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New Bakken Data Analytics Interactive Tool

Date Published: 10/11/2022
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Resource Abstract

This webinar details the uses and convenience of the new Data Analytics Interactive Tool. The completion optimization analysis focused on four areas of the BPS that were identified by a geologic cluster analysis tool, which subdivided the BPS wells into groups using measurements of geologic and geochemical variables, oil and gas properties, and water chemistry. Four subareas, or clusters, of producing wells were identified within the BPS that are characterized by distinctive geologic characteristics. For each cluster, a predictive model was built using the names of fields, operators, and service companies and the values of different completion parameters to predict 6-month cumulative oil production. The goal of running the completion optimization calculations for each cluster (i.e., four separate predictive models) was to remove or minimize variations attributable to geologic heterogeneity and, thereby, strengthen the predictive models and overcome some of the challenges encountered in previous data analytics efforts. The results of the calculations suggested that the predictive models for each of the four clusters were significantly stronger than those created for the entire BPS, indicating that the cluster grouping improved the fitted models by removing some of the geologic variations.

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