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.