San Joaquin Valley SPE Section General Section Mtg

Optimization of Well Placement in Waterfloods under Geological Uncertainty

(SPE 191660 - SPE ATCE 2018 – Dallas, TX - Sep 25, 2018)


Thursday, November 8, 2018 @ 11:30 AM

Petroleum Club 12th Floor – 5060 California Avenue, Bakersfield

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Speaker:  Cenk Temizel, Reservoir Engineer, Aera Energy

Reservations:  RSVP by November 6th to avoid walk-in payments

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Or Email Tom Hampton at thampton@sentinelpeakresources.com



     Optimum well placement in intelligent fields, using previously developed optimal control methods to maximize net present value (NPV), is becoming practical with recent advances in technologies as well as their applications in the petroleum industry. To efficiently use these methods in an intelligent field, an assessment of its economic aspects and its performance, especially in reservoirs with high degree of heterogeneity or uncertainty, is crucial. By using such methods, fields can be developed better. The process could be used as a reliable tool for improving the decision-making process.

There are multiple optimization techniques used in the industry for optimizing well placement (e.g. direct and gradient optimization). With the use of a reservoir simulation model, this study aims to provide a comparative performance analysis of certain optimization techniques. To make the evaluation stronger and more applicable to a realistic case, the model selected for this study has a high degree of geological uncertainty and constraints for computation time, infrastructure and complexity to decide on optimal well placements. This will lead to more robust decisions in reservoir management. Identification of the right strategy helps in optimizing larger scale, million-cell model simulations enabling practical implementation of reservoir simulation coupled with optimization.

Optimum well placement in complex reservoirs requires a complete grasp of optimization methods, key factors and constraints but most importantly the understanding of the effect of geological uncertainty. This study illustrates the optimization practices by outlining the significant components in the process illustrated on a benchmark model.


Cenk Temizel is a reservoir engineer at Aera Energy LLC in Bakersfield, California, USA since 2013.  He has 12 years of experience in the industry working on reservoir simulation, smart fields, heavy oil, optimization, geomechanics, field development, EOR with Schlumberger and Halliburton in the Middle East, the US and the UK. He holds a BS degree (Honors) from Middle East Technical University – Ankara (2003) and an MS degree (2005) from University of Southern California (USC), Los Angeles, CA both in petroleum engineering. He was a teaching/research assistant at USC and Stanford University (Heavy Oil Group) before joining the industry. He received Halliburton Innovation Award in 2012 along with US patents and publications in the area of reservoir management, EOR and smart field workflows and 2nd place at SPE Global R&D Competition at SPE ATCE 2014 in Amsterdam. He serves as a technical reviewer for journals. His interests include reaction kinetics/dynamics of fluid flow in porous media and enhanced oil recovery processes.

E-mail: ctemizel@aeraenergy.com

Society of Petroleum Engineers - San Joaquin Valley Section
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