18-13 Mapping Geothermal Resources with Python
Session: Shaping a Sustainable Future with Geology in the Twenty-First Century: Geology and Society Division Turns 22
Presenting Author:
John AndrewsAuthors:
Andrews, John R.1, Paine, Jeffrey G.2(1) BEG/JSG/UT, Austin, TX, USA, (2) BEG/JSG/UT, Austin, TX, USA,
Abstract:
Geothermal energy for direct-use and electricity generation is attracting the attention of decision makers and the scientific community, so we’ve undertaken an effort to map this resource for the state of Texas at county-level scale. For our pilot project, we created digital geothermal attribute maps (isothermal and depth-at-temperature) for a twenty-county area on the south Texas coastal plain using bottom hole temperature (BHT) data acquired from S&P Global’s Energy Portal and SMU’s Geothermal Lab (>15,000 wells). From these data, thermal gradients were calculated by linear regressions across the study area in 5x5 km bins. A linear interpolation algorithm was then employed to calculate ten temperature-at-depth (1-10km, 1km intervals) and eleven depth-to-temperature (50-300°C, 25°C intervals) rasters from these thermal gradients. These rasters were subsequently contoured, and the contour shapefiles were entered into a GeMS-compliant geodatabase and delivered to the USGS as part of our STATEMAP 2024 contract.
Thermal gradients, raster grids, and shapefiles were all processed, calculated, and generated using the Python programming language (v3.7) and the scipy, geopandas, numpy, and osgeo.gdal modules, among others. Python was employed so that our goal to create a largely automated processing chain could be realized. This project is phase I of a multi-phase effort. Subsequent phases will expand the geographic scope to eventually include the whole state of Texas, as well as incorporate additional data (e.g. uncompiled BHT data) and methodologies (e.g. algorithms incorporating regional lithology) to arrive at more accurate and precise results. We are likewise exploring alternative deliverable datatypes in addition to isoline shapefiles and rasters, including voxelated volumes and triangulated irregular network (TIN) temperature and depth horizons.
Geological Society of America Abstracts with Program. Vol. 57, No. 6, 2025
doi: 10.1130/abs/2025AM-10841
© Copyright 2025 The Geological Society of America (GSA), all rights reserved.
Mapping Geothermal Resources with Python
Category
Topical Sessions
Description
Session Format: Oral
Presentation Date: 10/19/2025
Presentation Start Time: 11:15 AM
Presentation Room: HBGCC, 302B
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