The oil and gas industry has great experience with the applications of data analytics, artificial intelligence, and machine learning in the reservoir engineering discipline, specifically in reservoir surveillance and reservoir modeling and performance prediction. The situation with these technologies is similar to what is happening in other reservoir subdisciplines, for example in reservoir characterization and reservoir management.
Despite the wide range of data science and engineering applications, there is still room for improvement. In this SPE Live, SPE Data Science and Engineering Analytics Technical Director Silviu Livescu and SPE Reservoir Technical Director Rodolfo Camacho address some of the challenges in the application of data analytics, artificial intelligence, and machine learning to several reservoir engineering problems and answer some of the questions related to those applications in reservoir modeling and performance prediction.
Rodolfo Camacho, SPE Reservoir Technical Director
Silviu Livescu, SPE Data Science and Engineering Analytics Technical Director
Birol Dindoruk, Moderator
This video was first presented as an SPE Live event. More SPE Live videos can be found on the SPE Energy Stream.