Ninth International Geostatistics Congress, Oslo, Norway
June 11 – 15, 2012

No Paper Available


Plenary 4

Abstract No.:



Event-based Geostatistical Modeling: Description and Applications


M.J. Pyrcz, Chevron Energy Technology Company (US)
T. McHargue, Stanford (US)
J. Clark, Chevron Energy Technology Company (US)
M. Sullivan, Chevron Energy Technology Company (US)
S. Strebelle, Chevron Energy Technology Company (US)


Event-based methods provide unique opportunities to improve the integration of geologic concepts into reservoir models. These models are constructed by establishing initial and boundary conditions and generating a sequence of rule-based depositional and erosional events. This may be accomplished over a continuum of complexity from very simple geometric models to complicated formulations. Yet, even the application of simple rules, including few conceptual interactions based on an understanding of stratigraphic relationships and parametric geometries for event scale depositional and erosion features have been shown to efficiently produce complicated and realistic reservoir heterogeneities. In more complicated forms, initial and boundary conditions may be the result of careful analysis of paleobathymetry and external controls on sediment supply and the event rules may be fueled by process models. These models have interesting features that depart from typical geostatistical models. Firstly, these models preserve all information at all scales during their construction allowing for exact down-scaling and placement of realistic reservoir properties. Secondly, these models demonstrate emergent behaviors. While all traditional geostatistical modeling methods honor input statistics, event-based models may exhibit statistics not explicitly prescribed. In typical event-based reservoir modeling applications, these features are not utilized that is models are constructed at a single scale and emergent behavior is suppressed to reproduce a specific conditional model. Yet, these emergent features result in complicated, realistic heterogeneities with various potential research applications. Access to methodologies that rapidly build realistic, scalable and emergent reservoir architectures has enabled a variety of modeling applications including; (1) impact of model scale, (2) seismic resolvability, (3) value of information, (4) flow relevance of advanced architecture, (5) iterative and rule-based conditioning to sparse well and seismic data, (6) numerical analogs for architectural concepts, (7) statistical analysis and classification of architectures, (8) unstructured grid construction and (9) utilization as training and visualization tools.




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