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This analysis traces how high-performance computing enhances seismic imaging in the oil and gas sector, suggesting future innovations.
Seismic imaging has undergone transformative advances over the past four decades, driven by the coevolution of migration algorithms and high-performance computing (HPC) architectures. ExxonMobil’s journey, from Kirchhoff prestack depth migration to elastic full-waveform inversion, exemplifies how innovations in algorithmic complexity have been enabled by progressive leaps in compute density, memory bandwidth, and energy efficiency. This article traces the history of seismic imaging, inversion, and compute infrastructure at ExxonMobil, highlighting key milestones in algorithm development, hardware acquisition, and workflow integration. It further explores the emerging challenges and opportunities presented by 4D seismic monitoring, hybrid physics-AI workflows, and future HPC architectures. The narrative underscores that sustained advances in subsurface imaging depend on a holistic approach combining physics-based modeling, scalable computing, and power-efficient hardware, poised to unlock unprecedented subsurface insights.
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Suresh et al. (2026) studied this question.
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