SPE and Project Innerspace are organizing the first Geothermal AInnovation Competition, hosted by the SPE Gulf Coast Section and the SPE Data Science and Engineering Analytics Technical Section. Teams from around the world are invited to participate in this exciting virtual competition aimed at showcasing the potential of AI-assisted workflows in the geothermal lifecycle. This contest is the third collaboration between SPE and Project Innerspace, after the SPE Geothermal Datathon organized at PIVOT2022 and the SPE Geothermal Datathon that is closing in July and will be announced at PIVOT2023. SPE and Project Innerspace, together with Geothermal Rising, have been selected by DoE to be the administrators of GEODE project, a 5-year initiative to facilitate technology transfer from oil and gas into geothermal, announced in May.
The inaugural Geothermal AInnovation Competition challenges the participating teams to propose LLM-based workflows for any discipline (geophysics, geology, drilling and completions, reservoir engineering, production engineering, process engineering, and HSES) that would support accelerated assessments to facilitate the implementation of geothermal projects, paving the way for a greener and more sustainable future.
This competition aims to highlight the disruptive force of LLM to accelerate geothermal, from field development to research and development of new enablers. Participants are allowed to utilize any of the existing pre-trained models in the public domain to present conceptual ideas of applications of LLM-models into the lifecycle of geothermal developments.
The registration is open to all AI-enthusiasts that want to explore opportunities in the geothermal world. This is a good opportunity for students and young professionals to utilize advances of AI to excel in a new energy domain.
The competition is scheduled to start on July 26 and allows participations in teams of 1 to 4 members. The participants will have until August 31 to develop an LLM-based workflow applicable to a geothermal energy topic. Participants will submit a video of maximum three minutes where they will describe the target problem, the selected information and datasets to apply the LLM model and a visualization of how the coded workflow works in one geothermal example. To ensure homogeneity among proposals, participants are requested to use only open access pre-trained LLM models. The winning team will be announced at PIVOT2023 on September 20.
Register here - SPE-GCS
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PushpeshSharmaAspenTech
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