Abstract

Bakken shale has been subjected to more attention during the last decade. Recently released reports discussing the high potential of the Bakken formation coupled with advancements in horizontal drilling, increased the interest of oil companies for investment in this field. Bakken formation is comprised of three layers. In this study upper and middle parts are the core of attention. Middle member which is believed to be the main reserve is mostly a limestone and the upper member is black shale. The upper member plays as a source and seal which has been subject to production in some parts as well.

In this study, a Top-Down Intelligent Reservoir Modeling technique has been implemented to a part of Bakken shale formation in Williston basin of North Dakota. This innovative technique utilizes a combination of conventional reservoir engineering methods, data mining and artificial intelligence to analyze the available data and to build a full field model that can be used for field development. Unlike conventional reservoir simulation techniques which require wide range of reservoir characteristics and geological data; Top-Down modeling utilizes the publicly available data (production data and well logs) in order to generate reservoir model. The model accuracy can be enhanced as more detail data becomes available. The model can be used for proposing development strategies.

The model is then used to identify remaining reserves and sweet spots that can help operators identify infill locations. Furthermore, a predictive model was generated, history matched and economical analysis for some proposed new wells is performed.

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