Regional Mapping of Genetic Intervals in the Almond Formation, Greater Wamsutter Field, Southwest Wyoming: An Iterative Geostatistical Approach to High-Grading Well Locations and Implications for Reserves Bookings

Natasha M. Rigg¹ and Jeffrey M. Yarus^2
1Anadarko
²Landmark Graphics/Halliburton

Wamsutter field produces from the Almond formation, a tight gas sand reservoir in the Washakie Basin, and has been, historically, developed as a statistical play with poor correlation to geologic parameters.  In order to continue an economic drilling program and accurate reserve estimation and reporting in Greater Wamsutter field, better prediction of reservoir-quality sands is necessary. Geostatistical methods were utilized to improve the geologic geocellular model and high-grade well locations in order to enhance economics in the field and prepare for future increased density spacing. 

A pragmatic approach was used to conduct a basin-wide, lithostratigraphic analysis of the Almond Formation within the Washakie Basin, using previous studies, increased well control, and additional Almond core.  Further, a unique cross-section analysis was performed using color-filled conductivity, gamma ray, and bulk density logs that were plotted on a single track for each well. Cross-section lines were generated on a closely spaced grid, creating a “pseudoseismic” display, which illuminated flooding surfaces, sands, and coals. Using a Galloway-type approach to genetic stratigraphy, marine flooding surfaces in the middle Main Almond unit were identified and correlated during Phase I of this project. This unique cross section analysis helped to identify eight genetic lithostratigraphic intervals, considerably different from other interpretations.

The total available wells in the field were divided into training and testing sets in order to set up an iterative process for achieving convergence around accurate predictions using a combination of deterministic and stochastic methods. A series of refinement steps where improvements to the log normalization process, well top correlations, and the GDE maps, were performed to allow well locations to be high-graded based on total net sand thickness. The well data were divided into to sets; a training set and testing set.  Training wells were used to create hand-drawn, gross depositional environment (GDE) maps that were used in a collocated cosimulation procedure to ensure the “human” element was included in the model for each interval. Testing wells were used to measure the uncertainty of the final models.

Geostatistical modeling of gross and net sand data proved to be an efficient, cost-effective method to high-grade well locations, given a robust geologic framework. Additionally, the methodology proved valuable in interrogating the data and identifying anomalies, which were either corrected or explained. The result was a reduction in the uncertainty in the geologic framework, and an explanation of the uncertainty that remained.  While this methodology has caused Anadarko to internally change its thinking around Wamsutter gas reserves, the company is currently considering how this new model can be used to formally book reserves.  

AAPG Search and Discovery Article #90098©2009 AAPG Education Department, Houston, Texas 9-11 September 2009