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At least 343 records · Page 19

Geologic Mapping of Ascraeus Mons, Mars

Ascraeus Mons (AM) is the northeastern most large shield volcano residing in the Tharsis province on Mars. We are funded by NASA's Mars Data Analysis Program to complete a digital geologic map based on the mapping style. Previous mapping of a limited area of these volcanoes using HRSC images (13-25 m/pixel) revealed a diverse distribution of volcanic landforms within the calderas, along the flanks, rift aprons, and surrounding plains. The general scientific objectives for which this mapping is based is to show the different lava flow morphologies across AM to better understand the evolution and geologic history.

Volcanoes↗

3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydraulic conductivity. Vertical connectivity (a through going network of permeable areas that allows advection of heat from depth to the shallow subsurface) is rare and is confined to relatively small volumes that have highly variable spatial distribution. This local compartmentalization of connectivity represents a significant challenge to understanding hydrothermal circulation and for exploring, developing, and managing hydrothermal resources. Here, we present an evaluation of the geologic characteristics that control this compartmentalization in hydrothermal systems through 3-D analysis of the Brady geothermal field in western Nevada. A published 3-D geologic map of the Brady area is used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity. The 3-D distribution of these variables is compared to the distribution of productive and non-productive fluid flow intervals along production wells and non-productive wells via principal component analysis (PCA). This comparison elucidates which geologic and structural variables are most closely associated with productive fluid flow intervals. Results indicate that production intervals at Brady are located: (1) within or near to known and stress-loaded macro-scale faults, and (2) in areas of high fault and fracture density. This submission includes the published journal article detailing this work, the published 3-D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3-D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using existing R programs.

15 GEOTHERMAL ENERGY↗

Development of an Inertial Sensor-based Methodology for Spacesuited Geology Task Assessments during Simulated Lunar Extravehicular Activities

Lunar surface exploration during Artemis missions will require the specific skill set of geology sampling. Apollo astronauts had extensive training and used specialized tools to collect lunar rocks, core samples, pebbles, sand, and dust. The inflexibility of the pressurized Apollo spacesuits forced sampling to be taken at a standstill posture. However, new exploration spacesuits are expected to incorporate advanced materials and joint bearings, allowing for greater mobility and a wider range of functional postures. Thus, science and exploration during Artemis missions will likely involve a variety of standing, squatting, and kneeling postures. In preparation for future lunar exploration missions, NASA provides geologic training to astronauts and other mission personnel. This professional training with a spacesuit in simulated lunar environments will enhance performance and reduce risk of injury to astronauts on the lunar surface. However, anecdotally, untrained or newly trained people wearing prototype planetary spacesuits have been observed to performing motions differently than a trained geologist would when conducting the same geology sampling tasks. Therefore, a tool for evaluating geology postures at extravehicular activity (EVA) training facilities becomes required. In this paper, we introduce a novel inertial measurement unit (IMU)-based method of geology task assessments in spacesuited conditions during simulated lunar EVAs. As a case study, two subjects (one geologist and one non-geologist) participated and donned the Mark III prototype planetary spacesuit during offloading with the spreader bar gimbal in NASA’s Active Response Gravity Offload System (ARGOS). For automated geology task assessments, the spacesuit was instrumented with three wireless IMUs (APDM Opal, OR, USA): one on the chest and one each on the left and right ankle bearings. Then subjects performed geology tasks using various tools (rake, trench, hammer chisel, scoop, and drive tube) for 45 minutes each. The chest IMU measured the torso tilt angle in the sagittal plane. We used an ensemble learning method with the ankle IMUs to discriminate between standing and kneeling activities. IMU data were processed using custom MATLAB (Mathworks, MA, USA) software. In our case study, the developed method was able to discriminate differences in standing and kneeling activity levels between subjects who were all highly experienced with spacesuited testing. Our preliminary data showed one subject maintained the constant and lower range of the upper body tilt angle while both standing and kneeling, while the other subject showed more variation of the upper body tilt angle and preferred bending the upper body rather than changing from standing to kneeling posture and vice versa. While geology experience may be a factor, these results need further investigation as suit sizing and ARGOS offloading configurations have been proven to have a significant influence on suited ARGOS tasks. Also, more subjects will be needed to complete these tasks for validation. IMU-based geology task assessments can provide useful information for geology training programs. Additionally, our IMU-based posture analysis can provide new insights into how to evaluate spacesuited geology task characteristics of astronauts during simulated lunar EVAs.

Kyoung Jae Kim↗

Final report

In eastern Nevada and western Utah is an extensive terrane that has experienced a complex tectonic history of Mesozoic deformation and superposed Tertiary extension. The Mesozoic tectonic history of this area has been the subject of controversy for the past twenty or more years. The debate has centered on whether major Mesozoic geologic structures were due to compressional or extensional tectonic regimes. The goal of our research was to decipher the deformational history of the area by combining detailed geologic mapping, remote sensing data analysis, and U-Pb and K-Ar geochronology. This study area includes the Dolly Varden Mountains and adjacent Currie Hills, located in the semi-arid environment of the northeastern Great Basin in Nevada. Vegetation cover in the Dolly Varden Mountains typically ranges from about 10 percent to 50 percent, with some places along drainages and on high, north-facing slopes where vegetation cover approaches 100 percent. Sagebrush is found at less vegetated lower elevations, whereas pinon pine and juniper are prevalent above 2,000 meters. A variety of geologic materials is exposed in the study area. A sequence of Late Paleozoic and Triassic sedimentary rocks includes limestone, dolomite, chert, sandstone, siltstone and shale. A two-phase granitic stock, called the Melrose, intruded these rocks, resulting in metamorphism along the intrusive contact. Tertiary volcanic rocks cover most of the eastern part of the Dolly Varden Mountains and low-lying areas in the Currie Hills.

Zamudio, Joe↗

Machine learning to identify geologic factors associated with production in geothermal fields: a case-study using 3D geologic data, Brady geothermal field, Nevada

Abstract In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fluid-flow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fluid-flow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k -means clustering (NMF k ), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes.

58 GEOSCIENCES↗

Use of TV pictures obtained from weather satellites to study the geological structure of the earth

Results are presented of Soviet investigations into the use of television imagery obtained from meteorological satellites for the interpretation of tectonics, lithology, and structural properties of the earth. The area investigated encompassed the eastern part of Iran, and the western regions of Afghanistan and Pakistan. Interpretation of the features identified during the analysis was accomplished by comparing these features with physical, geographic, geological, and tectonic maps. It was concluded that television pictures of the earth from space can be used for geological and structural analysis.

Bashilova, I. I.↗

Hydrological Modeling of the Jezero Crater Outlet-Forming Flood

Jezero crater is a site of prime scientific interest because it was a lake early in Mars history. Preserved clay- and carbonate-bearing sedimentary fans on Jezero's western and northwestern margin (Fig. 2) are accessible to future exploration. Geologic context [1] and stratigraphic analysis of the western fan strongly support the interpretation that these fans were deposited as deltas into the lake. This has helped establish Jezero as one of the final candidate landing sites for Mars 2020. The high level of certainty that Jezero was a lake results from the existence of its outlet valley, which required filling of the crater to form [e.g., 1,4]. Here, we specifically focus on how this outlet valley was carved by the dam breach flood that eroded the eastern crater rim. We have completed preliminary modeling in both 1D and 2D of the outlet's formation.

Geology↗

Examining Volcanic Terrains Using In Situ Geochemical Technologies; Implications for Planetary Field Geology

Regardless of the target destination for the next manned planetary mission, the crew will require technology with which to select samples for return to Earth. The six Apollo lunar surface missions crews had only the tools to enable them to physically pick samples up off the surface or from a boulder and store those samples for return to the Lunar Module and eventually to Earth. Sample characterization was dependent upon visual inspection and relied upon their extensive geology training. In the four decades since Apollo however, great advances have been made in traditionally laboratory-based instrument technologies that enable miniaturization to a field-portable configuration. The implications of these advancements extend past traditional terrestrial field geology and into planetary surface exploration. With tools that will allow for real-time geochemical analysis, an astronaut can better develop a series of working hypotheses that are testable during surface science operations. One such technology is x-ray fluorescence (XRF). Traditionally used in a laboratory configuration, these instruments have now been developed and marketed commercially in a field-portable mode. We examine this technology in the context of geologic sample analysis and discuss current and future plans for instrument deployment. We also discuss the development of the Chromatic Mineral Identification and Surface Texture (CMIST) instrument at the NASA Goddard Space Flight Center (GSFC). Testing is taking place in conjunction with the RIS4E (Remote, In Situ, and Synchrotron Studies for Science and Exploration) SSERVI (Solar System Exploration and Research Virtual Institute) team activities, including field testing at Kilauea Volcano, HI..

Young, K. E.↗

Physics-embedded inverse analysis with algorithmic differentiation for the earth’s subsurface

Abstract Inverse analysis has been utilized to understand unknown underground geological properties by matching the observational data with simulators. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented with embedded physics and a technique known as algorithmic differentiation. We use a physics-embedded generative model, which takes statistically simple parameters as input and outputs subsurface properties (e.g., permeability or P-wave velocity), that embeds physical knowledge of the subsurface properties into inverse analysis and improves its performance. We tested the application of this approach on four geologic problems: two heterogeneous hydraulic conductivity fields, a hydraulic fracture network, and a seismic inversion for P-wave velocity. This physics-embedded inverse analysis approach consistently characterizes these geological problems accurately. Furthermore, the excellent performance in matching the observational data demonstrates the reliability of the proposed method. Moreover, the application of algorithmic differentiation makes this an easy and fast approach to inverse analysis when dealing with complicated geological structures.

54 ENVIRONMENTAL SCIENCES↗

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs: Preprint

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulations have been conducted in TETRAD-G and CMG STARS to explore different injection and production fluid flow rates and allocations and to develop a training data set for ML. This process included simulating the historical injection and production since 1979 and prediction of future performance through 2040. ML networks were created and trained using TensorFlow based on multilayer perceptron (MLP), long short-term memory (LSTM), and convolutional neural network (CNN) architectures. These networks took as input selected flow rates, injection temperatures, and historical field operation data and produced estimates of future production temperatures. This approach was first successfully tested on a simplified single fracture doublet system, followed by the application to the BHS reservoir. Using an initial BHS dataset with 37 simulated scenarios, the trained and validated network predicted the production temperature for 6 production wells with the mean absolute percentage error of less than 8%. In a complementary analysis effort, the principal component analysis applied to 13 BHS geological parameters revealed that vertical fracture permeability shows the strongest correlation with fault density and fault intersection density. A new BHS reservoir model was developed considering the fault intersection density as proxy for permeability. This new reservoir model helps to explore under-exploited zones in the reservoir. A data gathering plan to obtain additional subsurface data was developed; it includes temperature surveying for three idle injection wells, at which the reservoir simulations indicate high bottom-hole temperatures. The collected data assist with calibrating the reservoir model and may lead to converting these wells to producers to access under-exploited zones in the reservoir. Data gathering activities are planned for the first quarter of 2021.

40 EE - Geothermal Technologies Office (EE-4G)↗

Micro-XRF for In Situ Geological Exploration of Other Planets

In situ analysis of rock chemistry is a fundamental tool for exploration of planets. To meet this need, a high-spatial-resolution micro x-ray fluorescence (Micro-XRF) instrument was developed that is capable of determining the elemental composition of rocks (elements Na U) with 100 microns spatial resolution, thus providing insight to the composition of features as small as sand grains and individual laminae. The resulting excitation beam is of sufficient intensity that high signal-to-noise punctual spectra are acquired in seconds to a few minutes using an Amptek Silicon Drift Detector (SDD). The instrument features a tightly focused x-ray tube and HVPS developed by Moxtek that provides up to 200 micro-A at 10 to 50 keV, with a custom polycapillary optic developed by XOS Inc. and integrated into a breadboard Micro-XRF (see figure). The total mass of the complete breadboard instrument is 2.76 kg, including mounting hardware, mounting plate, camera, laser, etc. A flight version of this instrument would require less than 5W nominal power and 1.5 kg mass. The instrument includes an Amptek SDD that draws 2.5 W and has a resolution of 135 to 155 eV FWHM at 5.9 keV. It weighs 180 g, including the preamplifier, digital pulse processor, multichannel analyzer, detector and preamp power supplies, and packaging. Rock samples are positioned relative to the instrument by a three-axis arm whose position is controlled by closed-loop translators (mimicking the robotic arm of a rover). The distance from the source to the detector is calculated from the position of a focused laser beam on the sample as imaged by the camera. The instrument enables quick scans of major elements in only 1 second, and rapid acquisition (30 s) of data with excellent signal-to-noise and energy resolution for trace element analysis

Wade, Lawrence A.↗

Geological photointerpretation of the Paraguana Peninsula using ERTS-A multispectral photography

A methodology was developed to evaluate multispectral analysis of orbital imagery on the interpretation of geology, coastal geomorphology and sedimentary processes. The images analyzed were obtained during the pass of ERTS satellite over the center region of Venezuela on October 19, 1972. ERTS-1 multispectral images in black and white paper copies and transparencies of the 4 bands and false color composites at scales of 1:1,000,000 and 1:500,000 were interpreted. Lithology and outcrop patterns of the following geological formations have been interpreted: igneous and metamorphic basement of Cocodite and Santa Ana, Jurassic-Cretaceous metamorphics of Pueblo Nuevo, Cantaure Miocene-Pliocene sediments, and Quaternary alluvium, dunes, beach ridges, bars and reefs. A prominent and extensive Paraguana tonal anomaly shaped as an 8 has been discovered at the NW of the Peninsula. Its erosional origin has exposed light toned lower beds at the center, with additional evidence of topographic depression and development of underground drainage of karst origin. Coastal geomorphology, its processes and energy has been interpreted with the help of wind direction analysis (ENE-WSW) at sea level through the orientation of transported materials (water vapor, water and sediments) by clouds, waves, sea current, plumes of suspended sediments associated to river outlets, dunes, sediment sources and shore-line orientation.

Albrizzio, C.↗

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗

Dynamic modeling studies of basin-scale pressure interference and CO 2 plume evolution in multi-well geologic CO 2 storage

This research employs numerical modeling to analyze how CO 2 plumes and pressure fronts evolve when CO 2 is injected into a single storage formation from multiple projects located in proximity. Here, this analysis also evaluates the extent to which injection well spacing alleviates pressure buildup in the absence of active pressure management tactics. The simulation approach was based on a single, homogenous saline aquifer in which CO 2 injection occurs under a one-injector baseline case and several multi-well cases where well spacing varies. Analysis results show that the extent of pressure buildup is in the range of tens or a few hundreds of kilometers and contingent upon the defining pressure buildup demarcating the front edge. For the geological setting evaluated in this paper, our analysis suggests that without active basin pressure management strategies, commercial-scale projects would likely need to be sited far apart to avoid pressure interference from one another. Analysis results show the radius of CO 2 plume varies approximately from 2 to 3 km from injection wells (each injecting 1 Mt/year for 30 years) depending on cases and modeling parameters assumed. Given the pressure interference, this paper thus draws attention to the importance of greater coordination among storage operators and regulatory stakeholders. Because this analysis assumes a very specific geologic setting, this exploratory analysis bears further investigations across other geologic scenarios.

42 ENGINEERING↗

FECM/NETL CO 2 Saline Storage Cost Model (2024): User’s Manual

The U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM), in collaboration with the National Energy Technology Laboratory (NETL), has developed the FECM/NETL CO 2 Saline Storage Cost Model (CO2_S_COM). This Excel-based tool provides a comprehensive framework for estimating the costs and breakeven prices associated with storing carbon dioxide (CO 2 ) in deep saline formations. Designed from the perspective of a CO 2 storage site owner, the CO2_S_COM incorporates four integrated modules—project management, financial analysis, activity cost estimation, and geological evaluation—to deliver fast, robust, and actionable insights for evaluating project finances. This is the user's manual for CO2_S_COM. The model may be accessed at this link: FECM/NETL CO2 Saline Storage Cost Model CO2_S_COM 2024 (v4) - Submissions - EDX

54 ENVIRONMENTAL SCIENCES↗

MODFLOW6 models used to evaluate potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, Southern Nevada

The hydrograph for well ER-5-3-2 in Frenchman Flat, southern Nevada, has previously unexplained water-level fluctuations. Four, three-dimensional, groundwater models (MODFLOW 6) were developed to evaluate potential stresses and hydrologic conditions affecting the well ER-5-3-2 hydrograph. Four model scenarios were developed that simulated: (1) wellbore leakage without recharge, (2) wellbore leakage with recharge, (3) shallow (low transmissivity) and deep (high transmissivity) carbonate rocks, and (4) lateral heterogeneity of carbonate rocks. Input and output files for the four model scenarios are in the model and output directories, respectively. Hydraulic conductivity, specific storage, and wellbore-leakage rates (when simulated) were estimated with parameter estimation (PEST) by minimizing a weighted composite, sum-of-squares objective function. The objective function was informed by measurement and Tikhonov regularization observations. Measurement observations included drawdowns from the constant-rate aquifer test and water-level altitudes measured in well ER-5-3-2 from 2001-2021. Tikhonov regularization informed hydraulic conductivity and specific storage parameters that were insensitive to measurement observations, where homogeneity was the preferred relation. Batch files, executables, and MODFLOW 6, PEST, and post-processing utilities are in the ancillary directory. Supplementary data also are included in the ancillary directory, including site information, high-frequency water-level and aquifer-test data, transmissivity estimates, water-chemistry data, and water-temperature analyses. This USGS data release contains data, analyses, and model files for the simulations and analysis results described in U.S. Geological Survey Scientific Investigations Report (https://doi.org/10.3133/sir20225132).

54 ENVIRONMENTAL SCIENCES↗