260: Small Faults, Big Impact - Improving CCUS With Seismic Attributes Seismic Soundoff podcast

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260: Small Faults, Big Impact - Improving CCUS with Seismic Attributes

5d ago 24:05

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“The goal is to keep injected CO₂ safely in place - that’s why understanding fault networks is so critical.” In this episode, host Andrew Geary welcomes David Lubo-Robles, lead author of The Leading Edge paper on detecting small-offset faults for carbon capture and storage (CCUS). David explains how advanced seismic attributes, without relying on machine learning, can help geoscientists better map faults that influence the movement of CO₂ underground. His insights demonstrate the importance of applied geophysics in enabling safer and smarter reservoir management in the era of climate solutions. KEY TAKEAWAYS > Advanced Seismic Attributes Matter: Multispectral coherence and volumetric aberrancy help visualize subtle faults often missed by traditional methods. > Fault Mapping Is Critical for CCUS: Understanding both large and small faults reduces geological risk and improves CO₂ storage safety. > Applied Geophysics Is Essential: From modeling to monitoring, geophysicists play a vital role in every stage of a successful CCUS project. CALL TO ACTION Want to dig deeper into how seismic attributes enhance fault detection for carbon storage? Read David’s paper in The Leading Edge, “Detection of small-offset faults in seismic data: An application for carbon capture and storage.” Whether you're in CCUS, oil and gas, or geothermal, this workflow offers tools you can apply today. Read at https://doi.org/10.1190/tle44040276.1. GUEST BIO Dr. David Lubo-Robles is a Postdoctoral Research Associate and Lead Software Developer at the AASPI Consortium at the University of Oklahoma. David is a geophysicist interested in developing and applying innovative tools using machine learning, quantitative seismic interpretation, and seismic attribute analysis for oil and gas, geothermal reservoir characterization, hydrogen storage, and carbon capture, utilization, and storage (CCUS). His paper, “Quantifying the sensitivity of seismic facies classification to seismic attribute selection: An explainable machine-learning study,” was awarded Honorable Mention, Best Paper in Interpretation in 2022. David received his MS and Ph.D. in Geophysics at the University of Oklahoma. LINKS * Visit https://seg.org/podcasts/episode-260-small-faults-big-impact-improving-ccus-with-seismic-attributes for all the links mentioned in this episode.

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