PGS/Rock Solid Images

Machine learning for oil and gas exploration

Shale rock

EPCC completed a machine-learning project with Rock Solid Images (now part of PGS), a geoscience consulting firm that provides borehole characterisation with the goal of reducing exploration drilling risk for oil and gas companies.

PGS is one of the main players in the interpretation of seismic data with well log data and it has built its business on using advanced rock physics methods combined with sophisticated geologic models to deliver highly reliable predictions of where oil and gas might be found.

The project focused on optimising the process of petrophysical interpretation by using machine learning. Pattern recognition underlies the action performed by the experienced petrophysicist, so a key question was whether machine learning approaches could bring down the interpretation time from a week to a matter of a few hours or even minutes.

The 12-month project, called Streamlined Workflows for Optimal Petrophysics (SWOOP), was funded by the Oil and Gas Innovation Centre and achieved significant optimisation across various petrophysical workflows utilising a novel machine learning model(s).

It is really interesting not only to learn more about this industry but also see how it is starting to use machine learning techniques to address grand challenges.

Dr Nick Brown EPCC