An Integrated Approach to Tight Gas Sand Reservoir Evaluation: Examples from the

Cretaceous Williams Fork Formation in Mamm Creek Field, Piceance Creek Basin,

Colorado

By

Lesley W. Evans

Schlumberger Holditch-Reservoir Technologies, Denver, CO

Steven G. Stancel

Schlumberger Data and Consulting Services, Denver, CO

Michael P. Dempsey

EnCana Oil & Gas (USA) Inc, Denver, CO

Operators have historically had difficulty identifying pay and predicting production from low permeability gas sandstone reservoirs. In the Williams Fork in the Piceance Basin, reservoir properties were assumed to be uniformly poor, with productivity controlled by the relative abundance of natural fractures. Hence operators frequently adapted a statistical approach to this play. Schlumberger’s experience in tight gas sandstone reservoirs indicated that matrix properties were not uniform and that their quantification would significantly advance Williams Fork reservoir evaluation. The evaluation tool built for the Williams Fork play is a robust, integrated log property model.

Log model construction began the identification of rock types based on core-derived relationships of porosity, permeability and grain size. Core data indicates that the majority of Williams Fork reservoirs are microporous and nannoporous (rock types II and III). Further model refinements were accomplished using SEM, XRD, and capillary pressure data that identified occluding cements, clay morphologies and distributions, and pore throat sizes. For individual wells, the Williams Fork log model was calibrated by integrating local data such as fracture distribution, aperture, phi and k from Formation Micro-Imager (FMI) interpretations and water salinity variation from production logs (PLs). Detailed PL analyses (PSPLITR and ProFIT) of individual zone production and stimulation efficiency were compared to log model productivity predictions to further refine the local log model.

The Williams Fork log model and PowerSTIM process provides significantly improved pay identification and a basis for comparing reservoir units, reservoir properties and productivity predictions.

AAPG Search and Discovery Article #90004©2002 AAPG Rocky Mountain Section, Laramie, Wyoming