Scaling subsurface imaging — The role of high-performance computing evolution in enabling ExxonMobil’s advanced seismic technology
Масштабирование подпочвенной визуализации — роль эволюции высокопроизводительных вычислений в обеспечении передовых сейсмических технологий ExxonMobil
2026-01-01
SCID: 54.1/62u8npxc
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4D seismic monitoringHPC architecturesKirchhoff prestack depth migrationcompute densityelastic full-waveform inversionenergy efficiencyhigh-performance computinghybrid physics-AI workflowsmemory bandwidthmigration algorithmsseismic imaging
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Abstract (AI)
Abstract 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.
Key Findings
1
Advances in seismic imaging at ExxonMobil were driven by coevolution of migration/inversion algorithms and HPC architectures over four decades.
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Emerging challenges and opportunities identified are 4D seismic monitoring, hybrid physics-AI workflows, and adapting to future HPC architectures.
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Key milestones include algorithm development, hardware acquisition, and workflow integration that together advanced subsurface imaging capabilities.
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Progression from Kirchhoff prestack depth migration to elastic full-waveform inversion was enabled by increases in compute density, memory bandwidth, and energy efficiency.
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Sustained improvements in subsurface imaging require a holistic combination of physics-based modeling, scalable computing, and power-efficient hardware.
Research Object
ExxonMobil’s seismic imaging and subsurface imaging technology and workflows
Research Subject
The enabling role of high-performance computing evolution (compute density, memory bandwidth, energy efficiency) and algorithmic advances (migration algorithms to elastic full-waveform inversion) in scaling and improving subsurface/4D seismic imaging, including hybrid physics-AI workflows and workflow integration
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2026-01-01
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