4.5 Article

The impact of fine-scale turbidite channel architecture on deep-water reservoir performance

Journal

AAPG BULLETIN
Volume 97, Issue 2, Pages 251-284

Publisher

AMER ASSOC PETROLEUM GEOLOGIST
DOI: 10.1306/04021211067

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This article concentrates on the question, Which parameters govern recovery factor (RF) behavior in channelized turbidite reservoirs? The objective is to provide guidelines for the static and dynamic modeling of coarse reservoir-scale models by providing a ranking of the investigated geologic and reservoir engineering parameters based on their relative impact on RF. Once high-importance (H) parameters are understood, then one can incorporate them into static and dynamic models by placing them explicitly into the geologic model. Alternatively, one can choose to represent their effects using effective properties (e.g., pseudorelative permeabilities). More than 1700 flow simulations were performed on geologically realistic three-dimensional sector models at outcrop-scale resolution. Water-flooding, gas injection, and depletion scenarios were simulated for each geologic realization. Geologic and reservoir engineering parameters are grouped based on their impact on RF into H, intermediate-importance (M), and low-importance (L) categories. The results show that, in turbidite channel reservoirs, dynamic performance is governed by architectural parameters such as channel width, net-to-gross, and degree of amalgamation, and parameters that describe the distribution of shale drapes, particularly along the base of channel elements. The conclusions of our study are restricted to light oils and relatively high-permeability channelized turbidite reservoirs. The knowledge developed in our extensive simulation study enables the development of a geologically consistent and efficient dynamic modeling approach. We briefly describe a methodology for generating effective properties at multiple geologic scales, incorporating the effect of channel architecture and reservoir connectivity into fast simulation models.

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