(1) Stanford University, Stanford, CA
ABSTRACT: Bridging the Gap Between Sub-Seismic Geological Heterogeneity and Large Scale Dynamic Data: A Streamline Approach
Building accurate reservoir models means constraining the model to all available data, including static data such as geological heterogeneity information and seismic, and dynamic data in the form of pressure and flow measurement from wells. The current state-of-the-art reservoir modeling does not easily allow such joint integration of static and dynamic data. Most work-flows are hierarchical, first building a static model (geology/seismic), then a dynamic (flow history). Such approach often leads to the destruction of geological information due to the matching to production data which is done often devoid of any geological information, yet comes at the expense of producing predictive models. In this presentation, a new work-flow is presented that jointly integrates all information. Sub-seismic geological information is integrated using a novel geostatistical modeling technique, termed multiple-point geostatistics. Dynamic data is integrated using a new perturbation technique, termed "probability perturbation" that maintains the correct geological heterogeneity while matching the production data. The production data is matched using a novel streamline-based history matching tool that minimizes computing time and allows extracting the sensitivity of dynamic data on fine scale geological heterogeneity. A large case study with more than 130 wells and over 200.000 grid blocks provides proof that the method works in practice.
AAPG Search and Discovery Article #90026©2004 AAPG Annual Meeting, Dallas, Texas, April 18-21, 2004.