An abundance of horizontal drilling in the Woodford Shale (Late Devonian through Early Mississippian) in the Anadarko Basin, Oklahoma continues to reveal producing trend relationships that when used in combination with other geologically-based data can be used to characterize the fairway. An integrated effort was undertaken to identify, characterize, and map these geological parameters which, when combined into a play fairway map, guide the drilling/appraisal program in the Woodford Shale.
The depositional framework of the Woodford formation served as a starting point to explain the spatial distribution of sweet spot lithofacies. It was derived from examination of three cores that represent a transition from shallower to deep water environments. These environments are outer shelf, intermediate and distal basinal. From the outer slope to deep basin, cores show decreased influence from extrabasinal processes. Regional maps were constructed on Woodford thickness, original gas-in-place (OGIP) and density and neutron log porosity „convergence". Evaluation of numerous parameters indicates that variation in fairway risk can be derived from a combination of these key parameters. The parameters were evaluated using appropriate economic and parametric risk cut off ranges (defined as high, moderate, and low economic risk) to generate an individual risk-level fairway map. The composite play fairway map was generated by statistically combining these individual risk maps. Estimated, non-normalized ultimate recovery (EUR) values derived from 359 producing horizontal wells were integrated with the calculated Woodford thickness, OGIP, and „convergence" thickness results to derive a predictive EUR model. The statistically valid relationship between predictive EUR and produced EUR is evidence that the three key parameters, related to basinal setting and organic preservation, are linked to Woodford well performance. The resultant risk map for the Woodford provides a tool for synergistic integration of existing geology and engineering data to drive an early drilling/appraisal program as well as to testing the production statistics for anomalies.
