In unconventional hydrocarbon resources, the estimation of the expected ultimate recovery for individual wells and the appropriate spacing for infill drilling near existing wells both have strong economic implications. A field test called microseismic depletion delineation has previously been proposed as a method to probe the reservoir directly to determine the extent of the depleted region near horizontal wells that have been produced for a significant period of time. In this work, we performed a numerical simulation of a microseismic depletion delineation field test in order to further understand the physical mechanisms that underpin the method. The modeling framework developed herein can be used to help design field tests and interpret field observations. We observed that application of a model that coupled fluid flow, fracture mechanics, poroelasticity, and geologic structure was able to produce the physical behavior necessary to interpret observations from microseismic depletion delineation field tests.
The successful exploitation of unconventional resources depends on the ability to develop strategic engineering designs using economic considerations as the primary drivers. In shale oil plays, like the Bakken for instance, suitable wellpad geometries and well trajectories are first determined and then repeated many times in an efficient pattern in order to reduce drilling costs. Similarly, hydraulic fracture treatments are commonly performed in repeatable patterns across many wells. This methodology is attractive from an economic standpoint, but given that heterogeneity exists in all reservoirs and that operational difficulties can arise, the approach may not always result in the optimal recovery for a given well. Evidence from field data has indicated that productivity of individual wells, and even individual completion stages, can be highly variable [1, 2]. It is useful to develop tests that can be applied in the field in order to assess the recovery efficiency of wells and individual completion stages within each well. This information can be helpful from a reservoir management perspective, for example, in order to estimate ultimate recovery or to determine appropriate spacing for infill drilling in a given asset.