This paper addresses a simulation workflow carried out to identify the key drivers that impact well refracturing performance, improve refrac candidate selection in the Permian basin, and optimize refrac design.
The first step of the workflow involved history-matching numerical models using a fully coupled hydraulic fracturing and reservoir simulator to field observations from two different datasets in the Permian basin. After model calibration, a blind test was conducted to assess the models’ effectiveness in predicting the refrac uplift (the MB1 model was presented in URTeC: 4245581). The initial blind test overestimated the refrac uplift by a difference lower than 10% of the wells’ EUR. The magnitude of behind-casing crossflow was consequently adjusted in the models to improve the match. Comparing Bakken and Permian Basin models, the Permian matches tend to require greater crossflow, possibly because of greater casing size and inner annular area. The calibrated models were then used to carry out a sensitivity analysis on key design variables to compare refrac performance between cases. Finally, an economic optimization analysis was conducted on refrac proppant loading, water intensity and stage length to improve the refrac design for each model from an economic standpoint.
The sensitivity analysis showed that well spacing, infill well spacing and refrac completion size are the main variables that impact long-term refrac uplift. Additionally, well spacing, refrac completion size, well age and infill well spacing have the strongest impact on the short term. Original cluster spacing was seen to have a strong impact on results at wide spacings (≈150ft), and a more moderate impact at tighter spacings (<75ft). Guidelines on refrac candidate selection were put together based on the previous results. The economic optimization showed that the net present value (NPV) trends vary between datasets depending on the difference in incremental uplifts when transitioning from smaller to bigger jobs. This is mostly driven by the amount of new fracture area created versus fracture re-activation. This paper provides new insights to improve refrac candidate selection in the Permian basin and identifies the key operational variables that impact refrac performance. This work also quantifies the expected refrac uplift under different scenarios to improve refrac completion design. Additionally, this paper explores the importance of proper behind-casing isolation to prevent strong crossflow between clusters and fracture re-activation that may lead to worse refrac performance.