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Deep Learning/Machine Learning Technical Interest Group (TIG)

Applying new analytics, neural networks, computational approaches using structured and unstructured data, and also training neural networks with supervised and unsupervised algorithms. Chaired by Patrick Ng and Andrew Munoz.

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Last Post 12 Feb 2021 12:57 PM by Patrick Ng

Why Energy in Data 2021?

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Patrick Ng

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Posts:148

12 Feb 2021 12:57 PM
As any emerging technologies, often we struggle through the initial period of cutting-edge and bleeding edge, before reaching wider adoption and wiser application. As in AVO (used to derisk prospects predrill) and depth imaging (credited for opening up the entire Gulf of Mexico deepwater subsalt play), “conventional wisdom” changed from convention to convention before we as an industry converged on a set of best practice based on play and geology. Anticipate the use of AI and machine learning (ML) will continue to grow, I see EiD 2021 at the critical juncture of tech, creativity and analytics, e.g., ML for stacked pay development and collaboration for delivering the lowest cost BOE. Participation helps us move fast from efficiency to efficacy, which translates into savings in cost and time, for thriving in the post-covid world. Be a player. https://energyindata.org/
Attachments A letter from the Energy in Data co-chairs.pdf