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Портал Begell Электронная Бибилиотека e-Книги Журналы Справочники и Сборники статей Коллекции
International Journal for Uncertainty Quantification
Импакт фактор: 4.911 5-летний Импакт фактор: 3.179 SJR: 1.008 SNIP: 0.983 CiteScore™: 5.2

ISSN Печать: 2152-5080
ISSN Онлайн: 2152-5099

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International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2012003765
pages 259-278

EFFECTIVE PARAMETRIZATION FOR RELIABLE RESERVOIR PERFORMANCE PREDICTIONS

Xiao-Hui Wu
ExxonMobil Upstream Research Company, P. O. Box 2189, Houston, TX 77252, USA
Linfeng Bi
ExxonMobil Upstream Research Company, P. O. Box 2189, Houston, TX 77252, USA
Subhash Kalla
ExxonMobil Upstream Research Company, P. O. Box 2189, Houston, TX 77252, USA

Краткое описание

The purpose of reservoir modeling and simulation is to predict reservoir performance for development and depletion planning. Despite decades of research, efficient and reliable reservoir performance predictions are still a challenge in practice. In this paper, we present an overview of reservoir modeling as it is commonly practiced today and the challenges it faces. More specifically, we focus on the challenges posed by the large amount of uncertainty inherent in the characterization of reservoirs that are heterogeneous at multiple scales. We discuss the practical implications of these challenges and recent developments toward addressing them. In particular, we examine the need for effective parametrization of geologic concepts and related recent advances in parametrization and parameter reduction techniques, including their advantages and limitations. Using numerical examples from two different depositional environments, we show that effective parametrization can be achieved by taking advantage of the geologic hierarchy underlying most geologic concepts and a general understanding of the impact of geologic features on fluid flow. Finally, we propose an approach to systematically derive fit-for-purpose parametrization for practical reservoir modeling problems.


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