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Big Data Meets Geothermal Exploration (CRADA Final Report)

As part of the Cyclotron Road program, Zanskar Geothermal & Minerals, Inc. investigated the application of micro-earthquake and ambient noise seismology methods to imaging and characterizing the structural characteristics and hydrothermal flux of subsurface faults. Significant advances in what could be resolved were enabled by two major developments in seismology: 1) the availability of large-n arrays of low-cost seismometers, and 2) the availability of increased computational power and semi-automated data reduction algorithms. In tandem, these advances may improve the signal-to-noise ratio and spatial precision of the data collected and enable higher-resolution characterization of subsurface fracture systems and their spatio-temporal evolution. These tools supported efforts to reduce dry-hole risk and to improve wellfield productivity for geothermal resource development. In particular, two applications of these advances were evaluated: 1) fracture-seismic imaging, which was used to detect ambient emissions from fluid-filled fractures, and 2) reservoir tomography, which used information about travel paths, source locations, and source parameters of micro-earthquakes to identify areas of enhanced permeability. Integration of these methods provided guidance for siting wells and served as prior constraints for reservoir models, informing forecasts of power potential and production and injection strategies aimed at minimizing temperature decline and improving overall resource productivity.

15 GEOTHERMAL ENERGY

Utah FORGE: Neubrex Well 16B(78)-32 DAS Data - April, 2024

This dataset comprises Distributed Acoustic Sensing (DAS) data collected from the Utah FORGE monitoring well 16B(78)-32 (the producer well) during hydraulic fracture stimulation operations conducted in April 2024. The data were acquired continuously over the stimulation period at a temporal sampling rate of 10,000 Hz (10 kS/s) and a spatial resolution of approximately 3.35 feet (1.02109 meters). The measurements were captured using a Neubrex NBX-S4100 Time Gated Digital DAS interrogator unit connected to a single-mode fiber optic cable, which was permanently installed within the casing string. All recorded channels correspond to downhole segments of the fiber optic cable, from a measured depth (MD) of 5,369.35 feet to 10,352.11 feet. The DAS data reflect raw acoustic energy generated by physical processes within and surrounding the well during stimulation activities at wells 16A(78)-32 and 16B(78)-32. These data have potential applications in analyzing cross-well strain, far-field strain rates (including microseismic activity), induced seismicity, and seismic imaging. Metadata embedded in the attributes of the HDF5 files include detailed information on the measured depths of the channels, interrogation parameters, and other acquisition details. The dataset also includes a recording of a seminar held on September 19, 2024, where Neubrex's Chief Operating Officer presented insights into the data collection, analysis, and preliminary findings. The raw data files, stored in HDF5 format, are organized chronologically according to the recording intervals from April 9 to April 24, 2024, with each file corresponding to a 12-second recording interval.

15 GEOTHERMAL ENERGY

Fluid flow near the surface of earth's outer core

This review examines the recent attempts at extracting information on the pattern of fluid flow near the surface of the outer core from the geomagnetic secular variation. Maps of the fluid flow at the core surface are important as they may provide some insight into the process of the geodynamo and may place useful constraints on geodynamo models. In contrast to the case of mantle convection, only very small lateral variations in core density are necessary to drive the flow; these density variations are, by several orders of magnitude, too small to be imaged seismically; therefore, the geomagnetic secular variation is utilized to infer the flow. As substantial differences exist between maps developed by different researchers, the possible underlying reasons for these differences are examined with particular attention given to the inherent problems of nonuniqueness.

Bloxham, Jeremy

Performance Evaluation Modeling of Network Sensors

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

probability of detection

Plate Margin Deformation and Active Tectonics Along the Northern Edge of the Yakutat Terrane in the Saint Elias Orogen, Alaska and Yukon, Canada

The northwest directed motion of the Pacific plate is accompanied by migration and collision of the Yakutat terrane into the cusp of southern Alaska. The nature and magnitude of accretion and translation on upper crustal faults and folds is poorly constrained, however, due to pervasive glaciation. In this study we used high-resolution topography, geodetic imaging, seismic, and geologic data to advance understanding of the transition from strike-slip motion on the Fairweather fault to plate margin deformation on the Bagley fault, which cuts through the upper plate of the collisional suture above the subduction megathrust. The Fairweather fault terminates by oblique-extensional splay faulting within a structural syntaxis, allowing rapid tectonic upwelling of rocks driven by thrust faulting and crustal contraction. Plate motion is partly transferred from the Fairweather to the Bagley fault, which extends 125 km farther west as a dextral shear zone that is partly reactivated by reverse faulting. The Bagley fault dips steeply through the upper plate to intersect the subduction megathrust at depth, forming a narrow fault-bounded crustal sliver in the obliquely convergent plate margin. Since . 20 Ma the Bagley fault has accommodated more than 50 km of dextral shearing and several kilometers of reverse motion along its southern flank during terrane accretion. The fault is considered capable of generating earthquakes because it is linked to faults that generated large historic earthquakes, suitably oriented for reactivation in the contemporary stress field, and locally marked by seismicity. The fault may generate earthquakes of Mw <= 7.5.

Bruhn, Ronald L.

NASA Tech Briefs, November 2012

The topics include: Visual System for Browsing, Analysis, and Retrieval of Data (ViSBARD); Time-Domain Terahertz Computed Axial Tomography NDE System; Adaptive Sampling of Time Series During Remote Exploration; A Tracking Sun Photometer Without Moving Parts; Surface Temperature Data Analysis; Modular, Autonomous Command and Data Handling Software with Built-In Simulation and Test; In-Situ Wire Damage Detection System; Amplifier Module for 260-GHz Band Using Quartz Waveguide Transitions; Wideband Agile Digital Microwave Radiometer; Buckyball Nucleation of HiPco Tubes; FACT, Mega-ROSA, SOLAROSA; An Integrated, Layered-Spinel Composite Cathode for Energy Storage Applications; Engineered Multifunctional Surfaces for Fluid Handling; Polyolefin-Based Aerogels; Adjusting Permittivity by Blending Varying Ratios of SWNTs; Gravity-Assist Mechanical Simulator for Outreach; Concept for Hydrogen-Impregnated Nanofiber/Photovoltaic Cargo Stowage System; DROP: Durable Reconnaissance and Observation Platform; Developing Physiologic Models for Emergency Medical Procedures Under Microgravity; Spectroscopic Chemical Analysis Methods and Apparatus; Low Average Sidelobe Slot Array Antennas for Radiometer Applications; Motion-Corrected 3D Sonic Anemometer for Tethersondes and Other Moving Platforms; Water Treatment Systems for Long Spaceflights; Microchip Non-Aqueous Capillary Electrophoresis (MicronNACE) Method to Analyze Long-Chain Primary Amines; Low-Cost Phased Array Antenna for Sounding Rockets, Missiles, and Expendable Launch Vehicles; Mars Science Laboratory Engineering Cameras; Seismic Imager Space Telescope; Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations; A Posteriori Study of a DNS Database Describing Super critical Binary-Species Mixing; Scalable SCPPM Decoder; QuakeSim 2.0; HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler; MPST Software: MoonKommand

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The future of subsurface monitoring: AEC’s breakthroughs in CCS technology

Carbon capture and storage (CCS) has emerged as a key solution in the fight against climate change. However, for CCS to succeed, it is crucial to ensure that the sequestered CO2 stays safely trapped underground. The U.S. Department of Energy (DOE) has emphasized the need for advancements in subsurface monitoring, measurement, reporting, and verification. Aside from caprock integrity failure, the other primary failure points usually involve defective cement in the casing annulus of wellbores or plugged and abandoned wells. In addition, many energy producers (e.g., oil and gas, geothermal) and storage and disposal operators (e.g., H2 and water) must deal with the same issue. Poorly placed or degraded cement can create pathways for gas or fluid to escape from casing annuli and in plugged and abandoned or orphan wells, posing environmental risks. Yet, a reliable and cost-effective way to monitor cement and well integrity over multiple decades is still unavailable. Traditional geophysical methods like 4D seismic imaging and surface-based electromagnetic monitoring lack the resolution and accuracy for detecting these types of failures (Vasco et al., 2022; Fawad and Mondol, 2021). Wireline logging is expensive to run continuously and is obtrusive to the operation. While fiber optics can potentially be a solution, its bulkiness can significantly compromise the cement's integrity. To address these challenges, the Advanced Energy Consortium (AEC) at The University of Texas at Austin’s Bureau of Economic Geology (the Bureau) has been pioneering research in subsurface monitoring using its portfolio of distributed autonomous microfabricated sensors for harsh subsurface environments since 2008. A class of these microsensors [System on a Chip (SoC)] can be mixed in cement and permanently placed without compromising the cement column; the sensors would then communicate with each other or a data acquisition (DAQ) master node. Another class of the AEC microsensors can be fully autonomous, with rechargeable micro-batteries capable of exceeding 100°C, flash memory, and, currently, a pressure and temperature sensor. They are designed to circulate in mud, geothermal fluids, U-loops, or pipelines. They can log data into memory and are unobtrusive to operations. Our team has been working on a multi-year DOE-funded project (DE-FE0031856)—supported by $2.95M in federal funding and $0.75M in cost-matching from the AEC—to demonstrate SoC sensor utility for CO2 leakage monitoring in CCS applications. This multi-institutional collaboration developed a novel sensing architecture utilizing radiofrequency (RF) microsensors embedded within the cement sheath. These sensors detect CO2 migration and are interrogated via a Smart Casing Collar (SCC).

58 GEOSCIENCES

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo

Utah FORGE 5-2419: Seismicity-Permeability Relationships Probed via Nonlinear Acoustic Imaging - 2024 Annual Workshop Presentation

This is a presentation on Seismicity-Permeability Relationships Probed via Nonlinear Acoustic Imaging by Pennsylvania State University, presented by Derek Elsworth. This video slide presentation discussed controls and acoustic signatures of aseismic through seismic evolution of relocation-stability-permeability on fractures in shear-reactivation as a precursor to, and a key predictor of, seismic moment magnitude of prospective triggered-seismicity. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 13, 2024.

15 GEOTHERMAL ENERGY

Helioseismic imaging of sunspots at their antipodes

Recent work by Braun et al. (1988) has shown that sunspots absorb helioseismic waves. It is proposed that sunspot absorption causes a seismic deficit that should be imaged at the antipode of the sunspot. If these images are observable, it should be possible to produce seismic maps of magnetic regions on the far side of the sun. Diagnostic applications would include lifetimes of higher-frequency modes, and possibly rotation of the solar interior and detection of subsurface magnetic structure. Elements of the theory of seismic imaging are outlined. The extention of acoustic holography to solar interior diagnostics in the context of antipodal imaging is proposed.

Lindsey, Charles

RGM: Random Geological Model Generation Package

This Fortran code is to accompany a manuscript to be submitted to Computers & Geosciences, a high-impact, peer-reviewed journal in computer methods for geosciences research. This Fortran code focuses on generation of synthetic geological models using a multi-randomization strategy. Generating high-fidelity synthetic geological models, including realistic seismic reflector migration images, faults, salt bodies, and relative geological time images, is the key for many supervised machine learning methods that aim to delineate faults and other geological properties of interest from seismic migration images. Our package contains two major functionalities: generating 2D synthetic random geological models and generating 3D synthetic random geological models. In each step of the generation process, we set random values for key properties of a geological model to improve the fidelity of the resulting geological model. The package also includes example codes on how to use the random geological model generation subroutines. We name this package RGM – Random Geological Model generation package.

Gao, Kai

Detecting and Characterizing Fracture Zones Using a Convolutional Neural Network

This project directly supports the Geothermal Technologies Office (GTO) objectives outlined in the Multi-Year Program Plan (MYPP) by advancing two key research areas: “Exploration and Characterization” and “Data, Modeling, and Analysis.” This project has successfully demonstrated a pre-drilling ability to image and characterize the distribution and connectivity of subsurface faults and fractures, key parameters for identifying permeable pathways that enable geothermal fluids to circulate and produce energy. Specifically, we developed and implemented innovative machine learning methodologies to enhance geothermal exploration. Large-scale faults were detected using a Convolutional Neural Network (CNN), while small-scale fractures were characterized using a novel Double-Beam Neural Network (DBNN). These tools have proven both technically effective and cost-efficient by reducing reliance on expensive exploratory drilling. Through collaboration with our geothermal industry partner, this research has significantly advanced techniques for identifying hidden geothermal systems and extending the productive lifespan of existing geothermal fields. We applied our methods to two geothermal fields—Soda Lake (Nevada) and Lightning Dock (New Mexico)—to identify shallow steam-charged fracture zones and characterize deep faults at depths of 1.5-2 km. The steam zone identified at the Soda Lake geothermal field showed excellent agreement with prior drilling data, validating the effectiveness of our approaches. In addition, the analysis revealed three new prospective drilling targets for further development and verification. The outcomes of this project improve our scientific understanding of geothermal reservoir behavior, enhance exploration efficiency, extend the economic life of existing geothermal plants. Ultimately, these advancements contribute to GTO’s goal of achieving more sustainable, affordable, and data-driven geothermal energy development across the United States.

15 GEOTHERMAL ENERGY

Fiscal year 1976 progress report on a feasibility study evaluating the use of surface penetrators for planetary exploration

The feasibility of employing penetrators for exploring Mars was examined. Eight areas of interest for key scientific experiments were identified. These include: seismic activity, imaging, geochemistry, water measurement, heatflow, meteorology, magnetometry, and biochemistry. In seven of the eight potential experiment categories this year's progress included: conceptual design, instrument fabrication, instrument performance evaluation, and shock loading of important components. Most of the components survived deceleration testing with negligible performance changes. Components intended to be placed inside the penetrator forebody were tested up to 3,500 g and components intended to be placed on the afterbody were tested up to 21,000 g. A field test program was conducted using tentative Mars penetrator mission constraints. Drop tests were performed at two selected terrestrial analog sites to determine the range of penetration depths for anticipated common Martian materials. Minimum penetration occurred in basalt at Amboy, California. Three full-scale penetrators penetrated 0.4 to 0.9 m into the basalt after passing through 0.3 to 0.5 m of alluvial overburden. Maximum penetration occurred in unconsolidated sediments at McCook, Nebraska. Two full-scale penetrators penetrated 2.5 to 8.5 m of sediment. Impact occurred in two kinds of sediment: loess and layered clay. Deceleration g loads of nominally 2,000 for the forebody and 20,000 for the afterbody did not present serious design problems for potential experiments. Penetrators have successfully impacted into terrestrial analogs of the probable extremes of potential Martian sites.

Blanchard, M. B.

Lower mantle heterogeneity, dynamic topography and the geoid

Density contrasts in the lower mantle, recently imaged using seismic tomography, drive convective flow which results in kilometers of dynamically maintained topography at the core-mantle boundary and at the Earth's surface. The total gravity field due to interior density contrasts and boundary topography predicts the largest wavelength components of the geoid remarkably well. Neglecting dynamic surface deformation leads to geoid anomalies of opposite sign than are observed.

Hager, B. H.

Lower mantle heterogeneity, dynamic topography and the geoid

Density contrasts in the lower mantle, recently imaged using seismic tomography, drive convective flow which results in kilometers of dynamically maintained topography at the core-mantle boundary and at the earth's surface. The total gravity field due to interior density constrasts and boundary topography predicts the largest wavelength components of the geoid remarkably well. Neglecting dynamic surface deformation leads to geoid anomalies of opposite sign than are observed.

Hager, B. H.

Survey Plan For Characterization of the Subsurface Underlying the National Aeronautics and Space Administration's Marshall Space Flight Center in Huntsville, Alabama

Topic considered include: survey objectives; technologies for non-Invasive imaging of subsurface; cost; data requirements and sources; climatic condition; hydrology and geology; chemicals; magnetometry; electrical(resistivity, potential); optical-style imaging; reflection/refraction seismics; gravitometry; photo-acoustic activation;well drilling and borehole analysis; comparative assessment matrix; ground sensors; choice of the neutron sources; logistic of operations; system requirements; health and safety plans.

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Large Meteorite Impacts and Planetary Evolution

The present volume of abstracts of conference papers discusses topics associated with the role of meteorite impacts on the Earth, the moon, and Titan. Particular attention is given to the description of the impact damage and the description of the actual craters. Attention is also given to the Sudbury structure, and the Chicxulub crater. Mineralogical, geophysical, petrographic, seismic and image data are described and discussed.

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