Predictive statistical models with natural language processing (NLP) rules and knowledge representations can deliver enhanced results for use cases in subsurface and wells disciplines. These range from helping identify bypassed pay, mitigating cognitive bias in well planning, reservoir and field analogue generation, early identification of drilling issues, to generating optimal completion design for petroleum engineers, competitor intelligence, improving search ranking & suggestions, stimulating serendipity, and discovery of new knowledge.
When the new DSEA Technical Section was created in 2022, we started planning a newsletter series, the first of which appeared on December 1, 2022. Paul Cleverley had the privilege of writing the first article of substance of that inaugural issue. The title was Natural Language Processing in the Subsurface and Wells Disciplines, and the article was really an elaborate 13-page paper with figures and references. During this SPE Live, we dig deeper into Paul’s knowledge of how AI applies to Oil & Gas.
Speaker: Dr. Paul Cleverley, from Infoscience Technologies Ltd. in the UK.
Moderated by: Claude Baudoin, independent consultant in IT and Knowledge Management, and member of the SPE Data Science and Engineering Analytics Technical Section.