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Computational Seismic Interpretation


Our work in computational seismic interpretation is mainly concerned with developing computational methods and algorithms to help seismic interpreters and geophysicists process and understand seismic data more efficiently. Our work covers developing new seismic attributes, detection, and delineation of subsurface structures, developing expressive descriptors for seismic data and using these descriptors to detect and classify certain structures in seismic volumes. We also work on applying various machine learning techniques to help solve various computational seismic interpretation problems including salt dome detection and tracking, fault detection and tracking, semantic segmentation of seismic volumes, and other novel applications.

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