The interpretation of microseismic data was initially focused on hydraulic fracture length and height, providing an important measurement to calibrate planar fracture propagation models. However, microseismic data in the Barnett shale exhibited significantly more complex patterns compared to typical tight-gas sands. The concept of stimulated reservoir volume (SRV) was developed to provide some quantitative measure of stimulation effectiveness in the Barnett shale based on the size of the microseismic "cloud." SRV is now ubiquitous when discussing well performance and stimulation effectiveness in unconventional reservoirs. However, SRV and similar techniques provide little insight into two critical parameters: hydraulic fracture area and conductivity. Each of these can vary significantly based on geologic conditions and fracture treatment design. Hydraulic fracture area and fracture conductivity, combined with reservoir permeability, stress regime, and rock properties, control well performance, not SRV.

The concept of SRV has spawned numerous reservoir engineering models to approximate the production mechanisms associated with complex hydraulic fractures and to facilitate production modeling and well performance evaluations (e.g., rate transient analysis). However, these reservoir engineering models are often divorced from the fracture mechanics that created the fracture network, a significant limitation when evaluating completion effectiveness. Additionally, the interpretation of the microseismic data and the calculation of SRV are poorly linked to the actual hydraulic fracture geometry and distribution of fracture conductivity.

This paper presents detailed numerical reservoir simulations coupled with hydraulic fracture modeling that illustrates the limitations and potential misapplications of the SRV concept. This work shows that simplifying assumptions in many SRV-based rate transient models may lead to estimates of hydraulic fracture length and reservoir permeability that are not well suited for completion optimization. Two case histories are presented that illustrate the limitations of SRV-based well performance evaluations. The paper concludes that using microseismic images to estimate a SRV may not be sufficient for completion evaluation and optimization. However, the simple calculation of microseismic volume (MV) can provide significant insights to guide fracture and reservoir modeling endeavors.

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