Risk assessment of brine contamination to aquatic resources from energy development in glacial drift deposits: Williston Basin, USA

摘要

Contamination to aquatic resources from co-produced water (brine) associated with energy development has been documented in the northeastern portion of the Williston Basin; an area mantled by glacial drift. The presence and magnitude of brine contamination can be determined using the contamination index (CI) value from water samples. Recently, the U.S. Geological Survey published a section (～2.59 km~2) level risk assessment of brine contamination to aquatic resources for Sheridan County, Montana, using oilfield and hydrogeological parameters. Our goal was to improve the Sheridan County assessment (SCA) and evaluate the use of this new Williston Basin assessment (WBA) across 31 counties mantled by glacial drift in the Williston Basin. To determine if the WBA model improved the SCA model, results from both assessments were compared to CI values from 37 surface and groundwater samples collected to evaluate the SCA. The WBA (R~2 = 0.65) outperformed the SCA (R~2 = 0.52) indicating improved model performance. Applicability across the Williston Basin was evaluated by comparing WBA results to CI values from 123 surface water samples collected from 97 sections. Based on the WBA, the majority (83.5%) of sections lacked an oil well and had minimal risk. Sections with one or more oil wells comprised low (8.4%), moderate (6.5%), or high (1.7%) risk areas. The percentage of contaminated water samples, percentage of sections with at least one contaminated sample, and the average CI value of contaminated samples increased from low to high risk indicating applicability across the Williston Basin. Furthermore, the WBA performed better compared to only the contaminated samples (R~2 = 0.62) versus all samples (R~2 = 0.38). This demonstrates that the WBA was successful at identifying sections, but not individual aquatic resources, with an increased risk of contamination; therefore, WBA results can prioritize future sampling within areas of increased risk.