Print this pageA Showcase of Reservoir Models Generated by Event-Based Geostatistical Modeling
Michael J. Pyrcz1, Morgan Sullivan1, Timothy McHargue2, Nicholas Drinkwater1, Julian Clark2, Andrea Fildani2, and Henry W. Posamentier1
1Earth Science R&D, Chevron Energy Technology Company, Houston, TX
2Earth Science R&D, Chevron Energy Technology Company, San Ramon, CA
Geostatistics is often used to build multiple models of reservoir geological heterogeneity for the probabilistic assessment of reservoir flow response. Current geostatistical algorithms enable the reproduction of spatial statistics inferred from available conditioning data and analogues, but rarely integrate information related to depositional processes. Indeed, because conventional geostatistical models are constructed without any concept of time or depositional sequence, they have a limited ability to incorporate the sedimentological, stratigraphic, and process-based rules, which explain the distribution and architectural stacking patterns of facies geobodies with implication for porosity/permeability heterogeneity.
The event-based approach was recently introduced as a new branch of geostatistics, wherein stochastic models are constructed as a sequence of depositional events. The sedimentological process and allogenic forcing are incorporated as a set of empirical and predictive rules that control architecture.
These models comprise: type models for training, demonstration to test flow response sensitivities, constraint training images for multiple point simulation; or even conditioning to sparse well data and soft data (seismic). Furthermore, event-based geostatistics may be applied as a new framework to test selected sedimentological rules and analyze their impact on reservoir heterogeneity, as even straightforward rules are difficult to test without a numerical laboratory, due to feedbacks and interactions between rules.
Rules are developed to build event-based models that represent slope valley and distributary lobe complex deepwater settings. The resulting models showcase the power of simple, intuitive rules to reproduce complicated architecture and expand our understanding of depositional systems.
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