Beschreibung
This work demonstrates the development and the application of a set of integrated artificial expert systems in the area of forecasting, reservoir evaluation and multilateral well design. The applied method has gradually progressed in degrees of complexity from addressing a preliminary case of volumetric single phase gas reservoirs completed with only dual-laterals towards an expanded form of the same system with varying multi-laterals and reservoir properties to eventually and successfully implementing it to multiphase reservoirs with bottom water drive systems completed with multi-laterals (choice of 2-5 laterals). The developed method and tools cover a wide spectrum of rock and fluid properties spanning tight to conventional sands. The developed approach successfully delivers a total of five distinct artificial expert systems, three of which serve as proxies to the conventional numerical simulator and the other two as inverse-looking solutions, one that addresses the multi-lateral well design problem and the other that estimates critical reservoir properties that can be used at the very least as first estimators in assist history matching problems.
Autorenporträt
Dr.Talal is Acting Unit Head within Reservoir Management Department at Saudi Aramco. Talal holds a PhD in Energy & Mineral Engineering from Penn State University. He's one of the company's leading experts in reservoir management of intelligent fields and artificial intelligence applications. Talal is an SPE member and has published numerous papers.
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