A Fully Integrated and Updated Geothermal Gradient Atlas of the World

Abstract Scope The energy transition offers multiple opportunities for traditional energy companies and their geoscience workforce to explore for new types of energy resources. In this paper. we report on new initiatives to develop fully integrated databases using GIS and AI to provide added value and new insights into the world's current and diversified existing data repositories. One such initiative, the Global Heat Flow Database (GHFD), seeks to create a geothermal gradient atlas of the world, combining existing maps and data into a searchable, georeferenced mapping format with layers reflecting temperatures, landforms, geological features, and other information for making decisions about exploring for geothermal energy, and siting and developing geothermal plants and infrastructure. The project scope is global and requires the mining and integration of large modern and archived data sets. We also list several diverse datasets that are complementary to creating a truly global database, and we provide examples of methods and workflows involved in the process of prospecting for geothermal resources and creating geothermal heat flow gradients and maps. Methods The global geothermal gradient atlas involves a team effort by geologists and data scientists to identify, QC, and classify relevant geothermal data from structured and unstructured sources, including public and commercial databases, maps and reports, and other repositories of georeferenced temperature and depth. The processes of combining databases, clean up and QC of data, and incorporation of different functional layers in a GIS system will involve several important steps: 1) creating a uniform standard for managing the data; 2) utilization of platforms that enable data acquisition, ingestion, cleaning, and application of various machine learning algorithms to assure quality and uniformity; and 3) including other useful and related data, which will be available as layers in the GIS system. Results The resulting database will be available as a searchable atlas for industry and academia use, and from which custom maps, studies, and data can be exported. The global geothermal atlas database will adhere to FAIR Data Principles (Findable, Accessible, Interoperable, and Reusable). First deliverables will consist of the integrated geothermal gradient temperature and depth data for use with QGIS, ArcGIS or other GIS mapping software. Apps will allow the atlas users to compare the geothermal prospectivity by geographical location, and to rank in terms of amenability to development according to geothermal resource and proximity to end users and conveyance infrastructure. Discrete database layers will include geographic landforms, major infrastructure, and geological information including fault systems and major structural features. Novel information Several aspects make the project unique and differentiate it from others. First, is the fact that state of the art data management and machine learning systems will be used to ingest, classify, clean, and easily access the data. The results will be a geothermal gradient database and atlas that are significantly more accurate than those in use today. Second, is the fact that accessibility and front-end apps will make the data base multi-functional and suitable for a wide range of geothermal applications, including exploration for optimal sources near communities, siting and developing sedimentary and igneous geothermal plants, identifying prospects for shallow as well as deeper geothermal energy generation, and repurposing producing, declining, or abandoned oil and gas wells for use in geothermal energy production.