"Sometimes the traditional methods are way more effective or efficient in handling certain things. To succeed in this new paradigm, we need to build on our strong fundamentals and progress further."
Ivan Lim Chen Ning shares how data-driven methods are reshaping geophysics by challenging traditional workflows and opening new possibilities. He highlights the role of AI, machine learning, and fiber-optic sensing in improving seismic interpretation, imaging, and monitoring. His insights show how combining strong fundamentals with modern digital tools can help geophysicists solve problems more effectively.
Read the September issue of TLE about data-driven geophysics at https://library.seg.org/toc/leedff/44/9.
KEY TAKEAWAYS
> AI and data-driven tools open new paths. They help geophysicists move beyond traditional workflows to find faster and simpler solutions.
> Fiber-optic sensing changes monitoring. DAS provides continuous well data, replacing point sensors and revealing signals directly.
> Strong fundamentals still matter. Success comes from combining proven geophysical methods with modern digital skills.
GUEST BIO
Ivan Lim Chen Ning is an Earth Scientist – Fiber Optics at Chevron, where he analyzes Distributed Fiber Optic Sensing (DFOS) data and develops real-time algorithms for field applications. He applies deep learning and signal processing to improve DFOS workflows, advancing distributed acoustic sensing in the energy industry. A member of Chevron’s Emerging Leader 2024 cohort, Ivan is recognized for solving cross-disciplinary challenges and driving innovation to help secure energy for the future.
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"Sometimes the traditional methods are way more effective or efficient in handling certain things. To succeed in this new paradigm, we need to build on our strong fundamentals and progress further."
Ivan Lim Chen Ning shares how data-driven methods are reshaping geophysics by challenging traditional workflows and opening new possibilities. He highlights the role of AI, machine learning, and fiber-optic sensing in improving seismic interpretation, imaging, and monitoring. His insights show how combining strong fundamentals with modern digital tools can help geophysicists solve problems more effectively.
Read the September issue of TLE about data-driven geophysics at https://library.seg.org/toc/leedff/44/9.
KEY TAKEAWAYS
> AI and data-driven tools open new paths. They help geophysicists move beyond traditional workflows to find faster and simpler solutions.
> Fiber-optic sensing changes monitoring. DAS provides continuous well data, replacing point sensors and revealing signals directly.
> Strong fundamentals still matter. Success comes from combining proven geophysical methods with modern digital skills.
GUEST BIO
Ivan Lim Chen Ning is an Earth Scientist – Fiber Optics at Chevron, where he analyzes Distributed Fiber Optic Sensing (DFOS) data and develops real-time algorithms for field applications. He applies deep learning and signal processing to improve DFOS workflows, advancing distributed acoustic sensing in the energy industry. A member of Chevron’s Emerging Leader 2024 cohort, Ivan is recognized for solving cross-disciplinary challenges and driving innovation to help secure energy for the future.
Adapt or Be Left Behind: Lessons for the Next Generation of Geophysicists
Seismic Soundoff
28 minutes 47 seconds
2 weeks ago
Adapt or Be Left Behind: Lessons for the Next Generation of Geophysicists
"Geophysics plays a central role in this energy transition because it provides the tools and insights needed to understand, manage, and optimize subsurface resources. These resources are critical for both traditional and renewable energy systems."
Geophysics is essential for geothermal energy, carbon storage, hydrogen storage, and critical minerals. Joël Le Calvez and Erkan Ay explain how methods like multi-physics workflows and distributed acoustic sensing are improving reliability, scalability, and safety. They also highlight the skills and mindset geophysicists need to succeed in a rapidly changing energy landscape.
Read the October issue of The Leading Edge that features a special section about geophysics for new energies at https://library.seg.org/toc/leedff/44/10.
KEY TAKEAWAYS
> Geophysics provides the foundation for safe, efficient, and scalable use of subsurface resources in the energy transition.
> Multi-physics workflows and DAS technologies reduce uncertainty and improve monitoring of geothermal and storage projects.
> Future geophysicists must combine technical expertise with adaptability, collaboration, and field experience.
GUEST BIOS
Joël Le Calvez is Principal Geologist at SLB, where he develops software for processing, visualization, and interpretation of microseismic monitoring data. His work supports applications ranging from hydraulic fracture treatment to CO₂ sequestration and geothermal injection, using downhole, shallow wellbore, and surface arrays. Before joining SLB, Joël contributed to research at the Bureau of Economic Geology’s Applied Geodynamics Laboratory and at Etudes et Recherches Géotechniques. He holds a Ph.D. in salt tectonics, an M.Sc. in geosciences, and a B.Sc. in physics.
Erkan Ay is an accomplished geophysicist with more than 18 years of international experience across oil and gas, carbon capture and storage, and academic research. He is recognized for advancing techniques in microseismic monitoring, DAS, 4D VSP, and seismic-while-drilling. Erkan’s work integrates seismology and petrophysics to better characterize complex subsurface structures. Currently, Erkan serves as Chair of the SEG Research Committee and Vice Chair of the SEG IMAGE 2026 Technical Committee, guiding collaborative efforts to advance geophysics for sustainable energy solutions.
Seismic Soundoff
"Sometimes the traditional methods are way more effective or efficient in handling certain things. To succeed in this new paradigm, we need to build on our strong fundamentals and progress further."
Ivan Lim Chen Ning shares how data-driven methods are reshaping geophysics by challenging traditional workflows and opening new possibilities. He highlights the role of AI, machine learning, and fiber-optic sensing in improving seismic interpretation, imaging, and monitoring. His insights show how combining strong fundamentals with modern digital tools can help geophysicists solve problems more effectively.
Read the September issue of TLE about data-driven geophysics at https://library.seg.org/toc/leedff/44/9.
KEY TAKEAWAYS
> AI and data-driven tools open new paths. They help geophysicists move beyond traditional workflows to find faster and simpler solutions.
> Fiber-optic sensing changes monitoring. DAS provides continuous well data, replacing point sensors and revealing signals directly.
> Strong fundamentals still matter. Success comes from combining proven geophysical methods with modern digital skills.
GUEST BIO
Ivan Lim Chen Ning is an Earth Scientist – Fiber Optics at Chevron, where he analyzes Distributed Fiber Optic Sensing (DFOS) data and develops real-time algorithms for field applications. He applies deep learning and signal processing to improve DFOS workflows, advancing distributed acoustic sensing in the energy industry. A member of Chevron’s Emerging Leader 2024 cohort, Ivan is recognized for solving cross-disciplinary challenges and driving innovation to help secure energy for the future.
