Fiber optic measurements including Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) have been established as common tools to monitor the downhole condition during hydraulic fracturing treatment as well as during production. Several authors presented a methodology of quantitative interpretation for DAS and DTS data to estimate injected/produced fluid volume distribution among perforation clusters. The quantitative interpretation allows us to not only diagnose the stimulation efficiency but also optimize the completion design for subsequent fracturing jobs. This study investigates how completion parameters are correlated with fracturing stimulation performance based on the field application of DAS and DTS interpretation methodology. The field data from MIP-3H provided by the Marcellus Shale Energy and Environmental Laboratory is analyzed in this work.

As previously presented, a DAS/DTS integrated interpretation method estimates fracture half-length distribution for each stage. In this approach, fractures are assumed to be created in a swarm pattern from each perforation cluster. We do not assign fractures only at the perforation cluster locations but assume that multiple fractures are initiated along a stage interval with much smaller spacing than cluster spacing. This fracture swarm model is supported by several field observations. Once the DAS interpretation estimates the injected fluid volume for each perforation cluster, by considering the fluid volume distribution as an input parameter for the DTS interpretation, the temperature inversion provides the half-length of each fracture. This interpretation approach allows us to estimate uniformity of the fracture half-length distribution. To statistically describe the fracture uniformity, a uniformity index is defined. The estimated uniformity index is compared with inflow rate for each stage to investigate how the uniformity of fracture distribution contributes to well performance. The inflow profile is estimated by interpreting the DTS data during production. The comparison shows that the stages with uniform fracture half-length distribution are more productive. This result implies that the stages more uniformly stimulated become more productive.

By observing the relationship between the uniformity index and several completion parameters such as injection rate, total volume of injected fluid, proppant concentration and so on, we can investigate what parameter is more influential to the fracture stimulation efficiency. The statistical analysis illustrates that the uniformity of the fracture half-length distribution and high productivity are correlated with high injection rate. Based on this study, the injection rate would be one of the primary design parameters to maximize the fracturing stimulation performance in this field case. As demonstrated in this study, the evaluation of fracturing stimulation design based on the interpretation of DAS and DTS data would be an essential approach to optimize it.

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