Optimizing ESP Operations with AI and Machine Learning to Improve Well Performance


30 min


Energy, Oil & Gas,Presentation

At the 2022 Machine Learning in Oil and Gas Conference, SoftServe’s Director of AI and Data Science Iurii Milovanov and Vital Energy’s Principal Data Scientist David Benham presented on how AI and ML applications can improve oil and gas production and discussed the challenges learned from building a ML solution for ESP optimization.

Manual ESP monitoring and management is time-consuming, expensive, and prone to human errors. Intelligent technologies can take the complexity out of operating ESPs helping recognize problems, identify opportunities, and optimize production rates.

Our speakers:

Iurii Milovanov

Iurii Milovanov, SoftServe’s Director of AI and Data Science

Iurii Milanov is a computer science expert with 11 years of experience in building enterprise-level AI, big data and advanced analytics solutions. His research interests include various aspects of modern, progressive IT, and state-of-the-art artificial intelligence, such as distributed and parallel computing, large-scale machine learning, natural language processing, computer vision, and speech recognition.
David Benham

David Benham, Vital Energy’s Principal Data Scientist

David Benham's expertise lies in unlocking the power of data to accelerate Vital Energy’s digital transformation. Prior to joining Vital Energy, David spent an additional nine years in the energy sector and another three years in the manufacturing sector. His focus has primarily been initiatives that solved various business challenges in the well planning, performance, and production domains.

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