R&D/innovation

Texas A&M Researchers To Develop AI-Powered Drilling System To Accelerate Critical Mineral Discovery

Backed by a $3.5 million US Department of Energy grant, Texas A&M researchers are developing an AI-enabled drilling system that can identify critical minerals in real time, reducing exploration time and costs for rare earth element deposits.

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The team's prototype, seen here, will undergo initial testing at the NOV Springett Technology Center in Navasota, Texas.
Source: NOV.

A team of Texas A&M (TAMU) researchers are looking to advance the time it takes geologists to determine if a site contains sufficient deposits to warrant development. The team, led by TAMU Associate Professor Ramon Shor, SPE, received $3.5 million from the US Department of Energy Advanced Research Projects Agency through its Reliable Ore Characterization with Keystone Sensing program to create an advanced drilling system that can identify valuable minerals in real time. 

The project, Rapid Analysis of Precious and Targeted Ores with Rotary Drilling, consists of the development of a mobile drilling system based on coiled tubing drilling that combines faster drilling technology, real-time rock analysis, and artificial intelligence. The researchers hope their development can reduce the time needed to evaluate potential deposits of rare earth elements and other critical minerals. 

“Critical minerals are essential components in everyday technologies,” said Shor. “But searching for these minerals can take years and cost large amounts of money for sometimes little payoff.” 

The current process of exploration for critical minerals can take years as companies drill hundreds of shallow exploratory boreholes, collect thousands of feet of rock core, and send samples off for analysis.

Shor’s system will utilize advanced sensing technologies and machine learning to identify minerals in real time, allowing drilling teams to make immediate decisions about where to continue drilling.

Shor is working on the project alongside Wencheng Jin and Siddharth Misra, SPE, both from TAMU, Eric van Oort, SPE, Pradeep Ashok, SPE, and Maggie Chen, all from The University of Texas at Austin, Chuck Wright, SPE, from NOV, and David Tonner, SPE, from Diversified Wellbore Logging.

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