"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.
The Missing Tool Every Geoscientist Needs for the Next Decade
Seismic Soundoff
28 minutes 34 seconds
2 months ago
The Missing Tool Every Geoscientist Needs for the Next Decade
"The glossary will bridge two complex worlds, geoscience and sustainability, and make them easier to understand."
Maria Angela Capello shares her vision for a new glossary that connects geoscience to sustainability in clear, practical terms. She explains how a shared vocabulary can help scientists, educators, and policymakers better understand the purpose and global impact of geoscience work. By linking technical expertise to the UN Sustainable Development Goals, the glossary aims to inspire collaboration, education, and a stronger sense of purpose across the profession.
KEY TAKEAWAYS
> A dedicated glossary can make sustainability concepts easier to understand and apply in geoscience work.
> Geoscientists contribute to all 17 UN Sustainable Development Goals, not just climate-related ones.
> Clear, shared language can help connect technical work to education, policy, and public understanding.
GUEST BIO
Maria Angela Capello (MAC) is a global leader in the energy sector, championing sustainability, equity, and diversity. An active collaborator with the United Nations and major geoscience societies, she has been honored with Italy’s Star of Italy knighthood and UNESCO recognition for advancing the UN Sustainable Development Goals. A sought-after speaker and author of three books, MAC is the only person to serve as a Distinguished Lecturer for AAPG, SPE, and SEG. She advises on sustainability, ESG, and leadership worldwide, with certifications from Cambridge University and IFP School.
LINKS
* Read "The Geophysical Sustainability Atlas: Mapping geophysics to the UN Sustainable Development Goals" - https://doi.org/10.1190/tle40010010.1
* K-12 Resources - https://education.americangeosciences.org/resources
* Practical Geocommunication for the American Geosciences Institute - https://training.geologize.org/pages/agi
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.
