3D Geological and Seismic Forward Modeling of a Sinuous Slope Channel Complex, Brushy Canyon Formation, West Texas

Tomasso, Mark¹, David R. Pyles¹, Florence L. Bonnaffé¹, David C. Jennette² (1) The University of Texas at Austin, Austin, TX (2) The University of Texas at Austin, Austin,

Seismic interpretation reflects some aspects of the sub-surface geology, but the scaling of seismic images rarely shows the full geological picture. Many stratigraphic architectural elements are typically at higher resolution than the acquired seismic image, and their interpretability on seismic profiles is often limited. The ability to directly compare outcrops with seismic objects has the potential to bridge this scale-gap. Seismic forward modeling of outcrops enables the examination of known stratigraphy and depositional elements at various scales.

We discuss the construction of a fully three-dimensional geologic model, based upon the Beacon Channel outcrop of the Brushy Canyon Formation of west Texas, which is interpreted as a sinuous slope channel complex. A high-resolution 3D digital outcrop dataset was acquired using a ground-based lidar scanner. The main stratigraphic surfaces and architectural elements identified using traditional field methods were interpreted directly onto the digital data, similar to seismic interpretation, providing a detailed 3D outcrop interpretation. These outcrop-constrained stratigraphic data were used to construct a 3D zone-based reservoir model. Petrophysical properties from producing analog reservoirs of similar depositional settings were assigned to lithofacies zones. Use of property transforms allowed an accurate representation of intra-zone facies asymmetry.

Seismic forward modeling of the reservoir model was carried out at several peak frequencies, allowing a direct comparison between outcrop architecture and its seismic image at varying resolutions. Results show that for small multistorey channel complexes, the internal architecture is unlikely to be resolved on exploration-grade seismic data, indicating that knowledge derived from outcrop analogs is crucial for filling in these gaps.