Authors: Oscar Mauricio Molina and Camilo Mejia, Enovate Upstream; Mayank Tyagi, Louisiana State University; Felipe Medellin, Beicip Inc; Hani Elshahawi, Novidigitech LLC; Kumar Sujatha, Ayatis



The geothermal energy industry has never quite realized its true potential despite the seemingly magical promise of nonstop, 24/7 renewable energy sitting just below the surface of the Earth. In this paper, we discuss an integrated cloud-based workflow aimed at evaluating the cost-effectiveness of adopting geothermal production in low to medium enthalpy systems by either repurposing existing oil and gas wells or by co-producing thermal and fossil energy. The workflow introduces an automated and intrinsically secure decision-making process to convert mature oil and gas wells into geothermal wells, enabling both operational and financial assessment of the conversion process, whether partial or complete. The proposed workflow focuses on the reliability and transparency of fully automated technical processes for the geological, hydrodynamic, and mechanical configuration of the production system to ensure the financial success of the conversion project, in terms of heat production potential and cost of development. The decision-making portion of the workflow comprises the technical, social, environmental factors driving the return on investment for the total or partial conversion of wells to geothermal production. These components are evaluated using artificial intelligence (AI) algorithms that reduce bias in the decision-making process. The automated workflow involves assessment of the following:

  • Heat Potential: A data-driven model to determine the geothermal heat potential using geological conditions from basin modeling and data from offset wells.
  • Flow Modeling: An ultra-fast, physics-based modeling approach to determine pressure and temperature changes along wellbores to model fluid flow potential, thermal flux, and injection operations.
  • Mechanical Integrity: Casing and completions integrity and configuration are embedded in the process for flow rates modeling.
  • Environmental, Social, and Governance (ESG): A decision modeling framework is setup to ensure the transparent validation of the technical components and ESG factors, including potential for water pollution, carbon emissions, and social factors such as induced seismicity and ambient noise levels.

The assurance of key ESG metrics will ensure a viable and sustainable transition into a globally available low-carbon source of energy such as geothermal. Our novel cloud- based automated decision-making environment incorporates a blockchain framework to ensure transparency of technical-related processes and tasks, driving the financial success of the conversion project. Ultimately, our automated workflow is designed to encourage and support the widespread adoption of low-carbon energy in the oil and gas industry.