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At least 181 records · Page 10

Machine Learning for Geothermal Resource Exploration in the Tularosa Basin, New Mexico

Geothermal energy is considered an essential renewable resource to generate flexible electricity. Geothermal resource assessments conducted by the U.S. Geological Survey showed that the southwestern basins in the U.S. have a significant geothermal potential for meeting domestic electricity demand. Within these southwestern basins, play fairway analysis (PFA), funded by the U.S. Department of Energy’s (DOE) Geothermal Technologies Office, identified that the Tularosa Basin in New Mexico has significant geothermal potential. This short communication paper presents a machine learning (ML) methodology for curating and analyzing the PFA data from the DOE’s geothermal data repository. The proposed approach to identify potential geothermal sites in the Tularosa Basin is based on an unsupervised ML method called non-negative matrix factorization with custom k-means clustering. This methodology is available in our open-source ML framework, GeoThermalCloud (GTC). Using this GTC framework, we discover prospective geothermal locations and find key parameters defining these prospects. Our ML analysis found that these prospects are consistent with the existing Tularosa Basin’s PFA studies. This instills confidence in our GTC framework to accelerate geothermal exploration and resource development, which is generally time-consuming.

15 GEOTHERMAL ENERGY↗

CO2 Storage Site Analysis, Screening, and Resource Estimation for Cenozoic Offshore Reservoirs in the Central Gulf of Mexico

The storage potential of hydrocarbon reservoirs in the central Gulf of Mexico (GOM) makes future development of CO2 storage projects in those areas promising for secure, large-scale, and long-term storage purposes. Focusing on the producing and depleted hydrocarbon fields in the continental slope of the central GOM, this paper analyzed, assessed, and screened the producing sands and evaluated their CO2 storage potential. A live interactive CO2 storage site screening system was built in the SAS® Viya system with a broad range of screening criteria combined from published studies. This offers the users a real-time assessment of the storage sites and enables them to adjust the filters and visualize the results to determine the most suitable filter range. The CO2 storage resources of the sands were estimated using a volumetric equation and the correlation developed by the National Energy Technology Laboratory (NETL). The results of this study indicate that 1.05 gigatons of CO2 storage resources are available in the developed reservoirs at the upper slope area of the central GOM. The Mississippi Canyon and Green Canyon protraction areas contain the fields with the largest storage resources.

Hu, Xitong↗

Cliff Retreat Rates Associated with a Low-Level Radioactive Waste Disposal Facility in Los Alamos, New Mexico, USA

We present an analysis and interpretation of potential cliff stability at a low-level waste disposal facility at Los Alamos National Laboratory, New Mexico, using cliff morphologic and fracture characteristics coupled with carbon-14 surface exposure dating. Our study is important as it directly bears on the licensing criteria for low-level radioactive waste sites. We find that future characteristic cliff failures will likely not breach disposal pits and shafts over the 1000-year minimum regulatory period. Further, we find, using a multivariate regression model, that slope angle and cliff face aspect are sub-equal in importance to predict regions of high risk of failure when combined with surface exposure ages and assuming that old exposure ages are most indicative of stability (instability) and therefore can aid decision making in final design implementation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NGEE Arctic Rainfall Simulator Validation Data from Los Alamos National Laboratory, New Mexico, Summer 2022

Experiments evaluating the uniformity and intensity of rainfall produced by the NGEE Arctic Rainfall Simulator (NARS) were conducted at Los Alamos National Laboratory, New Mexico, over summer 2022. Petri dishes were placed in a grid within the NARS plot. Simulated rainfall was collected in each petri dish and the intensity and uniformity of the simulator was subsequently calculated. This data package contains two .csv files, one that summarizes the rainfall intensity and uniformity for each experiment, the other that contains individual petri dish water volume and intensity for each plot location and experiment. The Python scripts to control NARS are also included. The NGEE Arctic Rainfall Simulator (NARS) is a variable intensity rainfall simulator (RFS) with a frame design based on the Humphry et al. (2002) RFS and a water delivery system based on the Walnut Gulch (Paige et al., 2004) RFS. The NARS uses an aluminum frame that is fully deconstructable for transportation to field locations and a water system that enables variable rain intensity. Rain intensity control and data collection are automated using a Raspberry Pi microcomputer. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Distribution and directional fabric of ash-flow sheets in the northwestern Mogollon Plateau, New Mexico.

Individual ash-flow sheets distributed over wide areas in the Mogollon-Datil volcanic province can be delineated and related by flow direction techniques to specific source cauldrons. Two major mid-Tertiary ash flows in the Mogollon Plateau have measurable microscopic directional fabric indicative of primary flow direction imprinted in the ash-flow sheets during late-stage laminar flow. Regional stratigraphic relationships and flow patterns of the ash-flow sheets indicate a late Tertiary origin of the Mogollon Plateau depression. They also show that Basin-Range faulting in southwestern New Mexico was not initiated until after emplacement of the younger ash flow (23 m.y. B.P.). Directional fabric is an inherent property of many calc-alkalic ash-flow sheets and measurement of preferred orientation provides a powerful tool in unravelling the geologic history of complex volcanic terrane.

Rhodes, R. C.↗

Initial evaluation of the geologic applications of ERTS-1 imagery for New Mexico

Coverage of approximately one-third of the test site, the state of New Mexico, had been received by January 31, 1973 and all of the images received were MSS products. Features noted during visual inspection of 91/2 x 91/2 prints include major structural forms, vegetation patterns, drainage patterns and outcrops of geologic formations having marked color contrasts. The Border Hills Structural Zone and the Y-O Structural Zone are prominently reflected in coverage of the Pecos Valley. A study of available maps and remote sensing material covering the Deming-Columbus area indicated that the limit of detection and the resolution of MSS products are not as good as those of aerial photographs, geologic maps, and manned-satellite photographs. The limit of detection of high contrast features on MSS prints in approximately 1000 feet or 300 meters for linear features and about 18 acres for roughly circular areas.

Vonderlinden, K.↗