In this work we address the importance of numerical modeling for conducting sensitivity analysis of stacked, multi-stage, multi-well pad completions, as well as multi-pad completions, to optimize well placement and maximize well productivity. Designing stacked, multi-stage, multi-well, completions requires an evaluation of the induced stresses between interacting fractures and the effect that these stresses introduce into the growth of subsequent fractures. We tested the importance of the induced stressess by using two hydraulic fracture simulators that evaluate fracture geometry, propped surface area, and the local and far-field induced stresses at the end of the fracture treatment.

Using a real case study in the Midland basin, we investigated the consequences of optimizing well placement to maximize well productivity using single-well simulations (i.e., assuming standalone wells), compared to conducting the same optimization using multi-well modeling (i.e., field zipper frac configuration). Results show that one cannot optimize the placement of stacked wells by treating them as standalone wells.

We also investigated the effect of zipper fracture sequencing on the propped surface areas and well productivity. Results show that fracture sequencing affects the order of interaction between fractures and their associated induced stresses. In turn, this leads to changes in the fracture geometry and propped surface area, and thus influences the productivity of the entire pad or multi-pad system. The consequences of these changes are not easy to anticipate based on the knowledge of the individual well's behavior (either single stage modeling or multi-stage modeling). For the present case under investigation, after selecting the optimal wells placement, the propped surface area was practically insensitive to fracture sequencing. This, however, is not commonly the case. Furthermore, results showed a strong sensitivity to leakoff and the corresponding fracturing fluid efficiency. Unfortunately, this is not a parameter that can be controlled (except by using fluid loss additives and viscocifying agents). At the same time, this demonstrates the necessity of obtaining field leakoff measurements for accurate modeling.

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