AI-driven Reservoir Management through Streamlined Opportunity Identification and Ranking in the AWS Cloud.


In this webinar, learn how to streamline opportunity identification for field development planning, maximizing return on capital investments, shortening decision cycles, and lowering risks.

Successful reservoir management requires an up-to-date backlog of opportunities that an asset team can pursue to meet expected production targets (such as re-perforations, drilling new wells, sidetracks and more). This involves a combination of geological knowledge, reservoir behavior, production history, completion information, and multi-disciplinary expertise. The process of gathering and analyzing data, identifying opportunities and then vetting each one of them is labor-intensive, and generally takes several months. When looking at alternative scenarios by considering different hypotheses, little time and resources are left to validate multiple candidates rigorously, which decreases confidence in the decisions being made.

Our presenters will talk about a movement towards digitalization and automation in reservoir management, and how a fully automated, collaborative cloud-native solution is revolutionizing the way asset teams work by applying advanced computational algorithms, AI, and data mining techniques to multi-disciplinary data. Additionally, they will explain how AWS cloud technologies enable digitalization, automation, and the new way of work.

During this webinar the presenters will cover how the solution:

  • Applies an automated, unbiased and systematic approach to opportunity identification.
  • Identifies many opportunities in a fraction of the time (largest/most cost effective/least risky ones), allowing more time for vetting of opportunities.
  • Integrates multidisciplinary data coherently, managing missing information, using a data-driven approach coupled with geo-engineering constraints.
  • Efficiently looks at alternative scenarios by varying initial assumptions.
  • Enables multi-disciplinary collaboration by breaking down functional silos.
  • AWS cloud role in automation, integration and multidisciplinary collaboration.

About our Presenters:

Hamed Darabi
Dr. Hamed Darabi
Chief Technology Officer, Quantum Reservoir Impact
Since 2013, Dr. Darabi served as the team lead and project managers for multiple field studies and was involved in the development various QRI's proprietary products. Prior to QRI, Dr. Darabi worked as reservoir engineer at Occidental Oil & Gas Corporation and various companies in Middle East, since 2006. 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 Asab Field in UAE during CO2 Injection.



Emmanuel Gringarten
Dr. Emmanuel Gringarten
Senior Director of Product Management, Emerson
As Senior Director of Product Management at Emerson, Emmanuel Gringarten is responsible for geology, reservoir, and production solutions. Emmanuel has 25+ years of expertise in developing reservoir modeling and reservoir engineering applications. He holds a Bachelor of Science in Mathematics from Imperial College, London and a Master and PhD in Petroleum Engineering from Stanford University.





Dmitriy Tishechkin
Dmitriy Tishechkin
Prinicipal Partner Technical Lead, Amazon Web Services
Dmitriy Tishechkin has over 20 years of experience of architecting and delivering enterprise solutions to customers, and 15 years spent in Energy industry. For more than 4 years with AWS, Dmitriy has been working with partner community to build, market, and launch their Exploration and Production workflows on AWS. Dmitriy is interested in renewable energy and reducing carbon footprint technologies.

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