Seismic Soundoff

209: Thinking like an algorithm - utilizing machine learning in seismic data

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Synopsis

"The driving objective of AASPI is to try and reveal and see more patterns in the seismic data than we can see just looking at the seismic amplitude data." Heather Bedle, Principal Investigator at Attribute Assisted Seismic Processing and Interpretation (AASPI) at the University of Oklahoma, joins Seismic Soundoff. In this episode, you will discover how AASPI reveals hidden patterns in seismic data, pushes the boundaries of geologic interpretation, and reshapes our understanding of the Earth using cutting-edge research and technology. Heather shares insights into how machine learning has been utilized in geophysics for decades, emphasizes the importance of critical thinking when interpreting algorithmic outputs, and discusses the potential biases inherent in machine learning models. Listeners will be intrigued by AASPI's innovative research, including Heather's favorite attribute, aberrancy, which is pushing the boundaries of seismic detail. She also highlights AASPI's drive towards transparency and how