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At least 397 records · Page 22

Newly acquired core enhances geologic understanding of the northern Paradox Basin Cane Creek play, southeastern Utah

The Cane Creek interval is an emerging unconventional heterolithic play within the Pennsylvanian Paradox Formation of the northern Paradox Basin, southeastern Utah. Structural controls (basement uplifts, salt movement, faults, fractures) likely control production from the Cane Creek, where total oil production of ~10 MMBO is just a fraction of current estimates of the undiscovered resource (up to 1.2 BBOE). Oil production has been most successful from unstimulated horizontal wells in the Cane Creek Unit in the central play area, whereas areas to the north (Greentown and Gunnison Valley) have to date proven to be largely unproductive from vertical and horizontal wells drilled without the benefit of 3D seismic or the deployment of modern hydraulic fracturing techniques. However, the limited historical drilling has shown significant promise (e.g., significant shows). The lack of core data in the northern part of the play has impeded thorough assessment of reservoir quality, character, and lithological facies heterogeneity. The Cane Creek is informally divided into three distinct zones. The upper A and basal C zones are composed of fabric destructive and wavy bedded anhydrite, dolomitic mudstone, and organic-rich algal laminated mudstones (source rock). The middle B zone is generally wave rippled and burrowed, low-permeability sandstone-siltstone (reservoir) with subordinate displacive anhydrite. Recent potash cores collected from the Salt Valley anticline near Crescent Junction, Utah (but east of the main play area), show thicker reservoir sandstone/siltstone packages (~40 ft) in the B zone, and parts of the C zone, in the northern part of the Paradox Basin in comparison to the central (~35 ft) and southern (~30 ft) areas. Source rock analyses from northern core/cuttings also indicate that it is well positioned within the oil window (VRo ~0.8), with thin organic-rich mudstone beds containing up to 20 wt% TOC. Because the siliciclastic reservoir rocks have low permeabilities (0.009–0.202 mD) and variable porosities (6–17%) due to dolomite-anhydrite cement, naturally occurring and possibly stimulated fractures may be essential for hydrocarbon recovery. To better understand the northern part of the Cane Creek play, a new core was obtained from the research stratigraphic well State 16-2 (January 2021). Details from this new core will help characterize reservoir quality via core analyses, petrography, fracture orientations, geomechanics, and correlation of facies and depositional trends. Additionally, an evaluation of matrix porosity/permeability will be conducted to determine its contribution to productivity.

02 PETROLEUM↗

Locating subsurface gravel with thermal imagery

A method was discussed for using 6 band thermal imagery to locate subsurface gravel deposits in vegetated areas. Geologic history is reviewed to select potential areas of study. An overflight was made using a thermal scanner. The data were processed with a computerized system to delineate areas showing a quartz signature radiated by a gravel deposit. The method was developed during a search for gravel on National Forest land in Louisiana. Processed data from thermal imagery was compared with known gravel deposits and exploratory drill hole logs. A high correlation was noted for a wide range of deposits, from commercial pits to trace deposits only a foot thick. Overburden at these sites varied from zero to sixty feet, near the maximum annual penetration by the thermal wave. It was concluded that the method can be used to locate buried gravel deposits and that more time and effort are needed to verify the usefulness for developing gravel pits adjacent to proposed construction sites.

Scholen, Douglas E.↗

Measuring Intracranial Pressure And Volume Noninvasively

Ultrasonic technique eliminates need to drill into brain cavity. Intracranial dynamics instrument probes cranium ultrasonically to obtain data for determination of intracranial pressure (ICP) and pressure-volume index (PVI). Instrument determines sensitivity of skull to changes in pressure and by use of mechanical device to exert external calibrated pressure on skull. By monitoring volume of blood flowing into jugular vein, one determines change of volume of blood in cranial system. By measuring response of skull to increasing pressure (where pressure increased by tilting patient known amount) and by using cranial blood pressure, one determines intial pressure in cerebrospinal fluid. Once PVI determined, ICP determined.

Cantrell, John H.↗

Residual service life of carbonated structures based on site non-destructive tests

Assessing the residual service life of carbonated reinforced concrete structures is typically conducted by measuring cover depths and carbonation of drilled cores, assuming the ''square root law'' for the progress of the carbonation front. Given the large spatial variability of carbonation depths, the required number of cores becomes prohibitive. A model is presented, based on numerous experimental data, by which the carbonation rate can be estimated by means of non-destructive site measurements of the air-permeability kT. A Weibull distribution of the carbonation rate K{sub c} is fitted to the results, which is a function of kT. Hence, for each kT value measured on site coupled with the cover depth x{sub d}, expected, optimistic and pessimistic values of the corrosion initiation time can be obtained without the need of drilling cores. The method is validated on 111 paired results of kT and x{sub d}, obtained on the emblematic Tokyo's Museum of Western Art.

36 MATERIALS SCIENCE↗

Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale. This has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. In this work, we implement ML-based geothermal exploration and an enhanced geothermal systems (EGS) design tool to achieve the above goals. Our exploration tool is GeoThermalCloud (GTC) EGS design tool is GeoDT-ML. GTC (github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. It enables the identification of critical measurements needed to identify geothermal resource signatures. GeoDT-ML (github.com/SmartTensors/GeoThermalCloud.jl/tree/master/) adds coupling to GeoDT (https://github.com/GeoDesignTool/GeoDT.git) for stochastic EGS design optimization and performance prediction. GeoDT-ML leverages recent advances in deep learning and high-performance computing. Contributors to this effort include LANL, PNNL, Google, Stanford, and Julia Computing.

15 GEOTHERMAL ENERGY↗

The snake geothermal drilling project. Innovative approaches to geothermal exploration

The goal of our project was to test innovative technologies using existing and new data, and to ground-truth these technologies using slim-hole core technology. The slim-hole core allowed us to understand subsurface stratigraphy and alteration in detail, and to correlate lithologies observed in core with surface based geophysical studies. Compiled data included geologic maps, volcanic vent distribution, structural maps, existing well logs and temperature gradient logs, groundwater temperatures, and geophysical surveys (resistivity, magnetics, gravity). New data included high-resolution gravity and magnetic surveys, high-resolution seismic surveys, three slimhole test wells, borehole wireline logs, lithology logs, water chemistry, alteration mineralogy, fracture distribution, and new thermal gradient measurements.

15 GEOTHERMAL ENERGY↗

Industrial use of land observation satellite systems

The principal industrial users of land observation satellite systems are the geological industries; oil/gas, mining, and engineering/environmental companies. The primary system used is LANDSAT/MSS. Currently, use is also being made of the limited amounts of SKYLAB photography, SEASAT and SIR-A radar, and the new LANDSAT/TM data available. Although considered experimental, LANDSAT data is now used operationally by several hundred exploration and engineering companies worldwide as a vastly improved geological mapping tool to help direct more expensive geophysical and drilling phases, leading to more efficient decision-making and results. Future needs include global LANDSAT/TM; higher spatial resolution; stereo and radar; improved data handling, processing distribution and archiving systems, and integrated geographical information systems (GIS). For a promising future, governments must provide overall continuity (government and/or private sector) of such systems, insure continued government R and D, and commit to operating internationally under the civil Open Skies policy.

Henderson, F. B., III↗

Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region

The project Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Rocky Mountain Carbon Capture and Storage (RMCCS) project investigated multiple geologic formations and characterized a local site on the Colorado Plateau for future CCS opportunities. The RMCCS project focused on the Cretaceous Dakota, Jurassic Entrada, and Pennsylvanian Weber Sandstones, the three largest regional formations. All formations in this project are potential CO2 storage resources for future power plants, natural gas processing plants, cement plants, and oil shale development projects. The area adjacent to Craig, Colorado, (Sand Wash Basin) was the area selected for detailed geologic characterization on the RMCCS project. The basin was selected in part because the geology can be extrapolated to other sites on the Colorado Plateau. Field mapping and seismic surveys were conducted to identify and evaluate the basin's structural configuration. A 9,745-foot deep characterization well was drilled to collect 131 feet of core and a suite of geophysical well log data. Petrophysical tests on samples of core were used to calibrate geophysical log data, which can be used to obtain storage resource estimates and evaluate associated uncertainty as well as simulate the hydrologic behavior of injected CO2. A detailed analysis of the primary formations (Dakota, Entrada and Weber sandstones) yielded a more accurate CO2 storage resource assessment for these formations within the Colorado Plateau; RMCCS estimates indicate a total CO2 storage resource of more than 38,000 million metric tons. The characterization of the Sand Wash Basin (2-D seismic surveys, multiple well logs and lithological, petrophysical and geochemical analyses) allowed for a detailed 3-D model to be constructed. The model served as the framework for analyses ranging from CO2 storage resource, injectivity, and subsurface flow to uncertainty estimates to evaluation of risk.

2-D seismic↗

Utah FORGE: Phase 3 Ground Water Level Monitoring Data

Groundwater data around the Utah FORGE site has been collected to determine the piezometric levels and compositional variability. Field measurements in 2020 are designed to obtain and survey new groundwater wells that have been drilled on the distal periphery of the Utah FORGE project area. The spreadsheet included in this submission contains ground water level data from the Utah FORGE site as monitored from wells WOW-2 and WOW-3. The well locations are also provided as UTM, Zone 12, NAD83 coordinates.

15 GEOTHERMAL ENERGY↗

Dixie Valley Engineered Geothermal System Exploration Methodology Project, Baseline Conceptual Model Report

The Engineered Geothermal System (EGS) Exploration Methodology Project is developing an exploration approach for EGS through the integration of geoscientific data. The Project chose the Dixie Valley Geothermal System in Nevada as a field laboratory site for methodlogy calibration purposes because, in the public domain, it is a highly characterized geothermal systems in the Basin and Range with a considerable amount of geoscience and most importantly, well data. This Baseline Conceptual Model report summarizes the results of the first three project tasks (1) collect and assess the existing public domain geoscience data, (2) design and populate a GIS database, and (3) develop a baseline (existing data) geothermal conceptual model, evaluate geostatistical relationships, and generate baseline, coupled EGS favorability/trust maps from +1km above sea level (asl) to -4km asl for the Calibration Area (Dixie Valley Geothermal Wellfield) to identify EGS drilling targets at a scale of 5km x 5km. It presents (1) an assessment of the readily available public domain data and some proprietary data provided by Terra-Gen Power, LLC, (2) a re-interpretation of these data as required, (3) an exploratory geostatistical data analysis, (4) the baseline geothermal conceptual model, and (5) the EGS favorability/trust mapping. The conceptual model presented applies to both the hydrothermal system and EGS in the Dixie Valley region.

15 GEOTHERMAL ENERGY↗

Dixie Valley Engineered Geothermal System Exploration Methodology Project, Baseline Conceptual Model Report

The Engineered Geothermal System (EGS) Exploration Methodology Project is developing an exploration approach for EGS through the integration of geoscientific data. The Project chose the Dixie Valley Geothermal System in Nevada as a field laboratory site for methodlogy calibration purposes because, in the public domain, it is a highly characterized geothermal systems in the Basin and Range with a considerable amount of geoscience and most importantly, well data. This Baseline Conceptual Model report summarizes the results of the first three project tasks (1) collect and assess the existing public domain geoscience data, (2) design and populate a GIS database, and (3) develop a baseline (existing data) geothermal conceptual model, evaluate geostatistical relationships, and generate baseline, coupled EGS favorability/trust maps from +1km above sea level (asl) to -4km asl for the Calibration Area (Dixie Valley Geothermal Wellfield) to identify EGS drilling targets at a scale of 5km x 5km. It presents (1) an assessment of the readily available public domain data and some proprietary data provided by Terra-Gen Power, LLC, (2) a re-interpretation of these data as required, (3) an exploratory geostatistical data analysis, (4) the baseline geothermal conceptual model, and (5) the EGS favorability/trust mapping. The conceptual model presented applies to both the hydrothermal system and EGS in the Dixie Valley region.

15 GEOTHERMAL ENERGY↗

Dixie Valley Engineered Geothermal System Exploration Methodology Project, Baseline Conceptual Model Report

The Engineered Geothermal System (EGS) Exploration Methodology Project is developing an exploration approach for EGS through the integration of geoscientific data. The Project chose the Dixie Valley Geothermal System in Nevada as a field laboratory site for methodlogy calibration purposes because, in the public domain, it is a highly characterized geothermal systems in the Basin and Range with a considerable amount of geoscience and most importantly, well data. This Baseline Conceptual Model report summarizes the results of the first three project tasks (1) collect and assess the existing public domain geoscience data, (2) design and populate a GIS database, and (3) develop a baseline (existing data) geothermal conceptual model, evaluate geostatistical relationships, and generate baseline, coupled EGS favorability/trust maps from +1km above sea level (asl) to -4km asl for the Calibration Area (Dixie Valley Geothermal Wellfield) to identify EGS drilling targets at a scale of 5km x 5km. It presents (1) an assessment of the readily available public domain data and some proprietary data provided by Terra-Gen Power, LLC, (2) a re-interpretation of these data as required, (3) an exploratory geostatistical data analysis, (4) the baseline geothermal conceptual model, and (5) the EGS favorability/trust mapping. The conceptual model presented applies to both the hydrothermal system and EGS in the Dixie Valley region.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Microseismic Monitoring Geophone Data from Well 78-32

This submission includes geophone data collected by Schlumberger from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. The data are hosted by the Center for High Performance Computing (CHPC) at the University of Utah, and a script for downloading the data is attached. Additional survey info and tips for running the script are included in the document below.

15 GEOTHERMAL ENERGY↗

Photometric classification of Hyper Suprime-Cam transients using machine learning

Abstract The advancement of technology has resulted in a rapid increase in supernova (SN) discoveries. The Subaru/Hyper Suprime-Cam (HSC) transient survey, conducted from fall 2016 through spring 2017, yielded 1824 SN candidates. This gave rise to the need for fast type classification for spectroscopic follow-up and prompted us to develop a machine learning algorithm using a deep neural network with highway layers. This algorithm is trained by actual observed cadence and filter combinations such that we can directly input the observed data array without any interpretation. We tested our model with a dataset from the LSST classification challenge (Deep Drilling Field). Our classifier scores an area under the curve (AUC) of 0.996 for binary classification (SN Ia or non-SN Ia) and 95.3% accuracy for three-class classification (SN Ia, SN Ibc, or SN II). Application of our binary classification to HSC transient data yields an AUC score of 0.925. With two weeks of HSC data since the first detection, this classifier achieves 78.1% accuracy for binary classification, and the accuracy increases to 84.2% with the full dataset. This paper discusses the potential use of machine learning for SN type classification purposes.

Takahashi, Ichiro↗

The first X-ray diffraction measurements on Mars

The Mars Science Laboratory landed in Gale crater on Mars in August 2012, and the Curiosity rover then began field studies on its drive toward Mount Sharp, a central peak made of ancient sediments. CheMin is one of ten instruments on or inside the rover, all designed to provide detailed information on the rocks, soils and atmosphere in this region. CheMin is a miniaturized X-ray diffraction/X-ray fluorescence (XRD/XRF) instrument that uses transmission geometry with an energy-discriminating CCD detector. CheMin uses onboard standards for XRD and XRF calibration, and beryl:quartz mixtures constitute the primary XRD standards. Four samples have been analysed by CheMin, namely a soil sample, two samples drilled from mudstones and a sample drilled from a sandstone. Rietveld and full-pattern analysis of the XRD data reveal a complex mineralogy, with contributions from parent igneous rocks, amorphous components and several minerals relating to aqueous alteration. In particular, the mudstone samples all contain one or more phyllosilicates consistent with alteration in liquid water. In addition to quantitative mineralogy, Rietveld refinements also provide unit-cell parameters for the major phases, which can be used to infer the chemical compositions of individual minerals and, by difference, the composition of the amorphous component.

Chemistry↗

Comprehensive Evaluation of the Geothermal Resource Potential within the Pyramid Lake Paiute Reservation Phase III Report

This project integrated state-of-the-art exploration technologies with a geologic framework and reservoir modeling to ultimately determine the efficacy of future geothermal production within the PLPT reservation. The information gained during this study should help the PLPT to make informed decisions regarding construction of a geothermal power plant. Additional benefits included the transfer of new technologies and geothermal data to the geothermal industry and it created and/or preserved nearly three dozen jobs accordance with the American Recovery and Reinvestment Act of 2009. A variety of tasks were conducted to achieve the above stated objectives. The following are the tasks completed within the project: 1. Permitting 2. Shallow temperature survey 3. Seismic data collection and analysis 4. Fracture stress analysis 5. Phase I reporting Permitting 7. Shallow temperature survey 8. Seismic data collection and analysis 9. Fracture stress analysis 10. Phase I reporting 11. Drilling two new wells 12. Borehole geophysics 13. Phase II reporting 14. Well testing and geochemical analysis 15. Three-dimensional geologic model 16. Three-dimensional reservoir analysis 17. Reservation wide geothermal potential analysis 18. Phase III reporting Phase I consisted of tasks 1 – 5, Phase II tasks 6 – 8, and Phase III tasks 9 – 13. This report details the results of Phase III tasks. Reports are available for Phase I, and II as separate documents.

15 GEOTHERMAL ENERGY↗

Newberry EGS Demonstration: Phase 2.2 Report

The Newberry Volcano EGS Demonstration is a five year field project designed to demonstrate recent technological advances for engineered geothermal systems (EGS) development. Advances in reservoir stimulation, diverter, and monitoring are being tested in a hot (>300 ºC), dry well (NWG 55-29) drilled in 2008. In the fall of 2014, 9,500m3 (2.5 million gallons) of groundwater were injected at a maximum wellhead pressure of 195 bar (2850 psi) over 4 weeks of hydraulic stimulation. Injectivity changes, thermal profiles and seismicity indicate that fracture permeability in well NWG 55-29 was enhanced. The fifteen-station microseismic array (MSA) located 398 seismic events, ranging in magnitude from M 0 to M 2.26. The next step is to drill a production well into the EGS reservoir. Advanced analysis of the microseismic data including hand picking of first arrivals, moment tensors, relative relocations, and velocity model improvements have resulted new higher-quality microseismic catalogs. These catalogs have been combined by relative weighting and gridding of seismic densities, resulting in probability-based maps and cross-sections, which have been used to plan a production well trajectory. The microseismic locations and times were also used to develop a reservoir diffusivity model, which can be used to evaluate stimulation plans such as dual-well stimulation.

15 GEOTHERMAL ENERGY↗

Impact of Drilling Operations on Lunar Volatiles Capture: Thermal Vacuum Tests

In Situ Resource Utilization (ISRU) enables future planetary exploration by using local resources to supply mission consumables. This idea of 'living off the land' has the potential to reduce mission cost and risk. On the moon, water has been identified as a potential resource (for life support or propellant) at the lunar poles, where it exists as ice in the subsurface. However, the depth and content of this resource has yet to be confirmed on the ground; only remote detection data exists. The upcoming Resource Prospector mission (RP) will 'ground-truth' the water using a rover, drill, and the RESOLVE science package. As the 2020 planned mission date nears, component level hardware is being tested in relevant lunar conditions (thermal vacuum). In August 2014 a series of drilling tests were performed using the Honeybee Robotics Lunar Prospecting Drill inside a 'dirty' thermal vacuum chamber at the NASA Glenn Research Center. The drill used a unique auger design to capture and retain the lunar regolith simulant. The goal of these tests was to investigate volatiles (water) loss during drilling and sample transfer to a sample crucible in order to validate this regolith sampling method. Twelve soil samples were captured over the course of two tests at pressures of 10(exp-5) Torr and ambient temperatures between -80C to -20C. Each sample was obtained from a depth of 40 cm to 50 cm within a cryogenically frozen bed of NU-LHT-3M lunar regolith simulant doped with 5 wt% water. Upon acquisition, each sample was transferred and hermetically sealed inside a crucible. The samples were later baked out to determine water wt% and in turn volatile loss by following ASTM standard practices. Of the twelve tests, four sealed properly and lost an average of 30% of their available water during drilling and transfer. The variability in the results correlated well with ambient temperature (lower the temperature lower volatiles loss) and the trend agreed with the sublimation rates for the same temperature. Moisture retention also correlated with quantity of sample: a larger amount of material resulted in less water loss. The drilling process took an average of 10 minutes to capture and transfer each sample. The drilling power was approximately 20 Watt with a Weight on Bit of approximately 30 N. The bit temperature indicated little heat input into formation during the drilling process.

drilling↗