Optimization of Well Placement Under Time-Dependent Uncertainty

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Abstract/Contents

Abstract
Determining the optimum location of the wells is a crucial decision to be made during afield development plan. The quality of the decision is strongly dependent upon the amount of the information available to the decision-maker at the time the decision is made. Knowing that the development phase of a reservoir is a dynamic period in which different categories of information are added to system from distinct sources, one should make the well placement decisions considering these time-dependent contributions of information. This study proposes an approach that addresses the value of time-dependent information to achieve better decisions in terms of reduced uncertainty and increased probable Net Present Value (NPV). A Hybrid Genetic Algorithm (HGA) was used as the optimization method to find the best locations of the wells. In order to find the optimum decisions for different risk attitudes, a utility framework, that enables the assessment of the uncertainty of the well-placement decisions, was used. Through this new approach, production history data obtained from the wells, as they are drilled, are integrated into the well placement decisions. Unlike previous approaches, well placement optimization is coupled with recursive history matching steps. To test the results of the proposed approach, an example reservoir and its realizations, all of which match the history response of the example reservoir, were investigated. At each step of optimization, a reduction in the uncertainty of the multiple realizations was observed, as production history became available.

Description

Type of resource text
Date created June 2004

Creators/Contributors

Author Ozdogan, Umut
Primary advisor Horne, Roland N.
Degree granting institution Stanford University, Department of Petroleum Engineering

Subjects

Subject School of Earth Energy & Environmental Sciences
Genre Thesis

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User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.

Preferred citation

Preferred Citation
Ozdogan, Umut. (2004). Optimization of Well Placement Under Time-Dependent Uncertainty. Stanford Digital Repository. Available at: https://purl.stanford.edu/yf084bb3073

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Master's Theses, Doerr School of Sustainability

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