Citronelle 2013 DAS VSP
The data in this archive are the distributed acoustic sensor (DAS) and well log data used in Daley, et al, 2016. Both raw and processed data are included
borehole↗
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Results for “seismic data processing”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Subsurface stress criticality associated with fluid injection and determined using machine learning
Machine-learning methods and apparatus are disclosed to determine critical state or other parameters related to fluid-driven failure of a terrestrial locale impacted by anthropogenic activities such as hydraulic fracturing, hydrocarbon extraction, wastewater disposal, or geothermal harvesting. Acoustic emission, seismic waves, or other detectable indicators of microscopic processes are sensed. A classifier is trained using time series of microscopic data along with corresponding data of critical state or failure events. In disclosed examples, random forests and artificial neural networks are used, and grid-search or EGO procedures are used for hyperparameter tuning. Once trained, the classifier can be applied to live data from a fluid injection locale in order to assess a frictional state, assess seismic hazard, assess permeability, make predictions regarding a future fluid-driven failure event, or drive engineering solutions for mitigation or remediation. Variations are disclosed.
Johnson, Paul Allan↗
Relaxation algorithms for matrix completion, with applications to seismic travel-time data interpolation
Travel time tomography is used to infer the underlying three-dimensional wavespeed structure of the Earth by fitting seismic travel time data collected at surface stations. Data interpolation and denoising techniques are important pre-processing steps that use prior knowledge about the data, including parsimony in the frequency and wavelet domains, low-rank structure of matricizations, and local smoothness. In this work, we show how local smoothness structure can be combined with low rank constraints using level-set optimization formulations, and develop a new relaxation algorithm that can efficiently solve these joint problems. In the seismology setting, we use the approach to interpolate missing stations and de-noise observed stations. The new approach is competitive with alternative algorithms, and offers new functionality to interpolate observed data using both smoothness and low rank structure in the presence of data fitting constraints.
constrained optimization↗
An advanced joint inversion system for CO 2 storage modeling with large date sets for characterization and real-time monitoring-enhancing storage performance and reducing failure risks under uncertainties
As large-scale, commercial storage projects become operational, the problem of utilizing information from diverse sources becomes more critically important. In this project, we developed, tested, and applied an advanced joint data inversion system for CO 2 storage modeling with large data sets for use in site characterization and real-time monitoring. Emphasis was on the development of advanced and efficient computational algorithms for joint inversion of hydro-geophysical data, coupled with state-of-the-art forward process simulations. The developed system consists of (1) inversion tools using characterization data, such as 3D seismic survey (amplitude images), borehole log and core data, as well as hydraulic, tracer and thermal tests before CO 2 injection, (2) joint inversion tools for updating the geologic model with the distribution of rock properties, thus reducing uncertainty, using hydro-geophysical monitoring data, and (3) highly efficient algorithms for directly solving the dense or sparse linear algebra systems derived from the joint inversion. The system combines methods from stochastic analysis, fast linear algebra, and high performance computing. The developed joint inversion tools have been tested through synthetic CO 2 storage examples.
01 COAL, LIGNITE, AND PEAT↗
The preliminary results: Seismic ambient noise Rayleigh wave tomography around Merapi volcano, central Java, Indonesia
Ambient noise tomography is relatively a new method for imaging the shallow structure of the Earth subsurface. We presents the application of this method to produce a Rayleigh wave group velocity maps around the Merapi Volcano, Central Java. Rayleigh waves group velocity maps were reconstructed from the cross-correlation of ambient noise recorded by the DOMERAPI array which consists 43 broadband seismometers. In the processing stage, we first filtered the observation data to separatethe noise from the signal that dominated by the strong volcanic activities. Next, we cross-correlate the filtered data and stack to obtain the Green’s function for all possible station pairs. Then we carefully picked the peak of each Green’s function to estimate the dispersion trend and appliedMultiple Filter Technique to obtain the dispersion curve. Inter-station group velocity curvesare inverted to produceRayleigh wave group velocity maps for periods 1 to 10 s. The resulted Rayleigh group velocity maps show the interesting features around the Merapi Volcano which generally agree with the previous studies. Merapi-Lawu Anomaly (MLA) is emerged as a relatively low anomaly in our group velocity maps.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Frequency–Magnitude Statistics of Laboratory Foreshocks Vary With Shear Velocity, Fault Slip Rate, and Shear Stress
Understanding the nucleation phase of earthquakes is key for advancing earthquake hazard assessment and improving earthquake early warning systems. However, little progress has been made in this area due to a poor understanding of nucleation processes and incomplete seismic and fault zone measurements. The ability to integrate measured fault zone properties with seismic data could significantly improve our understanding of how earthquakes begin and whether there are systematic variations in seismic properties preceding failure. In this work, we use high-resolution laboratory measurements of fault zone properties along with acoustic emission data to document temporal variations of foreshock properties. Our data show that foreshock size increases with shear stress, loading rate, and fault slip rate. We propose that the preseismic fault slip rate and fault zone thickness (i.e., porosity) work in concert to modulate foreshock properties.
15 GEOTHERMAL ENERGY↗
Appendices for Geothermal Exploration Artificial Intelligence Report
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especially regarding finding locations for viable EGS sites. This submission includes the appendices and reports formerly attached to the Geothermal Exploration Artificial Intelligence Quarterly and Final Reports. The appendices below include methodologies, results, and some data regarding what was used to train the Geothermal Exploration AI. The methodology reports explain how specific anomaly detection modes were selected for use with the Geo Exploration AI. This also includes how the detection mode is useful for finding geothermal sites. Some methodology reports also include small amounts of code. Results from these reports explain the accuracy of methods used for the selected sites (Brady Desert Peak and Salton Sea). Data from these detection modes can be found in some of the reports, such as the Mineral Markers Maps, but most of the raw data is included the DOE Database which includes Brady, Desert Peak, and Salton Sea Geothermal Sites.
15 GEOTHERMAL ENERGY↗
Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs which are titled Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files are used with the Geothermal Exploration Artificial Intelligence for the Salton Sea Geothermal Site to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Salton Sea Geothermal Site.
15 GEOTHERMAL ENERGY↗
Physics-based Induced Earthquake Forecasting: Process Understanding, and Hazards Mitigation
Disposal of saltwater co-produced with oil and gas is linked to elevated seismicity in the Central and Midwest US. There is a concern that these events may lead to widespread damage and an overall increase in seismicity. Thus an improved understanding of the spatially and temporally variable deformation and stress field associated with fluid injection operation is critically necessary for evaluating time-varying seismic hazards. Despite the improvements in seismic monitoring capacity and the resulting decrease in the magnitude detection threshold, estimates of induced earthquake probability remain elusive due to insufficient models incapable of accounting for the complex physics governing the process of induced seismicity. The proposed research effort will comprehensively analyze, integrate, and interpret geodetic, injection, and seismic data in the vicinity of the injection sites in Oklahoma to resolve the 4-dimensional distribution of pore pressure and stress in the shallow crust. This project, in particular, is focused on exploring the statistical relation between injection operation and increased earthquake hazard. The amplitude of and the extent to which pore pressure changes are determined by some factors, in particular, the hydrogeological properties of the rocks, such as diffusivity. Thus the available deformation data will be used to constrain hydrogeological properties of the medium, to accurately resolve the evolution of crustal stresses due to fluid injection. Having the time-varying models of stress changes, a statistical framework will be implemented to estimate the time-dependent probability of large earthquakes on the nearby fault systems. These data and models help to improve seismic hazard estimates and aid in constructing operational-induced earthquake forecast models. This information can also be integrated into the updated U.S. National Seismic Hazard Map, which local communities and authorities use in their earthquake risk estimates and mitigation efforts.
58 GEOSCIENCES↗
Gulf of Mexico miocene CO₂ site characterization mega transect
This project characterized the Miocene-age sub-seafloor stratigraphy in the near-offshore portion of the Gulf of Mexico adjacent to the Texas coast. The large number of industrial sources of carbon dioxide (CO₂) in coastal counties and the high density of onshore urbanization and environmentally sensitive areas make this offshore region extremely attractive for long-term storage of carbon dioxide emissions from industrial sources (CCS). The study leverages dense existing geologic data from decades of hydrocarbon exploration in and around the study area to characterize the regional geology for suitability and storage capacity. Primary products of the study include: regional static storage capacity estimates, sequestration “leads” and prospects with associated dynamic capacity estimates, experimental studies of CO₂-brine-rock interaction, best practices for site characterization, a large-format ‘Atlas’ of sequestration for the study area, and characterization of potential fluid migration pathways for reducing storage risks utilizing novel high-resolution 3D (HR3D) seismic surveys. In addition, three subcontracted studies address source-to-sink matching optimization, offshore well bore management and environmental aspects. The various geologic data and interpretations are integrated and summarized in a series of cross-sections and maps, which represent a primary resource for any near-term commercial deployment of CCS in the area. The regional study characterized and mapped important geologic features (e.g., Clemente-Tomas fault zone, the regionally extensive Marginulina A and Amphistegina B confining systems, etc.) that provided an important context for regional static capacity estimates and specific sequestration prospects of the study. A static capacity estimate of the majority of the Study area (14,467 mi 2 ) was estimated at 86 metric Gigatonnes. While local capacity estimates are likely to be lower due to reservoir-scale characteristics, the offshore Miocene interval is a storage resource of National interest for providing CO₂ storage as an atmospheric emissions abatement strategy. The natural petroleum system was used as an analog to infer seal quality and predict possible migration pathways of fluids in an engineered system of anthropogenic CO₂ injection and storage. The regional structural features (e.g., Clemente-Tomas fault zone) that exert primary control on the trapping and distribution of Miocene hydrocarbons are expected to perform similarly for CCS. Industrial-scale CCS will require storage capacity utilizing well-documented Miocene hydrocarbon (dominantly depleted gas) fields and their larger structural closures, as well as barren (unproductive, brine-filled) closures. No assessment was made of potential for CO₂ utilization for enhanced oil and gas recovery. The use of 3D numerical fluid flow simulations have been used in the study to greatly assist in characterizing the potential storage capacity of a specific reservoir. Due to the complexity of geologic systems (stratigraphic heterogeneity) and inherent limitations on producing a 3D geologic model, these simulations are typically simplified scenarios that explore the influence of model property variability (sensitivity study). A specific site offshore San Luis Pass (southern Galveston Island) was undertaken successfully, indicating stacked storage potential. Downscaling regional capacity estimates to the local scale (and the inverse) has proven challenging, and remains an outstanding gap in capacity assessments. In order to characterize regional seal performance and identify potential brine and CO₂ leakage pathways, results from three high-resolution 3D (HR3D) seismic datasets acquired by the study using novel HR3D (P-Cable) acquisition system showed steady and significant improvements in data quality because of improved acquisition and processing technique. Finely detailed faults and stratigraphy in the shallowest 1000 milliseconds (~800 m) of data allowed for the identification and mapping of unconformable surfaces including what is probably a surface associated with the last Pleistocene glacial lowstand. The identification of a previously unrecognized (in commercial seismic data) gas chimney that was clearly defined in the 2013 HR3D survey, indicates that HR3D surveys may be useful as both a characterization tool for the overburden of a potential carbon sequestration site and as an additional monitoring tool for future engineered injection sites. Geochemical modeling indicated that injection of CO₂ would result in minor dissolution of calcite, K-feldspar and albite. In addition, modeling of typical brines in Miocene age rocks indicate that approximately 5% of injection capacity would result from CO₂ dissolution into the brine. After extensive searches, no rock samples of the Marginulina A and Amphistegina B seals (“caprocks”) were obtained, but analyses of available core samples of other Miocene age mudrocks (seals or caprocks) indicate that they have sealing ability sufficient for potential CO 2 storage in underlying sandstone units.
01 COAL, LIGNITE, AND PEAT↗
Acoustic Energy Release During the Laboratory Seismic Cycle: Insights on Laboratory Earthquake Precursors and Prediction
Abstract Machine learning can predict the timing and magnitude of laboratory earthquakes using statistics of acoustic emissions. The evolution of acoustic energy is critical for lab earthquake prediction; however, the connections between acoustic energy and fault zone processes leading to failure are poorly understood. Here, we document in detail the temporal evolution of acoustic energy during the laboratory seismic cycle. We report on friction experiments for a range of shearing velocities, normal stresses, and granular particle sizes. Acoustic emission data are recorded continuously throughout shear using broadband piezo‐ceramic sensors. The coseismic acoustic energy release scales directly with stress drop and is consistent with concepts of frictional contact mechanics and time‐dependent fault healing. Experiments conducted with larger grains (10.5 μm) show that the temporal evolution of acoustic energy scales directly with fault slip rate. In particular, the acoustic energy is low when the fault is locked and increases to a maximum during coseismic failure. Data from traditional slide‐hold‐slide friction tests confirm that acoustic energy release is closely linked to fault slip rate. Furthermore, variations in the true contact area of fault zone particles play a key role in the generation of acoustic energy. Our data show that acoustic radiation is related primarily to breaking/sliding of frictional contact junctions, which suggests that machine learning‐based laboratory earthquake prediction derives from frictional weakening processes that begin very early in the seismic cycle and well before macroscopic failure.
58 GEOSCIENCES↗
Identification of Water-Saturated Zones in a Protective Hydraulic Earthen Structure by Synchronous Electromagnetic and Seismic Sounding
Results of field experiments in synchronized investigation of the protection embankment of the tailing pond of JSC Kovdor Mining and Processing Plant by means of different wave methods of electromagnetic and seismic sounding are presented. A comparative analysis of the data is carried out by means of which boundaries of zones of different degrees of water saturation of the embankment soils may be reliably established. The ranges of velocity of the electromagnetic wave and range of values of the ratio of the velocities of the longitudinal and transverse elastic wave in the transition from dry dense soil of the embankment to moistened soil right up through water-saturated soil are determined.
42 ENGINEERING↗
Small Scale Field Test Demonstrating CO 2 Sequestration In Arbuckle Saline Aquifer And By CO 2 -Eor At Wellington Field, Sumner County, Kansas
The objectives of this project are to understand the processes that occur when a maximum of 70,000 metric tonnes of CO 2 are injected into two different formations to evaluate the response in different lithofacies and depositional environments. The evaluation will be accomplished through the use of both in situ and indirect MVA (monitoring, verification, and accounting) technologies. The project will optimize for carbon storage accounting for 99% of the CO 2 using lab and field testing and comprehensive characterization and modeling techniques. Site characterization and CO 2 injection should demonstrate state-of-the-art MVA tools and techniques to monitor and visualize the injected CO 2 plume and to refine geomodels developed using nearly continuous core, exhaustive wireline logs, and well tests and a multi-component 3-D seismic survey. Reservoir simulation studies will map the injected CO 2 plume and estimate tonnage of CO 2 stored in solution, as residual gas, and by mineralization and integrate MVA results and reservoir models shall be used to evaluate CO 2 leakage. A rapid-response mitigation plan was developed to minimize CO 2 leakage and provide a comprehensive risk management strategy. The CO 2 was intended to be supplied from a reliable facility and have an adequate delivery and quality of CO 2 . However, several unforeseen circumstances complicated this plan: (1) the initially negotiated CO 2 supply facility went offline and contracts associated with CO 2 supply had to be renegotiated, (2) a UIC Class VI permit proved to be difficult to obtain due to the experimental nature of the project. Both subjects are detailed in separate deliverables attached to this report. The CO 2 enhanced oil recovery (EOR) and geologic storage in Mississippian carbonate reservoir was sucessully deployed. Approximately 20,000 metric tons of CO 2 was injected in the upper part of the Mississippian reservoir to verify CO 2 EOR viability in carbonate reservoirs and evaluate a potential of transitioning to geologic CO 2 storage through EOR. A total of 1,101 truckloads, 19,803 metric tons—an average of 120 tonnes per day—were delivered over the course of injection that lasted from January 9 to June 21, 2016. After cessation of CO 2 injection, the KGS 2-32 well was converted to water injector and continues to operate. CO 2 EOR progression in the field was monitored weekly with fluid level, temperature, and production recording and formation fluid composition sampling. It is important to note that normally, CO 2 EOR pilots are less efficient than commercial operations due to lack of directional and precise well control, lack of surface facilities for CO 2 recycling, and other factors. As a result of this pilot CO 2 injection, the observed incremental average oil production increase was ~68% with only ~18% of injected CO 2 produced back. Decline curve analysis forecasts of additional cumulative oil produced were 32.44M STB to the end of 2027. Wellington Mississippian pilot efficiency by the end of forecast calculations is 11 MCF per barrel of produced oil. Using 32M STB oil production and $1,964,063 cost of CO 2 , CO 2 EOR cost per barrel of oil production is ~$60. Simple but robust monitoring technologies proved to be very efficient in detecting and locating CO 2 . High CO 2 reservoir retentions with low yields within an actively producing field could help to estimate real-world risks of CO 2 geological storage for future projects. The Wellington Field CO 2 EOR was executed in a controlled environment with high efficiency. This case study proves that CO 2 EOR could be successfully applied in Kansas carbonate reservoirs if CO 2 sources and associated infrastructure are available. Recent developments in unconventional resources development in Mid-Continent USA and associated large volume disposal of backflow water and the resulting seismic activity have brought more focus and attention to the Arbuckle Group in southern Kansas. Despite the commercial interest, limited essential information about reservoir properties and structural elements has impeded the management and regulation of disposal, an issue brought to the forefront by recent seismicity in and near areas of large volumes and rates of brine disposal. The Kansas Geological Survey (KGS) collected, compiled, and analyzed available data, including well logs, core data, step rate tests, drill stem tests, 2-D and 3-D seismic data, water level measurements, and others types of data. Several exploratory wells were drilled and core was collected and modern suites of logs were analyzed. Reservoir properties were populated into several site-specific geological models. The geological models illustrate the highly heterogeneous nature of the Arbuckle Group. Vertical and horizontal variability results in several distinct hydro-stratigraphic units that are the result of both depositional and diagenetic processes. During the course of this project, it has been demonstrated that advanced seismic interpretation methods can be used successfully for characterization of the Mississippian reservoir and Arbuckle saline aquifer. Analysis of post-stack 3-D seismic data at the Mississippian reservoir showed the response of a gradational velocity transition. Pre-stack gather analysis showed that porosity zones of the Mississippian and Arbuckle reservoirs exhibit characteristic amplitude versus offset (AVO) response. Simultaneous AVO inversion estimated P- and S-impedances. The 3-D survey gather azimuthal anisotropy analysis (AVAZ) provided information about the fault and fracture network and showed good agreement to the regional stress field and well data. Mississippian reservoir porosity and fracture predictions agreed well with the observed mobility of injected CO 2 in KGS well 2-32. Fluid substitution modeling predicted acoustic impedance reduction in the Mississippian carbonate reservoir introduced by the presence of CO 2 . Seismicity in the United States midcontinent has increased by orders of magnitude over the past decade. Spatiotemporal correlations of seismicity to wastewater injection operations have suggested that injection-related pore fluid pressure increases are inducing the earthquakes. In this investigation, we examine earthquake occurrence in southern Kansas and northern Oklahoma and its relation to the change in pore pressure. The main source of data comes from the Wellington Array in the Wellington oil field, in Sumner County, Kansas, which has monitored for earthquakes in central Sumner County, Kansas, since early 2015. The seismometer array was established to monitor CO 2 injection operations at Wellington Field. Although no seismicity was detected in association with the spring 2016 Mississippian CO 2 injection, the array has recorded more than 2,500 earthquakes in the region and is providing valuable understanding to induced seismicity. A catalog of earthquakes was built from this data and was analyzed for spatial and temporal changes, stress information, and anisotropy information. The region of seismic concern has been shown to be expanding through use of the Wellington earthquake catalog, which has revealed a northward progression of earthquake activity reaching the metropolitan area of Wichita. The stress orientation was also calculated from this earthquake catalog through focal mechanism inversion. The calculated stress orientation was confirmed through comparison to other stress measurements from well data and previous earthquake studies in the region. With this knowledge of the stress orientation, the anisotropy in the basement could be understood. This allowed for the anisotropy measurements to be correlated to pore pressure increases. The increase in pore pressure was monitored through time-lapse shear-wave anisotropy analysis. Since the onset of the observation period in 2010, the orientation of the fast shear wave has rotated 90°, indicating a change associated with critical pore pressure build up. The time delay between fast and slow shear wave arrivals has increased, indicating a corresponding increase in anisotropy induced by pore pressure rise. In-situ near-basement fluid pressure measurements corroborate the continuous pore pressure increase revealed by the shear-wave anisotropy analysis over the earthquake monitoring period. This research is the first to identify a change in pore fluid pressure in the basement using seismological data and it was recently published in the AAAS journal Science Advances (Nolte et al., 2017). The shear-wave splitting analysis is a novel application of the technique, which can be used in other regions to identify an increase in pore pressure. This increasing pore fluid pressure has become more regionally extensive as earthquakes are occurring in southern Kansas, where they previously were absent. These monitoring techniques and analyses provide new insight into mitigating induced seismicity’s impact on society.
02 PETROLEUM↗
Walker Ranch 3D seismic images
Amplitude images (both vertical and depth slices) extracted from 3D seismic reflection survey over area of Walker Ranch area (adjacent to Raft River). Crossline spacing of 660 feet and inline of 165 feet using a Vibroseis source. Processing included depth migration. Micro-earthquake hypocenters on images. Stratigraphic information and nearby well tracks added to images. Images are embedded in a Microsoft Word document with additional information. Exact location and depth restricted for proprietary reasons. Data collection and processing funded by Agua Caliente. Original data remains property of Agua Caliente.
15 GEOTHERMAL ENERGY↗
High-Quality Revision of the Israeli Seismic Bulletin
Seismic bulletins, with trustworthy phase picks, origin times, and source locations are key for regional seismic studies, such as travel-time (TT) tomography, attenuation tomography, and anisotropy studies. To lay the groundwork for such studies in Israel, we revised the seismic bulletin of Israel and the surrounding area and obtained a trustworthy TT data set. From the earthquake and explosion bulletins of the Geophysical Institute of Israel, we compiled a starting data set of about 123,000 earthquakes and explosions that occurred during the past 40 yr. After screening out the poorly recorded events, we were left with a data set of ~38,000 well-recorded events. We then revised the remaining data set in two consecutive steps. In the first, we reviewed and updated station metadata, including changes in station metadata parameters over time. In the second step, we jointly relocated a list of selected seismic events, using the Bayesian hierarchical location software package (BayesLoc) of Myers et al. (2007) that performs joint relocation of multiple events. We observed striking dissimilarities between the spatial distributions of the newly relocated catalog and the initial locations. Although the depth distribution of the starting catalog is trimodal with peaks at 0, 5, and 10 km, the distribution in this study is unimodal, with a broad peak between 7.5 and 12.5 km. By differencing the observed arrival times and the origin times obtained through relocation with BayesLoc, we obtained a revised TT database that consists of 261,336 Pg, 132,876 Pn, 114,816 Sg, and 60,394 Sn arrivals, from a set of 30,458 jointly relocated seismic sources. In this work, we compared prerevision and postrevision TTs as a function of epicentral distance and concluded that the revised data set contains far fewer outliers and inconsistencies than the original data set. The revised TT data set may be used for seismic studies, such as TT tomography, attenuation tomography, and anisotropy studies.
58 GEOSCIENCES↗
CLEAP Project: OR-SAGE Analysis for MT, UT, and CO States
The OR-SAGE tool is designed to use industry-accepted practices in screening sites and then employ the proper array of data sources through the considerable computational capabilities of GIS technology available at ORNL. The tool was developed to screen the potential for NPP siting on a national and regional basis. However, because of the tool granularity, it is often focused specifically on the immediate area around user sites of interest. If data center siting parameters can be added to OR-SAGE, the ability to evaluate data center siting on a localized scale will be beneficial.1 More than 60 data sets have been collected and processed by ORNL to develop exclusionary, avoidance, and suitability criteria for screening sites for a variety of power generation types, including nuclear power plants. Available site evaluation parameters include population density, slope, seismic activity, proximity to cooling-water sources, proximity to hazard facilities, avoidance of protected lands and floodplains, susceptibility to landslide hazards, and many others. All siting parameters should be considered as flags to inform siting decisions and should not be used to rule in or rule out any NPP site. Once data center siting parameters are identified, appropriate data sets will be collected and processed. The OR-SAGE process is very versatile. Essentially, OR-SAGE is a visual, relational database. The database partitions the contiguous United States, a total of 720 million hectares (~1.8 billion acres), into 100-m by 100-m (1 hectare or ~2.5 acre) cells. The database is tracking just under 700 million individual land cells. Successive suitability criterion is applied to each cell in the database. User-specified thresholds can be applied to each siting parameter data layer. In this manner, a variety of scenarios can be quickly and thoroughly evaluated. Data can be added and/or revised within OR-SAGE to address user interests. Siting security assessment capability is currently being added to OR-SAGE. Security is expected to be of concern at data centers whether it is collocated with a nuclear power generating technology or not. If data center is collocated with a nuclear power generating source, the security threat attractiveness level of both will likely increase. It will be of additional benefit if a potential data center site is also assessed for security vulnerability.
97 MATHEMATICS AND COMPUTING↗
Evaluation of Station Performance of the Idaho National Laboratory Seismic Monitoring Network Using Network Detection Thresholds
The Idaho National Laboratory (INL) Seismic Monitoring Network is located in eastern Idaho and monitors a portion of the intermountain seismic belt. It has been in place for 50 yr and has undergone several major changes, the most recent of which has been the transition to the Antelope real‐time acquisition system and the implementation of automatic phase picking algorithms to aid in analysis. This study discusses the efforts to evaluate the performance of the INL seismic monitoring network (and other surrounding stations) using the new real‐time acquisition system. The method outlined by Wilson et al. (2021) is used to develop an empirical relationship between the observability of local earthquakes as a function of magnitude and distance. This relationship is used to produce detection thresholds for Pwaves for all stations of interest. The INL seismic network has two main goals: monitor tectonic‐and volcanic‐related events and measure ground motions for input into seismic hazard analysis. Because of these two overall objectives, several seismic stations have been installed near critical facilities and, therefore, are not as quiet as stations that are used primarily for earthquake detection. This is reflected in their detection thresholds, which are much smaller for stations away from facilities. This study shows that the INL Seismic Monitoring Network is able to detect earthquakes near INL facilities with M L > 1.2, with redundancies built in to ensure this sensitivity even if data became unavailable from some stations. This study also shows “holes” in the monitoring network where the detection of smaller earthquakes is highly dependent on sparsely placed seismic stations. In conclusion, the results of this study will be used to govern plans for expansion of earthquake monitoring in Idaho and the surrounding region and to fine‐tune the detection thresholds for individual stations.
58 - GEOSCIENCES↗
Identification of Faults Susceptible to Induced Seismicity (Final Report)
Central to the work documented in this report is the capability of geocellular models to represent the geologic conceptual model updated with fault identification from machine learning and joint inversion modeling of microseismic data measured and recorded as a consequence of CO 2 injection at a field demonstration site: the Illinois Basin - Decatur Project (IBDP). This work required seven unique geocellular models with 100s of simulated variations to gain a very high degree of confidence in the identification of geologic features present that contributed to induced microseismicity at IBDP. All forward modeling: pressure modeling, stress modeling, and seismic modeling used the same geologic conceptual model and representations of that model at different scales. The pressure modeling and poroelastic modeling created “snapshots” of pore pressure and stress field changes at different times during CO 2 injection, in which microseismic events were clustered (in time). These pressure and stress snapshots, within the framework and architecture of the geologic conceptual model via the geocellular model, informed the single fault and fault network models to ascertain the likelihood of fault movement (seismic or aseismic). The outcomes of the pressure, stress, and fault/fault network (seismic) modeling confirmed that the faults in the geologic conceptual model in Task 2 were likely the source of microseismic events measured at IBDP and acted as conduits for pressure to be transmitted from the injection interval into the Precambrian crystalline basement rock. This closely coordinated and integrated unique modeling approach was conducted to prove the viability of our proposed workflow 1) to better resolve crystalline basement faults, 2) detect subseismic faults that could be activated by injection, 3) increase the certainty in fault detection and their susceptibility to release seismic energy, and 4) understand transmission of pressure vertically from the well to the underlying fractured crystalline basement. The proposed methodology was effective in guiding an iterative process of calibrating forward modeling results based on similar geocellular models while honoring the geologic conceptual model (i.e., characterization data and knowledge of regional geology); this led to higher level of certainty in the identification of fault/faults zones to control seismicity and transmission of pressure to the regions of recorded and located injection induced seismicity.
58 GEOSCIENCES↗