This paper presents results from a collaborative industry study involving ten high-quality pad-scale datasets from the Delaware Basin, Midland Basin, Bakken, and Montney. The study had three primary goals: (a) compare/contrast observations between each dataset, (b) identify general strategies that can be used to mitigate parent/child impacts, and (c) provide concrete recommendations to optimize fracture design and well placement. For each dataset, an integrated hydraulic fracturing and reservoir simulation model was constructed and history matched to the observations. The models were calibrated to production data and pressure measurements, as well as to diagnostics such as: distributed acoustic sensing (DAS), microseismic, downhole imaging, chemical tracers, geochemical production allocations, and pressure observations from offset wells. History matching was performed by varying formation properties and model inputs to ensure consistency with the observations. Once the models were calibrated, the same set of approximately 120 sensitivity analysis simulations was performed on each model. Finally, an automated algorithm was used to quantitatively optimize fracture design and well placement to maximize economic performance. At each step in the process, the results were analyzed to identify the similarities and differences between the datasets and to explain why. The results show how differences in stratigraphy, well configuration, fracture design, and formation properties drive differences in parent/child phenomena. Optimal strategies to mitigate challenges depend on these site-specific conditions. Negative impacts from parent/child interactions cannot be entirely avoided. There is no strategy that can prevent the most important cause of child well underperformance – that wells are attempting to produce hydrocarbons from rock that has already been significantly depleted by parent well production. However, strategic design choices and quantitative economic optimization can significantly improve net present value and return on investment.
