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EVEREST™ – An Open-Source Platform For Decision Making Under Uncertainties


Disciplines: Data Science and Engineering Analytics | Health, Safety, Environment, and Sustainability | Reservoir

Course Description

The EVEREST™ tool is a decision support tool that can assist in different decision making under (reservoir) uncertainty, such as drilling order decision, drainage strategy or within well planning. 
The course covers EVEREST main functionalities and applications, related to drilling order optimization and drainage strategy (rates) optimization under reservoir uncertainty. 
The course will be a mix of an introduction to the theory of Robust Optimization and the EVEREST tool, including a demo of the usage and running optimization experiments.

Learning Level

Introduction to Intermediate

Course Length

1-day

Why Attend

To understand robust (under geological uncertainty) optimization theory and implementation using EVEREST. To learn how to prepare/run/analyze EVEREST tool and results. To quantitatively support decision making processes in reservoir engineering.

Who Attends

All subsurface personnel working with or contributing towards decision making and optimization of field development planning using reservoir models.

CEUs

.08 CEU/8 PDH

Cancellation Policy

All cancellations must be received no later than 14 days prior to the course start date. Cancellations made after the 14-day window will not be refunded. Refunds will not be given due to no show situations.

Training sessions attached to SPE conferences and workshops follow the cancellation policies stated on the event information page. Please check that page for specific cancellation information.

SPE reserves the right to cancel or re-schedule courses at will. Notification of changes will be made as quickly as possible; please keep this in mind when arranging travel, as SPE is not responsible for any fees charged for cancelling or changing travel arrangements.

We reserve the right to substitute course instructors as necessary.

Instructors

None Eduardo Barros is lead scientist at TNO for research on decision support workflows applied to the geo-energy sector and the technical lead for EVEREST-related research and consultancy activities. His original background is in petroleum engineering / reservoir engineering, with specialization in optimization-related activities applied to reservoir engineering problems over the years. He holds a PhD from TU Delft, Netherlands on the topic of value of information in closed-loop reservoir management.

None Remus Hanea is the Leading Advisor in History Matching and Optimization in Equinor. He also has a part time professorship position in the Department of Petroleum Engineering, in the group of Petroleum Geoscience.

None Rodolfo Oliveira is a Principal Engineer in Equinor working with research, development and implementations of EVEREST. He is the Project Leader for EVEREST in Equinor. He holds a PhD from Imperial College London in petroleum engineering and has a vas experience working from exploration to development of oil and gas reservoirs.

None Sławomir Szklarz is scientist at TNO, with focus on optimization, history matching and related topics, working on applications in various geo-energy domains. He holds MSc from TU Delft, Netherlands in applied mathematics. He is an optimization expert with advanced knowledge of the EVEREST tool, including its practical usage in real-life large-scale problems and research contributions to its further development.

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