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Seismic Soundoff

Seismic Soundoff

In-depth conversations in applied geophysics.

 
     

11 Aug 2022

Episode 159: Optimizing the benefits of machine learning for scientific problems


Souvik Mukherjee discusses his article in July's The Leading Edge about high-resolution imaging of subsurface infrastructure using AI.

The use of drones for geophysical data acquisition and artificial intelligence (AI) for geophysical data processing, imaging, and interpretation are active focus areas in current industry and academic applications. Unlocking their cumulative potential in single-focus applications can have a transformative impact, possibly leading to dramatic cost reductions in key use cases and new application areas for enhanced actionable business intelligence.

In this conversation, Souvik presents field study results from Texas and California that show the potential for imaging pipelines and other subsurface infrastructure using AI-based methods on high-resolution aboveground magnetic data. He also highlights the similarities and differences between conventional least-squares inversion and machine learning-based inversion and how he achieved a 100-fold increase in efficiency. Whether exploring AI, machine learning, algorithms, or the latest geophysical technology, this conversation has something for everyone.

Related links


Subscribers can read the full articles in the SEG Library, and abstracts are always free.

Credits

SEG produces Seismic Soundoff to benefit its members, and the scientific community and inform the public on the value of geophysics. To show your support for the show, please leave a 5-star rating on Apple Podcasts and Spotify. It takes less than five seconds to leave a 5-star rating and is the number one action you can take to show your appreciation for this free resource. And follow the podcast while you are on the app to be notified when each new episode releases. 

Original music created by Zach Bridges. This episode was hosted, edited, and produced by Andrew Geary at 51 features, LLC. Thank you to the SEG podcast team: Jennifer Cobb, Kathy Gamble, and Ally McGinnis.

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