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Loic Bethel Dje, Oklahoma State University petroleum engineering graduate student, along with his team members Juan Carlos Soberanes Merodio, independent drilling optimization manager, Oluchi Osuagwu, independent data scientist, and Vivek Kesireddy, a graduate student at Texas A&M University received third place at the Geothermal Energy from Oil + Gas Demonstrated Engineering (GEODE) Datathon for their project titled “Fracture Flow Facilitators”. 

 

Their project focused on analyzing connectivity and fracture-driven flow behavior in enhanced geothermal systems using tracer data, flowback responses and analytical modeling. By estimating flow velocities, residence times and heat recovery potential, they developed a predictive framework for long-term thermal performance.

Their future work will focus on integrating real-time field data, machine learning and digital twin technology to enhance geothermal reservoir design and optimize sustainable energy extraction.

 

This work will be presented during the George Stutz Student Days held on July 30, 2025 at the University of Nevada, Reno.

 

The GEODE consortium hosted two Datathons that tested the skills of emerging subject matter experts. Led by industry experts, the datathons invited students and young professionals with backgrounds in oil and gas (O&G) and geothermal energy to participate in unique challenges that used real, field-case analyses to explore the areas where geothermal and O&G technologies come together.

 

More than 140 participants from across the United States formed 43 teams representing 27 universities and 25 companies. Teams and individual participants submitted solutions that were innovative and unexpected, creating a difficult decision for the GEODE judges and giving them hope for the future of the geothermal sector.

 

“The Datathons, built through GEODE and powered by dedicated volunteers, showed the strong interest and skills of a new geothermal workforce ready to lead with data, collaboration, and creativity,” said Higinia Torregrosa, the U.S. subsurface lead for Project InnerSpace who coordinated the Datathons.

 

The Geosciences Datathon asked participants to develop ways to identify blind geothermal systems. Participants had to create innovative solutions using datasets from Nevada’s Great Basin, a region rich with geothermal activity. Their solutions used geophysics, geology, and machine learning to predict high-enthalpy zones where no surface signals exist.

 

Roland Horne, a Stanford University professor who specializes in geothermal energy and reservoir engineering, was one of the judges for the Geosciences Datathon and was impressed by the solutions submitted. “A lot of good projects, many of them innovative and well presented,” he said.

 

The Engineering Datathon focused on optimizing geothermal energy production through comprehensive data science applications. Participants used multiple datasets, including those from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE), a dedicated underground geothermal field laboratory sponsored by the U.S. Department of Energy. Datathon teams used that information to develop data-driven models to improve subsurface heat exchange and energy recovery efficiency by incorporating earthquake data, fiber optic temperature sensing, tracer tests, hydraulic fracturing logs, and more.

 

Pushpesh Sharma, director of product management at Aspen Technology and one of the judges of the Engineering Datathon, applauded all the submissions during a virtual awards ceremony on June 20. “I was very surprised by the quality of the submissions,” he said. “I think all of you did a great job.”

 

Read the full article here: GEODE Datathon Winners Announced | GEODE