--> Representing Geological Detail in Dynamic Modeling of Turbidite Reservoirs, by Frans van der Vlugt, Omer F. Alpak, Mark Barton, Carlos Pirmez, Kachi K. Onyeagoro, and Stephen J. Naruk; #90052 (2006)

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Representing Geological Detail in Dynamic Modeling of Turbidite Reservoirs

Frans van der Vlugt, Omer F. Alpak, Mark Barton, Carlos Pirmez, Kachi K. Onyeagoro, and Stephen J. Naruk
Shell International Exploration and Production, Houston, TX

The complex, multiscale nature of turbidite channel deposits in faulted reservoirs poses a significant challenge for geologically-consistent dynamic reservoir modeling. Conventional object-based geological modeling techniques employ geobodies that are randomly distributed within a regular grid. Use of such techniques often leads to the dilemma of choosing between an excessively large numerical mesh versus a coarser mesh with insufficient representation of stratigrapic relationships among geobodies. The latter choice provides for computational efficiency and is often the favored option, but implies in poor representation of key bounding shales that may occur between and within such geobodies. Extensive dynamic simulations irrevocably demonstrate that such bounding shales exert a substantial imprint on the sweep efficiency and ultimate recovery of reservoirs.

A novel workflow is developed for realistic three-dimensional modeling of turbidite channel reservoirs with complex structural and stratigraphic architectures. Our workflow employs a surface-based algorithm with the capability of generating complex channel architectures that range in scale from an individual bed to an entire canyon fill. A conforming irregular mesh is consistently used for both stratigraphic and dynamic reservoir modeling. Many of the limitations of object-based techniques are overcome without creating excessively large models. The impact of faults and stratigraphic heterogeneities on reservoir dynamics is accurately represented using state-of-the-art fault transmissibility models. Geological modeling parameters and their associated statistical distributions are derived from a proprietary database of stratigraphic and structural data accumulated over the years from turbidite outcrops and reservoir analogues.