2008 Joint Annual Meeting (5-9 Oct. 2008): Event-Based Modeling – a New Approach to Improve Our Understanding of Deep-Water Sedimentary Systems

Event-based modeling is a geostatistical approach where stochastic models are constructed from a sequence of depositional and/or erosional events following pre-determined stratigraphic rules. The result is a three-dimensional geologically-realistic model that can be examined within a stratigraphic framework. Other geostatistical algorithms that compute without a temporal sequence of distinct events have limited ability to generate a sedimentological and stratigraphic product representative of physical sedimentation. Compared to “classical” diffusive numerical modeling, the event-based approach differs in: (1) the facility to reproduce realistic high-resolution architecture, (2) the capability to rapidly incorporate intuitive rules, and (3) fast computational times. This modeling is used to predict transport, erosion, and deposition in deep-water systems where our understanding is limited by lack of direct observations.

In event-based modeling, the sedimentological processes and allogenic forcing inherently linked to the depositional record are incorporated as a set of rules that control the final architecture. Rules are conceptual, empirical and integrated with physics-based concepts, usually based on observations from numerous outcrops, high-resolution 3D seismic volumes, modern oceanographic data, and wells. Although there is still significant uncertainty regarding the details of turbidity-current processes, event-based modeling allows us to explore the implications of what we know about longer-term evolution and associated stacking of numerous sedimentation events. The implications of individual rules often can be anticipated, but the interaction of multiple rules may be surprising, which helps guide further research. The final objective is to test event-based modeling as an experimental platform for improving our understanding of fundamental constraints in natural depositional systems.