Automated, Cloud-based Well Selection and Ranking Using Artificial Intelligence
Dr. Hamed Darabi, CTO Quantum Reservoir Impact (QRI)
Dmitriy Tishechkin, Partner Global Tech Lead, Oil and Gas, AWS
Emmanuel Gringarten, Senior Director, Product Management at Emerson
Product: SpeedWise® Reservoir Opportunity
Successful reservoir management requires an up-to-date backlog of opportunities (i.e., reperforations, drilling a new well, or a side-track) that an asset team can pursue to meet expected production targets. This is extremely challenging and laborious to generate using traditional workflows.
In this webinar, we introduce SpeedWise Reservoir Opportunity (SRO), an AI-based technology developed as the result of a collaboration between Quantum Reservoir Impact (QRI), Amazon Web Services (AWS), and Emerson. SRO automates steps typically performed during the selection of field development candidates by applying advanced algorithms and AI/ML to multi-disciplinary datasets. This enables teams to rapidly review alternatives by leveraging cloud computing powered by a secure cloud native environment from AWS. The technology brings speed, accuracy, value creation, and risk mitigation to field development plans. Typical benefits are 90% reduction in time and manpower cost, 10X increase in number of scenarios that can be explored, and 20 to 50% annual savings in CapEx/OpEx at equivalent production levels.
Dr. Hamed Darabi is the Chief Technology Officer at Quantum Reservoir Impact (QRI). His current responsibility is to maintain key QRI technologies, expand QRI’s intellectual property, and ensure high-quality delivery of QRI technologies to clients. Since 2013, Dr. Darabi has served as team lead and project manager for multiple field studies, and has been involved in the development of some of QRI's proprietary products. He also worked on several giant fields in the Middle East to implement QRI technologies and perform reservoir studies.
Prior to QRI, Dr. Darabi worked as reservoir engineer at Occidental Oil & Gas Corporation and various companies in the Middle East. His experience spans reservoirs in California, Kuwait, Partitioned Zone, Iran, UAE, Mexico, and Iraq.
Dr. Darabi received his Ph.D. in Petroleum Engineering from the University of Texas at Austin, where he extensively studied reservoir simulator development and mathematical modeling. For his dissertation, he developed a non-isothermal compositional simulator to model asphaltene precipitation, flocculation, and deposition in oil reservoirs and near wellbore. Moreover, he studied the condition of asphaltene precipitation in the Asab Field in UAE during CO2 Injection.
Dmitriy Tishechkin has over 20 years of experience in architecting and delivering enterprise solutions to customers, and is a 15-year veteran of the energy industry. For close to 4 years at Amazon Web Services, Dmitriy has been working with partner communities to build, migrate, and launch their Exploration and Production workflows to AWS. After work, Dmitriy spends time with his family and plays table tennis.