Frac hits relates to the problem of newly created hydraulic fractures interacting with either primary and/or secondary fractures from offset wells. This fracture-driven interaction (FDI) represents a major concern for shale oil and gas producers given that infill wells experiencing frac hits typically underperform parent wells landed in the same zone. In addition, the sudden pressure communication established through frac hits between multi-fractured horizontal wells (MFHW) can result in damage to parent wells.
In this work, we introduce an analytical model to detect frac hits and assess the fraction of primary fractures connected between the infill and offset well. We assume that frac hits are due to overlapping primary fractures. Frac hits are modeled as a valve between MFHWs that allows certain degree of pressure communication. While the aperture of this valve is controlled by the number of frac hits, the leakage rate is governed by the bottomhole pressure (BHP) differential between wells.
The analytical solution to the fluid-flow model is derived in Laplace domain and is inverted numerically. We found that BHPs are coupled via the degree of interference coefficient δw, defined as the ratio of frac hits to the total number of primary fractures of the infill well. We utilize δw to history-match the analytical model with numerical data. As a result, history-matched δw delivers an estimate of the actual fraction of frac hits ((Equation)).
We study several sensitivity analyses to examine the impact of variation in MFHW properties on the accuracy of the estimation of (Equation) via δw. In general, our model gives an accurate estimation (Equation) for most of the cases evaluated in this work; however, we see that the analytical model may introduce significant error in the estimation of frac hits when SRV and matrix permeability are the same order magnitude. Type-curves for rate-normalized data as well as (Equation) vs δw tables are discussed herein. The computational script used for the analytical calculations in this work proved to be efficient and straightforward to implement.
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