Stochastic Modeling of Objects Extracted From High-Quality Seismic Data

In this paper we present an approach for modeling facies bodies based on detailed seismic interpretation of the reservoir’s sedimentological architecture. The approach involves the use of a highly constrained stochastic object model to integrate directly the seismic facies interpretations in a 3D reservoir model. It fills the gap between the use of seismic data in a true deterministic sense, where the facies body top and base are resolved and mapped directly, and stochastic methods where the relationship between seismic attributes and facies is defined by conditional probabilities.

In the new approach the lateral geometry of the facies bodies is controlled by seismic interpretations on horizon slices or by direct body extraction. Facies body thickness and cross-sectional shape are defined by a mixture of seismic data, well data and user defined object shapes. The stochastic terms in the model are used to incorporate local geometric variability which is used to increase the geological realism of the facies bodies and allow for correct, flexible well conditioning.

The result is a set of 3D facies bodies which are constrained to the seismic interpretations and well data. Each body is defined as a “parametric object” which includes information such as: Location of the body axis, depositional direction, axis-to-margin normals, and external body geometry. The parametric information is useful for defining geologically realistic intrabody petrophysical trends and for controlling connectivity between stacked facies bodies.