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Tobi Ore: Exploring machine learning, ensuring energy security

Tobi Ore

Tobi Ore, a doctoral candidate in the Department of Geology and Geography, is a driven individual with a longstanding aspiration of contributing to the energy industry. Despite being uncertain of how he was going to accomplish this, he discovered his research niche at the intersection of machine learning and seismic interpretation upon enrolling in graduate school at West Virginia University. Currently working under the guidance of Dengliang Gao, professor of geology, Ore’s research centers around the optimization of subsurface characterization processes using machine learning techniques. Through this work, he aims to improve energy exploration efficiency, enhance understanding of earth systems and reduce carbon footprint through underground storage.

My research on advancing machine learning for geophysical data interpretation would result in more efficient workflows with better flexibility for complex geology which will bolster energy security for society.

Q: Tell us about your research and how you are applying machine learning

A: For my master’s research, I applied machine learning to do more traditional predictions of shale reservoir properties from geophysical logs and seismic data. For my Ph.D., I am focusing on how to advance machine learning capabilities for interpreting seismic data. Seismic data are like an ultrasound for the earth that provides information about the subsurface. I am quantifying the uncertainty and bias associated with using machine learning to create an efficient workflow that will speed up interpretation. In particular, I am looking into cutting-edge methods to increase the reliability of applying machine learning to interpret seismic data from areas with complex subsurface geology. For example, I developed a workflow that incorporates multi-source domain adaptation to the machine learning workflow to achieve human-level performance without any extra manual interpretation of the seismic data.

Q: How much of an impact do you envision this research to have on society?

A:  With more data and computation power, there is a need to improve the speed and accuracy at which subsurface data is interpreted in the search for energy. This is because a clear picture of the subsurface is the goal of many geologic tasks in energy exploration, which has both economic and environmental ramifications. From the search for oil and gas to the effective storage of carbon dioxide, we are always working constantly to understand the structures and stratigraphy of the subsurface which is crucial to provide adequate energy and facilitating the transition to a carbon-neutral energy system. My research on advancing machine learning for geophysical data interpretation would result in more efficient workflows with better flexibility for complex geology which will bolster energy security for society.

Q: How would you describe your graduate school experience at WVU?

A: WVU exposed me to an environment that prioritized research and innovation, leading to a highly enlightening experience. When I came to WVU in 2018, I had zero experience in computer programming, with basic statistical knowledge. I knew these were skills that will be important in the future. I was always hungry to explore avenues that were going to broaden my horizon and, my graduate advisor gave me his full support, and this was what led me to obtain a graduate certificate in applied statistics. I got this extra certificate and knowledge at zero cost, too. The Department of Geography and Geology also gave me the opportunity to gain industrial experience by encouraging me to go for internships, which has aptly prepared me to hit the ground running after graduation. The department also attracts employers in the Appalachian basin to employ students directly from here. This was a plus for us. The vibrant and lively atmosphere of Morgantown has made my stay highly enjoyable. My experience at WVU, in general, has been great.

Q: How have you been handling grad school?

A: My first semester was not what I expected because of the standards I had set for myself, and it put a lot of pressure on me. As I went on to understand the professors better, I found out I was putting undue pressure on myself. I understood how much the professors were willing to help me because they are also humans. They made things clearer for me when I approached them, and I understood what they demanded from me academically. This helped me in settling in better and I adjusted accordingly. I also learned the importance of time management, allowing me to maintain a healthy balance between my academic responsibilities and personal life.

Q: From history, what scientific invention would you have loved to be a part of?

A: The discovery of neural networks has always fascinated me. Neural networks have revolutionized science and technology. It is fascinating that the concept and mathematics behind the neural network are basic, but it is a very powerful tool. Going back in time, I would have been interested in getting involved in its discovery. It is a fundamental component of what we do in machine learning and deep learning. 

Q: How do you spend your free time?

A: Usually, during my free time, I play basketball and soccer at the Rec Center. 

Q: What is your favorite pizza topping

A: I don’t have a favorite topping, but I love “meatzza.” It is the pizza that has a variety of meat. 

Written by Nathaniel Godwin