lunar core. However, the size of the lunar fluid core remained uncertain by _55 km (encompassing two contrasting 2011 Apollo seismic data analyses). Here we show that a new description of the lunar interior's dynamical model provides a determination of the radius and geometry of the lunar core-mantle boundary (CMB) from the LLR observations. We compare the present day lunar core oblateness obtained from LLR analysis with the expected hydrostatic model values, over a range of previously expected CMB radii. The findings suggest a core oblateness (f(c) = (2.2 ± 0.6) x 10(exp 14)) that satisfies the assumption of hydrostatic equilibrium over a tight range of lunar CMB radii (R(CMB) = 381 ± 12 km). Our estimates of a presently-relaxed lunar CMB translates to a core mass fraction in the range of 1.59 - 1.77% with a present-day Free Core Nutation (FCN) within (367±100) years.

Moon↗
DOE OSTI1994

Nuclear Safety [Vol. 35, No. 1, January-June 1994]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: THE CHERNOBYL ACCIDENT: 1 Chernobyl Accident Management Actions, A. R Sich 25 The IAEA-ASSET Approach to Avoiding Accidents is to Recognize the Precursors to Prevent Incidents, F. Reisch; ACCIDENT ANALYSIS: 36 A Review of the Available Information on the Triggering Stage of a Steam Explosion, D. F. Fletcher; 58 Analysis and Modeling of Flow-Blockage-Induced Steam Explosion Events in the High-Flux Isotope Reactor, R. P. Taleyarkhan, V. Georgevich, C. W. Nestor, U. Gat, B. L. Lepard, D. H. Cook, J. Freels, S. J. Chang, C. Luttrell, R. C. Gwaltney, and J. Kirkpatrick; 74 An Analysis of Disassembling the Radial Reflector of a Thermionic Space Nuclear Reactor Power System, M. S. El-Genk and D. V. Paramonov; CONTROL AND INSTRUMENTATION: 86 Standards for High-Integrity Software, D. R. Wallace, D. R. Kuhn, L M. Ippolito, and L. Beltracchi; DESIGN FEATURES: 98 Adoption of New Design Features for the Next Generation Nuclear Power Reactors, L. S. Tong; 114 Review of Nuclear Piping Seismic Design Requirements, G. C. Slagis and S. E. Moore; ENVIRONMENTAL EFFECTS: 128 PC-Based Probabilistic Safety Assessment Study for a Geological Waste Repository Placed in a Bedded Salt Formation, S. A. Khan; OPERATING EXPERIENCES: 142 Managing Aging in Nuclear Power Plants: Insights from NRC’s Maintenance Team Inspection Reports, A. Fresco and M. Subudhi; 150 Reactor Shutdown Experience, Compiled by J. W. Cletcher; 153 Selected Safety-Related Events, Compiled by G. A. Murphy; RECENT DEVELOPMENTS: 158 Reports, Standards, and Safety Guides, D. S. Queener; 168 Proposed Rule Changes as of Dec. 31, 1993; ANNOUNCEMENTS: 177 Symposium on Radioactive and Mixed Waste—Risk as a Basis for Waste Classification; 177 1995 Incineration Conference 178 Ninth Power Plant Dynamics Control and Testing Symposium; 174 The Authors

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Probabilistic Assessment and Uncertainty Analysis of CO2 Storage Capacity of the Morrow B Sandstone—Farnsworth Field Unit

This paper presents probabilistic methods to estimate the quantity of carbon dioxide (CO2) that can be stored in a mature oil reservoir and analyzes the uncertainties associated with the estimation. This work uses data from the Farnsworth Field Unit (FWU), Ochiltree County, Texas, which is currently undergoing a tertiary recovery process. The input parameters are determined from seismic, core, and fluid analyses. The results of the estimation of the CO2 storage capacity of the reservoir are presented with both expectation curve and log probability plot. The expectation curve provides a range of possible outcomes such as the P90, P50, and P10. The deterministic value is calculated as the statistical mean of the storage capacity. The coefficient of variation and the uncertainty index, P10/P90, is used to analyze the overall uncertainty of the estimations. A relative impact plot is developed to analyze the sensitivity of the input parameters towards the total uncertainty and compared with Monte Carlo. In comparison to the Monte Carlo method, the results are practically the same. The probabilistic technique presented in this paper can be applied in different geological settings as well as other engineering applications.

03 NATURAL GAS↗
NASA NTRS2002

Large Scale Deformation of the Western U.S. Cordillera

The overall objective of the work that was conducted was to understand the present-day large-scale deformations of the crust throughout the western United States and in so doing to improve our ability to assess the potential for seismic hazards in this region. To address this problem, we used a large collection of Global Positioning System (GPS) networks which spans the region to precisely quantify present-day large-scale crustal deformations in a single uniform reference frame. Our results can roughly be divided into an analysis of the GPS observations to infer the deformation field across and within the entire plate boundary zone and an investigation of the implications of this deformation field regarding plate boundary dynamics.

Bennett, Richard A.↗