Machine Learning Interprets Like Experts

The SubsurfaceAI Seismic application includes a new generation of deep learning models and is aligned with the OSDU Data Platform. These pattern recognition-based models work within and across seismic data, bringing the power of AI to the classic expert-led approach.
 
SubsurfaceAI Seismic is designed for operators for whom gaining a deep understanding of the subsurface from complex data sets – large and small, new and old – is critical to business success.
 
  • Interpret with orders of magnitude greater efficiency.
  • Integrate, visualize and develop new AI/machine learning models.
  • Gain unique understanding enabled by pattern recognition-based AI.
  • Import results into industry standard software packages, aligned to OSDU. 

4m12s | Learn about SubsurfaceAI Seismic, a cloud native application with a web front end, employing pattern recognition-based machine learning models, aligned with the OSDU Data Platform.

SubsurfaceAI for Seismic

In this 1-minute video, geoscientist and VP Energy Solutions Mason Dykstra sets out how a new generation of AI models based on pattern recognition and built into SubsurfaceAI applications enables seismic experts to interpret with human intuition.

Introducing Pattern Recognition AI

In this 5-minute video, Ben Lasscock, Energy Solutions Group Technical Lead, provides a deep dive into the SubsurfaceAI custom deep learning application for seismic, from labeling just a few lines and QCing predictions, to a final interpretation of the data set. 

AI/Machine Learning Interpretation Technology Updates

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You know seismic. We know Python.

Today, there are two major barriers to achieving the potential of deep learning in seismic interpretation; being able to quickly and consistently label seismic data, and being able to access (and use) a deep learning toolkit that enables quick experimentation with models, while iterating and managing all the data associated with your model and results.

Geophysicists need to be highly efficient at producing labeled data to train (and later, iteratively QC) deep learning models to deliver high quality interpretations.

SubsurfaceAI seismic overcomes both barriers. With as few as three interpreted seismic lines, the pattern recognition-based deep learning models enable you to create robust predictions across the entire seismic volume.

In this 4-minute video, Ben Lasscock, Energy Solutions Group Technical Lead at Enthought, discusses one of the deep learning elements of SubsurfaceAI for seismic, automating the interpretation of sequence stratigraphy.

Explore a New Generation of Digitally Enabled Workflows