After a successful new method of geothermal exploration found two new geothermal systems in ÁùºÏ±¦µä, the Department of Energy has awarded a major new grant to the ÁùºÏ±¦µä Bureau of Mines and Geology to research and expand the use of machine-learning to make the exploration process even more effective.
The two successful discoveries in the Great Basin by the ÁùºÏ±¦µä Bureau of Mines and Geology used a previously untried method for finding unknown, hidden geothermal resources, called blind systems, where there are no surface indications of hot water.
There had been no exploration previously in one of these areas and only minor previous exploration in the other. University of ÁùºÏ±¦µä, Reno geologists in the Bureau of Mines and Geology used a number of other surface and subsurface clues in their methodology developed as part of their Department of Energy funded Play Fairway project that has been underway since 2014.
As part of their analysis, James Faulds, director of the Bureau and principal investigator on both the play fairway and machine learning projects, and his team used a few basic machine learning techniques, and now have plans to step up this effort with this newly funded project from the DOE. The project is intended to apply artificial intelligence and machine learning techniques to geothermal exploration to identify previously unrecognized connections between the various datasets.
“This is like icing on the cake of our very successful geothermal play fairway project,” Faulds said. “This new project is aimed at facilitating additional discoveries of geothermal systems in ÁùºÏ±¦µä using machine learning methods and builds on our previous efforts on geothermal play fairways in the region.
“This machine learning project is hopefully the first phase of a long-term, multi-phase program. This first phase is funded at $500,000.”
While the Play Fairway project relied to some degree on expert opinion where machine training data might be used, this new grant will fund the introduction of an additional approximately 100 training sites and the addition of an industry partner with extensive applicable datasets.
For this project, Faulds has assembled a team of scientists from the ÁùºÏ±¦µä Bureau of Mines and Geology, USGS and experts in machine learning from MIT and the oil industry. Machine learning is a technique that teaches computers to analyze data, learn from the data and improve their performance through adaptation. The hope is that there will be higher success rates in geothermal exploration leading to greater efficiency and lower costs for geothermal exploration and development.
In a statement released by U.S. Senators Jacky Rosen (D-NV) and Catherine Cortez Masto (D-NV), they applauded the DOE for selecting the University’s geothermal exploration technology project as one of 10 national projects chosen for funding.
“Thanks to these funds, the University of ÁùºÏ±¦µä, Reno will be able to apply machine learning techniques to geothermal exploration and production,” said the Senators. “This technological investment will help to develop renewable energy technology to create a cleaner future for ÁùºÏ±¦µä and our entire country.”
The mission of the ÁùºÏ±¦µä Bureau of Mines and Geology is to provide the citizens of ÁùºÏ±¦µä with geologic information on geologic hazards and natural resources both to protect the public and facilitate, diversify and enhance ÁùºÏ±¦µä’s economic future. NBMG is a statewide public service unit that applies its expertise to the entire state. It is a division of the University of ÁùºÏ±¦µä, Reno and resides in the Mackay School of Earth Sciences and Engineering in the College of Science. Since its inception in 1929, it has served as the State Geologic Survey of ÁùºÏ±¦µä and a Bureau of information and analysis for geologic data throughout the state.
