Multivariate Modeling of 3D9C Data for Constructing a Static Reservoir Model of Algal Mounds in the Paradox Basin, CO
La Pointe, Paul1, Robert D. Benson2, and Claudia Rebne3
1Golder Associates Inc, Redmond, WA
2Colorado School of Mines, Golden, CO
3Legacy Energy, Denver, CO
A 3D9C survey was carried out over a six square mile portion of the Roadrunner and Towaoc Fields on the Ute Mountain Ute reservation in southwestern CO. This survey was jointly funded by the US DOE and the Southern Ute tribe's Red Willow corporation to promote development of Ismay algal mound plays in the Paradox Basin within the Ute Mountain Tribal lands and elsewhere in the Paradox Basin. Multicomponent data was utilized to better delineate the external mound geometry as well as to estimate internal mound reservoir parameters like matrix permeability, saturation and porosity. Simple cross-plotting of various multicomponent attributes against reservoir properties did not provide the desired predictive accuracy, in part due to sub-optimal frequency content which degraded attributes derived from the shear wave data. However, a multivariate statistical analysis greatly improved the predictive accuracy. These multivariate regressions were then used to prescribe reservoir properties for a static reservoir model, which in turn formed the basis for a dynamic reservoir simulation model of the project area to assess the usefulness of the multivariate relations developed. This poster illustrates the workflow used to carry out the multivariate modeling, key maps of the reservoir properties that were derived, the static model, and results from the dynamic simulation used to assess the usefulness of the approach. Results from wells drilled based on the seismic data are also presented.
AAPG Search and Discovery Article #90071 © 2007 AAPG Rocky Mountain Meeting, Snowbird, Utah