Integration of Discrete Feature Network Methods With Conventional Simulator Approaches

Bill Dershowitz; Paul LaPointe; Thorsten Eiben

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Integration of Discrete Feature Network Methods With Conventional Simulator Approaches

机译：离散特征网络方法与常规模拟器方法的集成

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The discrete feature network (DFN) approach offers many key advantages over conventional dual porosity (DP) approaches, par- ticularly when issues of connectivity dominate recovery and res- ervoir stimulation in fractured and heterogeneous reservoirs. DP models have been developed for complex multiphase and thermal effects, and have been implemented for basin scale modeling. However, DP models address only the dual porosity nature of Fractured reservoirs, generally simplifying connectivity and scale- Dependent heterogeneity issues which are modeled efficiently and More accurately by the DFN approach.

机译：离散特征网络（DFN）方法比传统的双重孔隙度（DP）方法具有许多关键优势，尤其是在连通性问题主导着裂缝性和非均质油藏的采收率和储层增产的情况下。已为复杂的多相和热效应开发了DP模型，并已将其用于盆地尺度建模。然而，DP模型仅解决了裂缝性储层的双重孔隙性质，通常简化了连通性和与规模有关的非均质性问题，这些问题通过DFN方法得以有效，更准确地建模。

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《SPE Reservoir Evaluation & Engineering》 |2000年第2期|p.165-170|共6页
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Bill Dershowitz; Paul LaPointe; Thorsten Eiben;
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中图分类石油、天然气工业;
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Integration of Discrete Feature Network Methods With Conventional Simulator Approaches

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