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At least 127 records · Page 7

Machine learning and shallow groundwater chemistry to identify geothermal prospects in the Great Basin, USA

This study discovers various geothermal prospects in the Great Basin, USA based on shallow groundwater chemical (geochemical) data. The geochemical data are expected to include hidden (latent) information that is a proxy for geothermal prospectivity. We processed the sparse geochemical data in the Great Basin at 14,341 locations including 18 attributes. Next, a non-negative matrix factorization with customized k-means clustering is applied to the geochemical data matrix that automatically finds three hidden geothermal signatures representing modestly, moderately, and highly confident geothermal prospects. The algorithm also evaluated the probability of occurrence of these types of resources through the studied region. There is a consistency between regional geothermal prospectivity as estimated by our ML methodology and the traditional play fairway analysis conducted over a portion of the study area. We also identify the dominant data attributes associated with each signature. Finally, our ML analyses allow us to reconstruct attributes from sparse into continuous over the study domain. The predicted continuous attributes can be used for future detailed geothermal explorations in the Great Basin.

15 GEOTHERMAL ENERGY↗

Kilauea Magnetotelluric Dataset

In 2002 and 2003 a collaborative effort was undertaken between Lawrence Berkeley National Laboratory, Sandia National Laboratories, the USGS Menlo Park, the USGS Hawaiian Volcano Observatory, and Electromagnetic Instruments Inc. to study the Kilauea volcano in Hawaii using the magnetotelluric (MT) technique. The work was motivated by a desire to improve understanding of the magma reservoirs and conduits within Kilauea and the East and Southwest Rift zones, which has implications for understanding Kilaueas plumbing system. An improved understanding of the rift zones has implications in understanding large-scale landslides that are generated in the Hilina Slump, which produce significant impacts on coastal communities. Up to eight stations operated simultaneously, with multiple remote reference sites, and data were processed using multi-station robust processing techniques. In total, data were acquired at 70 sites over the Southwest and East rift zones. Good to excellent quality data were obtained even in the harshest conditions, such as those encountered on the fresh lava flows of the East Rift Zone (ERZ), where electrical contact resistances are on the order of 100 kOhm. This data supports the continuing efforts to increase geothermal power on the island of Hawaii. Each of the 70 EDI files are the MT impedance tensors for 1 site. There is also a description of the processing of the data and a site map showing the locations of each site.

15 GEOTHERMAL ENERGY↗

Geothermal potential of Harrat Rahat, Northern Arabian Shield: geological constraints

Arabian Shield offers a strong potential for geothermal energy. However, only a limited amount of exploration effort has taken place. Harrat Rahat is a recent volcanic area located along the Makkah-Madinah-Nafud volcanic line in western Saudi Arabia. This study is oriented to identify the geothermal potential of Harrat Rahat. The geologic data was collected and processed. Here, we focus on evaluating the potential sources of subsurface heat and groundwater. Subsurface heat is based on the age of erupted volcanoes and the expected volume of subsurface magma chambers. An analogy with an existing geothermal field in a similar setting as Mexico suggests that the faults and the coincident seismicity may be associated with higher permeability. It is concluded that Harrat Rahat is characterized by a good geothermal potential for future geothermal energy source production.

58 GEOSCIENCES↗

Noctis Landing: A Proposed Landing Site/Exploration Zone for Human Missions to the Surface of Mars

The proposed Noctis Landing Site/Exploration Zone (LS/EZ) is shown in Figure 1. Our preliminary study suggests that the proposed site meets all key Science and Resources (incl. Civil Engineering) requirements. The site is of significant interest, as the EZ not only offers a large number and wide range of regions of interest (ROIs) for short-term exploration, it is also located strategically at the crossroads between Tharsis and Valles Marineris, which are key for long-term exploration. The proposed site contains Regions of Interest (ROIs) that meet the following Science requirements: -­‐ Access to (1) deposits with a high preservation potential for evidence of past habitability and fossil biosignatures and (2) sites that are promising for present habitability. The site presents a wide variety of ROIs qith likely aqueous features and deposits, including sinous channels and valleys, slope gullies, lobate debris aprons, impact craters with lobate ejecta flows, and "bathtub ring" deposits. Neutron spectrometry also suggests hydrogen is present within the topmost 0.3 m or so of 4 to 10 wt% WEH (Water Equivalent Hydrogen). -­‐ Noachian and/or Hesperian rocks in a stratigraphic context that have a high likelihood of containing trapped atmospheric gases. Collapsed canyon rim material with preserved stratigraphy is abundantly present and accessible. -­‐ Exposures of at least two crustal units that have regional or global extents, that are suitable for radiometric dating, and that have relative ages that sample a significant range of martian geological time. Canyons floors in Ius Chasma, Tithonium Chasma, and plateau tops on Tharsis and in Sinai Planum offer access to distinct crustal units of regional extent. -­‐ Access to outcrops with linked morphological and/or geochemical signatures indicative of aqueous or groundwater/ mineral interactions. Iron and sulfur-bearing deposits on canyon floors in Noctis Labyrinthus, and in Ius Chasma (IC) and Tithonium Chasma (TC) offer many such outcrop options. -­‐ Identifiable stratigraphic contacts and cross-cutting relationships from which relative ages can be determined. In place and collapsed canyon walls in NL, TC, and IC offer such opportunities. -­‐ Other types of ROIs include access points to surrounding plateau top areas for longer term regional exploration. A key attribute of the proposed Noctic Landing site is its strategic location to allow the shortest possible surface excusions to Tharsis and Valles Marineris (VM). VM is the feature and region on Mars that exposes the longest record of Mars' geology and evolution through time. Tharsis is the region of Mars that has experienced the longest and most extensive volcanic history, and might still be volcanically active. Some of the youngest lava flows on Mars have been identified on the western flanks of the Tharsis Bulge, i.e., within driving range of future longrange (500 - 1000 km) pressurized rover traverses. The proposed site also contains ROIs that offer the following Resources (incl. Civil Engineering) characteristics: -­‐ Access to raw material that exhibits the potential to (1) be used as feedstock for water-generating in situ resource utilization (ISRU) processes and (2) yield significant quantities (greater than 100 MT) of water. The raw material is likely in the form of hydrated minerals, and possibly ice/regolith mix. The top of the raw material deposit is at the surface. -­‐ Access to a region where infrastructure can be emplaced or constructed. This region is less than 5 km from the LS and contains flat, stable terrain. The region exhibits evidence for an abundant source of loose regolith. Several deep pits in the area combined with the availability of sand suggests that some natural terrain features can be adapted for construction purposes. -­‐ Access to raw material that exhibits the potential to be used as metal feedstock for ISRU and construction purposes. Iron and sulfur-rich mineral surface deposits have been identified in CRISM data in many locations in this area. Noctis Landing is the lowest-altitude location on Mars that straddles both the Tharsis region (above average geothermal gradients) and Valles Marineris (minimal crustal thickness from surface (valley floor) to a subsurface liquid water table. Noctis Landing has the potential for being an ideal site for eventual deep drilling on Mars to access deep subsurface liquid water and potentially encountering extant life. Available data remains insufficient to fully qualify the Noctis Landing site. Additional remote sensing data (visible, Near and Mid-IR, and radar) and surface reconnaissance via a high-mobility robotic rover are recommended. In particular, it will be important to assess the trafficability of the site, and its potential for yielding water and metals as a resource. Access to plateau tops from the Noctis Landing site on the canyon floor should be demonstrated. Future exploration of the site would also be enhanced significantly by the availability of robotic (tele-operatable) surveying and sample-collecting drones. Testing of the use of such collaborative science and exploration technologies should be conducted at terrestrial sites such as the Haughton-Mars Project site on Devon Island, High Arctic, among others. Note: Noctis Landing is not an official Mars nomenclature name for this location. Because the area of the proposed LS/EZ had no name, and because it is close to Noctis Labyrinthus to the West while being distinct from it, the provisional name Noctis Landing is proposed. Noctis means night in Latin.

Lee, Pascal↗

Evaluation and Optimization of Well Completion Options for the Utah FORGE Site

Orientation and completion for well pairs that have been subjected to multi-zonal stimulation play a critical role in the long-term performance of an Enhanced Geothermal Reservoir. Enhanced geothermal systems often rely on preferential flow along fractures between well injection and production locations. Modeling this preferential flow using discrete fracture networks (DNF) relies on stochastic realizations of the DFN based on geological sampling. Here we present the development of a stochastic optimization methodology to determine well completion options in a discrete fracture network based on using parallel subset simulation. Stochastic optimization will provide insight into regions where placements of the injection and production wells are optimal. An example optimization of well-pair location optimization based on a deterministic-stochastic DFN model representing FORGE follows a discussion of the theory.

15 GEOTHERMAL ENERGY↗

Utah FORGE 1-2409: PetroQuip Energy Services Zonal Isolation Solution for Geothermal Wells - 2024 Annual Workshop Presentation

This is a presentation on the Zonal Isolation Solution for Geothermal Wells by PetroQuip Energy Services, presented by Robert Coon. This video slide presentation discusses the proposed design and development of a multi-stage system consisting of an Open-Hole Packer (OHP), a Locking Bridge Plug (LBP), and a corresponding Locating Profile (LP). This presentation was featured in the Utah FORGE R&D Annual Workshop on August 14, 2024.

15 GEOTHERMAL ENERGY↗

Geothermal Data Gap Analysis Over the Western US

NREL, as part of the Play Fairway Analysis Retrospective, compiled and mapped publicly available geologic and geophysical data in relation to the 2008 USGS geothermal potential analysis. Included in this submission are maps displaying the publicly available data for LIDAR coverage, aeromagnetic coverage, gravity station locations, and geologic map coverage over the Western United States.

15 GEOTHERMAL ENERGY↗

Detectability of geothermal areas using Skylab X-5 data

The results are presented of a study which was undertaken to determine if data from a single near-noon pass of Skylab could be used to detect geothermal areas. The size and temperature requirements for a geothermally heated area to be seen by Skylab S-192 MSS X-5 thermal sensor were calculated. This sensor obtained thermal data with the highest spatial resolution of any nonmilitary satellite system. Only very large hot areas could be expected to be unambiguously recognized with a single data set from this instrument. The study area chosen was The Geysers geothermal field in Sonoma County, California, the only geothermal area of significant size scanned by Skylab. Unfortunately, 95% of the Skylab thermal channel data was acquired within 3 hours of local noon. For The Geysers area only daytime X-5 data were available. An analysis of the thermal channel data (10.2 to 12.5 um) revealed that ground temperatures determined by Skylab were normally distributed. No anomalous hot spots were apparent. Computer enhancement techniques were used to delineate the hottest 100 and 300 ground areas (pixel, 75 m by 75 m) within the study region. It was found that the Skylab MSS with the X-5 thermal detector does not have sufficient spatial resolution to locate unambiguously from daytime data any but the largest and hottest convectively created geothermal features, which in general are prominent enough to have been previously recognized.

Siegal, B. S.↗

Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties

This project developed machine learning (ML) methods, lab data sets, and field data to advance geothermal exploration and geothermal energy production. The work had three focus areas. One involved the development of ML methods to use microearthquakes (MEQs) for imaging geothermal reservoir properties and improving subsurface characterization – most importantly the evolution of permeability within the evolving reservoir. This part of the work included development of ML approaches for automated MEQ location, focal mechanism determination and identification of earthquake precursors. The second area focused on using MEQ signals generated by geothermal exploration and production to predict the relationship between fluid injection and seismicity. Here, we extended to reservoir scale our success in using ML to predict laboratory earthquakes and fault zone stress state. The third focus area was on lab experiments. Here, we developed new ML models for lab earthquake prediction and identification of precursors to failure to improve earthquake forecasting and early warning in geothermal settings. Major outcomes of our work include ML models that learn from MEQ signals during geothermal exploration and production to predict induced seismicity. MEQs occur naturally in connection with drilling and energy production. We developed ML methods to use the seismic waves from these events to characterize the elastic, hydraulic and poromechanical properties of reservoirs. Our work illuminated fracture geometry and the evolution of fracture permeability by incorporating seismic coda wave analysis and ML methods to relate fluid injection and seismicity. We significantly expanded laboratory earthquake prediction to include methods that use both passive measurements of microearthquakes within the lab fault zones and also active source acoustic measurements of fault zone elastic properties. These methods can now predict fault zone stress state, time to failure and the magnitude of lab earthquakes. Our work showed that repetitive stick- slip failure events during frictional sliding (the lab equivalent of earthquakes) are preceded by a cascade of micro-failure events that radiate energy in a manner that foretells unstable failure – manifest as laboratory MEQs. We documented a mapping between fracture properties and statistical attributes of elastic radiation. We extended existing works to geothermal reservoir scale and developed ML methods to determine reservoir permeability, fracture properties, and their evolution during geothermal energy production. An attractive feature of ML algorithms is their ability to handle big datasets and reveal patterns and correlations that may remain invisible to conventional analyses. Our work connected data from field, laboratory and intermediate scales to study permeability, stress, strength, fracture stiffness and geometry. At the field scale we used data from the Newberry Volcano field site, UtahFORGE, EGS Collab, and also the Bedretto underground research lab in Switzerland. These data sets are bridging the gap between the lab scale, theory, and reservoir scale. Our work produced plain language summaries to improve public understanding of DOE research. We also developed openly distributed ML and seismicity datasets for use by all researchers and we published connections between induced seismicity in geothermal areas and reservoir properties including permeability, fracture properties, and stress state. Our models are designed for the large data sets of induced seismicity typically associated with geothermal sites. We produced labeled event catalogs and used them on geothermal data to assess how ML can facilitate geothermal production and exploration. All datasets are available on the GDR Productivity: The project produced 32 publications in peer reviewed journals (two are in review). It supported the work of 6 PhD students, 40 conference presentations, 6 keynote talks at national meetings, and mentoring and professional development for 4 postdoctoral fellows.

15 GEOTHERMAL ENERGY↗

Seismic Monitoring near Ithaca, New York, Reveals Nonuniform Distribution of Microseismicity in an Intraplate Region

Abstract Cornell University intends to use a deep direct-use geothermal system to heat its Ithaca, New York, campus. In preparation for this project, the Cornell Seismic Network has been monitoring the background seismicity in this intraplate region since 2019. From January 2020 to June 2023, 95 events were detected within 20 km of the proposed geothermal well site, with local magnitudes ranging from −1.02 to 0.56. None of these events appear in regional or national catalogs. Events locate in a narrow geographic band, with one-fourth exhibiting multimodal hypocentral probability peaks both near the surface and at 1–4 km depth. We relocate events with a joint hypocenter and 1D velocity model inversion, in addition to a fully nonlinear method, and then compare observations with synthetic waveforms. Together, these approaches provide strong evidence for >95% of events locating at the surface or within the 3-km-thick sedimentary sequence. We explore how anthropogenic activity and regional topographic stress may contribute to frequent surficial events. This information is critical for characterizing the background microseismicity for comparison during future geothermal operations. Ithaca’s geology of Paleozoic sediments overlying Precambrian crystalline basement is typical of many continental interiors, so these results also provide insight into intraplate microseismicity patterns.

Geochemistry & Geophysics↗

DEEPEN Leapfrog Geodata Model Cleaned and Reformatted Exploration Datasets from Newberry Volcano

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the DEEPEN 3D play fairway analysis (PFA) conducted at Newberry Volcano for multiple play types (conventional hydrothermal, superhot EGS, and supercritical), existing geoscientific exploration datasets needed to be acquired, cleaned, reformatted, and assembled in Leapfrog Geothermal. This GDR submission includes all of the cleaned and reformatted (X (m), Y (m), elevation (m), processed data values) datasets used to build the Leapfrog Geodata model. Existing datasets were acquired from the GDR, from AltaRock, and from other sources. This yielded the following datasets: - Digital elevation model produced from LiDAR data by Ramsey and Bard, 2016 - MT surveys from 2006, 2011, 2014, and 2017 (including single inversions) - Gravity surveys from 2006, 2007, and 2011 (including single) - Earthquake catalogs from PNSN, LLNL, and the Newberry EGS Demonstration project - Seismic velocity model from Templeton et al., 2014 - The Frone, 2015 temperature model and a new one produced through extrapolating downhole temperature measurements and the SMU temperature at depth maps. Two versions of the new model are provided: 250 m spacing and 500 m spacing - EarthVision geologic model with alteration from Moser et al., 2016 - Well data from EGS well 55-29, deep geothermal wells, coreholes (GEO N-2 through 5) and several thermal gradient holes - "Newberry Well Data:" Location, simple lithology, directional survey data, and temperature data for the 34 wells and coreholes used in the Newberry PFA Although there are additional 2D datasets available in the area, such as aeromagnetic surveys, these were not included in the analysis. While it may be possible to project these datasets into three dimensions by assuming the surface measurements do not vary with depth, this method is associated with high uncertainty. Preexisting inversions of these data were unavailable, and inverting additional geophysical datasets is outside the scope of this project.

15 GEOTHERMAL ENERGY↗

Utah FORGE 10-3726: Geothermal Multiset Straddle for High Temperature Applications - 2024 Annual Workshop Presentation

This is a presentation on the Geothermal Multiset Straddle (GMS) for High Temperature Applications by Welltec, presented by Ricardo Vasques. This video slide presentation discusses the development of (1) an annular multiset isolation system; (2) a stimulation straddle isolation system; and (3) a multi open-close flow system, for geothermal environments. This is to enable effective zonal isolation and stimulation with multiset capabilities, to implement downhole controlled EGS in any location, and to extend the productive life of the well. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 15, 2024.

15 GEOTHERMAL ENERGY↗

Techno-Economic Viability of Flexible Dispatch of Unconventional Geothermal Systems

Flexible geothermal operations could boost project returns through the allocation of improved power purchase agreements and/or exploitation of power price arbitrage opportunities. In this study, we investigated the techno-economic feasibility of variable flow rate control and time-of-day pricing in closed-loop geothermal systems. We considered U-shaped multilateral system configurations and modeled a variety of technical system parameters. These designs were simulated using a slender-body theory (SBT) model for transient heat transfer and fluid flow. This subsurface model was integrated into the flexible geothermal economic model (FGEM) tool to evaluate the overall flexible geothermal system techno-economics. Future hourly ambient temperature conditions were based on the Sup3rCC dataset. Published datasets were used for future hourly wholesale electricity prices. We analyzed four operating strategies: 1) baseload operation, 2) seasonal dispatch (high flow rate during summer and nominal flow rate during the rest of the year), 3) net generation maximization by varying flow rate to maximize net power output, and 4) revenue maximization by varying flow rate to maximize revenue. We ran all four scenarios for a multiloop configuration with 12 lateral passes, 7-km vertical depth and 87-km total drilling length. Furthermore, we assumed a 60 degrees C/km geothermal gradient and ambient temperature and wholesale electricity prices for New Mexico as a typical state location. The nominal flow rate was set to 80 kg/s. When considering drilling costs of $1,000/m and a discount rate of 7%, the generation maximization scenario resulted in the lowest levelized cost of electricity (LCOE) of ~$150/MWh. When considering project return on investment (ROI), defined as lifetime net income divided by upfront capital costs, all flexible operation scenarios performed better than the base case scenario. The highest ROI of 80% was obtained with the revenue maximization scenario. With drilling costs of $200/m and a discount rate of 5%, the generation maximization scenario resulted in LCOE of $49/MWh.

flexible geothermal↗

Mapping potentials and bridging regional gaps of renewable resources in China

Reasonable and effective use of renewable resources can reduce dependence on traditional fossil-based energy sources and reduce carbon emissions. This study mapped the spatial potentials of renewable resources (i.e., solar radiation, precipitation, wind, and geothermal resources) in China. The results showed that China's most abundant renewable resources are located in the southwestern regions, which are significantly different from the spatial distribution patterns of population and economic development. Four southwestern provinces (Tibet, Qinghai, Sichuan, and Yunnan) make up only 7% of the national gross domestic product (GDP) and 30% of the national land area but possess 58% of the renewable resources. Furthermore, we found a weak to moderate degree of negative correlation between the emergy density of renewable resources and GDP per capita on the administrative levels of the prefecture-level cities for the whole country and in its eastern, central, and western regions. This means that the socioeconomically underdeveloped Midwest has more abundant renewable resources. A distributed energy-economic system may help to bridge the regional gaps of renewable sources in China. These findings can support policy decisions for the better development and use of renewable resources in China.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Variability in Diurnal and Seasonal Ambient Conditions on Geothermal Plant Performance and Cost

Geothermal plant performance is bounded by the second law efficiency, which accounts for the quantity of exergy that can be converted into useful work. This, in turn, is dependent on the geothermal resource temperature and the temperature of the heat sink (i.e., the ambient temperature). In this study, we show that ambient temperature variability on a diurnal and seasonal basis can affect performance and cost estimations for geothermal plants. We have utilized the updated System Advisor Model (SAM) to assess nine geothermal sites with existing resource capacities across three climate zones. Our analysis shows that both evaporatively-cooled flash and air-cooled binary cycle plants are affected by temperature, with a slightly higher effect in enhanced geothermal system binary sites. By assuming an ambient (wet bulb) temperature baseline of 15.6 degrees C (60 degrees F) and comparing baseline results to those from site-specific data, we observe up to 15% underestimation of plant performance and up to 20% overestimation of cost. These results make a case for the inclusion of location-based weather data as inputs to supply curves that are used in capacity expansion models for the prediction of future geothermal deployment scenarios.

ambient temperature↗

WELLS Interactive Application

The Wellbore Exploration and Location Logistic System (WELLS) Interactive Application is an interactive tool to enable easy exploration and visualization of the living national wellbore database (WELLS Database (https://edx.netl.doe.gov/dataset/wells_database)). The tool and underlying database were created and are maintained by the National Energy Technology Laboratory (NETL), providing visualization of the more than six million public wellbore records from more than 65 authoritative state, federal, and tribal resources. The WELLS Interactive Application serves up wellbore data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater, and other types of wells in a single, standardized, unified system. In addition to the surface location of these wells, the underlying database combines select key attributes for features such as well age, depth, and operating status. The system also provides users with references back to the original sources used in this unified platform. The underlying data can be accessed through the WELLS Database: https://edx.netl.doe.gov/dataset/wells_database Additional Information: The WELLS Interactive Application (formerly titled CO2-Locate) enables visualization and access to the public wellbore records through an intuitive web-based mapping tool. The WELLS Interactive Application was designed to help users visualize, query, analyze, and download wellbore records. Public wellbore points are included as a layer in the Map page, called Public Wells. Additionally, a multivariate hexagon grid summarizing well density from proprietary well data, called Well Density, is included to identify data gaps between the public and proprietary well data. Filtering functionalities in the tool allow these two layers to be spatially filtered by state, county, or basin as well as by status, type, true vertical depth, and spud year. The WELLS Interactive Application also contains a Near Me tool can be used to search and explore wellbore data within a user-defined distance of a specified location on the map, which can also be downloaded. The Query tool allows users to query the selected or filtered wells in the Public Wells layer and export the data. For additional information on these tool functionalities, see the help documentation on the About page of the tool. Notes for Consideration: The Well Density layer provided in this application is derived from proprietary wellbore data, the records of which do not always contain values for key features (status, type, true vertical depth, or spud year). Therefore, data might not be available when layers are queried for all filter combinations. Additionally, visualizing layers and applying filters may take additional time to load (i.e., draw on the map) due to the large size of the data.

ccs↗

Radar and infrared remote sensing of geothermal features at Pilgrim Springs, Alaska

High-altitude radar and thermal imagery collected by the NASA research aircraft WB57F were used to examine the structural setting and distribution of radiant temperatures of geothermal anomalies in the Pilgrim Springs, Alaska area. Like-polarized radar imagery with perpendicular look directions provides the best structural data for lineament analysis, although more than half the mapped lineaments are easily detectable on conventional aerial photography. Radiometer data and imagery from a thermal scanner were used to evaluate radiant surface temperatures, which ranged from 3 to 17 C. The evening imagery, which utilized density-slicing techniques, detected thermal anomalies associated with geothermal heat sources. The study indicates that high-altitude predawn thermal imagery may be able to locate relatively large areas of hot ground in site-specific studies in the vegetated Alaskan terrain. This imagery will probably not detect gentle lateral gradients.

Dean, K. G.↗