Characterizing and Modeling Fluvial Facies and Petrophysical Properties of a Pinedale Tight-Gas Reservoir in Greater Green River Basin, Wyoming

Ma, Yuan Zee¹, Terry Young², Earnest Gomez¹, Dennis Cox³, Fabian Iwere⁴ (1) Schlumberger, Denver, CO (2) BP, Houston, TX (3) BP America Production Company, Houston, TX (4) Schlumberger, Greenwood Village, CO

Pinedale Field produces gas from fluvial channel sandstones of the Upper Cretaceous Lance and Mesaverde formations in the Green River Basin, Wyoming. As the petrophysical properties are highly correlated with the facies, accurately modeling the facies is very important for determining the subsurface pore space, fluid distribution, and flow characteristics.

Fluvial facies were first defined at the well logs using a multi-step classification method that integrates gamma ray, resistivity, porosity and fluid-saturation logs. The method proves to be more robust in defining minority facies such as crevasse-splay when compared to neural-network and traditional statistical methods. Although such classified facies data are very important to guide the 3D modeling of the facies distribution, they don't give lateral dimensions, sinuosity and orientations of channels. Analog data were used to define fluvial object dimensions. The seismic data and attribute analyses provided an understanding of the regional geologic trends and channel orientations. Object-based modeling technique was used to integrate the well-log facies prediction, analog object dimension, channel sinuosity and orientation in building a 3D facies model. The final facies model mimics the ancient river deposition of channel, crevasse-splay and overbank facies.

The facies model was subsequently used to guide the petrophysical property modeling. The dependencies between rock properties were analyzed, and a workflow of modeling porosity, water saturation and permeability was developed using geostatistical methods. The final model honors the fluvial depositional characteristics and dependencies between the rock properties, and has improved the understanding of reservoir performance and reserve assessment.