Production trend analytics of the Pronghorn member of the Bakken Formation, Williston Basin, North Dakota

Abstract

Recognizing trends in horizontal targets can help predict the economic limits of a field as well as help rate potential drilling prospects. When assessing acreage making decisions quickly with data from various sources is essential. This study utilized multiple large, publicly available datasets to recognize trends in production data from a zone of interest without reviewing logs on a well-by-well basis. This ``quick look'' technique can be utilized to recognize and understand trends while minimizing geoscientist capital investment. Previous studies erroneously assigned the Pronghorn Member of the Bakken Formation to the underlying Three Forks Formation. Many operators continue this practice of misassignment of the Pronghorn as part of the Three Forks Formation. The Pronghorn also has a history of inconsistent nomenclature which makes using publicly reported production intervals challenging for separating wells producing from the Pronghorn. To separate horizontal wells producing from the Pronghorn top picks were used to delineate the surfaces of the Pronghorn and Three Forks. The Pronghorn and Three Forks top surfaces were used to create upper, and lower, cut-offs for a 3D point cloud. Well deviation survey points were compared to the 3D point cloud with a nearest-neighbor search to evaluate if they fell within the Pronghorn. If sufficient deviation survey points were identified to be within the 3D point cloud, the lateral was considered to be landing in the zone of interest. Production data was normalized for lateral length then assigned to the wells found to be landing in the zone of interest. This 3D point cloud search technique also searched the contents of The North Dakota Geological Survey's Wilson M. Laird Core and Sample Library. Cores separated from the core library were utilized to create isochore maps of the three lithofacies of the Pronghorn. Compiled variables sampled on a grid were evaluated for correlations. Where correlations of |r| > 0.3 were found residuals are normalized and mapped to better understand the controlling variables on production trends.