Using Evolution Strategy with Meta-models for Well Placement Optimization

Details Using Evolution Strategy with Meta-models for Well Placement Optimization Using Evolution Strategy with Meta-models for Well Placement Optimization

2010-11-24

arxiv.org/abs/1011.5481v1

Computer Science

Computational Engineering, Finance, and Science

ECMOR XII - 12 th European Conference on the Mathematics of Oil Recovery, Oxford : Royaume-Uni (2010)

Scientific paper

Optimum implementation of non-conventional wells allows us to increase considerably hydrocarbon recovery. By considering the high drilling cost and the potential improvement in well productivity, well placement decision is an important issue in field development. Considering complex reservoir geology and high reservoir heterogeneities, stochastic optimization methods are the most suitable approaches for optimum well placement. This paper proposes an optimization methodology to determine optimal well location and trajectory based upon the Covariance Matrix Adaptation - Evolution Strategy (CMA-ES) which is a variant of Evolution Strategies recognized as one of the most powerful derivative-free optimizers for continuous optimization. To improve the optimization procedure, two new techniques are investigated: (1). Adaptive penalization with rejection is developed to handle well placement constraints. (2). A meta-model, based on locally weighted regression, is incorporated into CMA-ES using an approximate ranking procedure. Therefore, we can reduce the number of reservoir simulations, which are computationally expensive. Several examples are presented. Our new approach is compared with a Genetic Algorithm incorporating the Genocop III technique. It is shown that our approach outperforms the genetic algorithm: it leads in general to both a higher NPV and a significant reduction of the number of reservoir simulations.

Affiliated with

Also associated with

No associations

Rating

Using Evolution Strategy with Meta-models for Well Placement Optimization does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Using Evolution Strategy with Meta-models for Well Placement Optimization, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Using Evolution Strategy with Meta-models for Well Placement Optimization will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-586173