Evaluation of Fracture Stimulation Design Based on Downhole Temperature Interpretation

Abstract

Hydraulic fracturing technique has significantly evolved with larger fluid volume, more fracturing stages, and tighter perforation cluster spacing to efficiently stimulate unconventional reservoirs. Several field observations clarified that the recent design creates complex fracture networks or swarm of fractures. The evaluation and optimization of fracturing design have become more critical for maximizing a fracture stimulation performance. Downhole temperature measurements are commonly used to diagnose downhole flow conditions. Although the technology allows us to qualitatively confirm the fluid flow profile and other issues occurring downhole during fracturing such as leakage through plugs, for optimizing the fracturing design, we also need to quantitatively interpret the flow profile. In this study, a comprehensive temperature interpretation method is presented. Using a wellbore/reservoir coupled thermal simulator as a forward model, the flow profiles during fracturing and production are quantitatively estimated by performing a temperature history match. An efficient inversion can be achieved by adopting the Levenberg-Marquardt algorithm or a type curve approach based on the Péclet number theory. In the context of heat transfer, the Péclet number represents a relationship between a temperature change and fluid flow rate at the location where temperature is measured. This concept is applied to estimate the flow rate at each cluster. Also, completion configuration effects on the temperature interpretation is considered. Although the flow profile is estimated based on temperature anomalies, the temperature behavior is determined by not only the fluid flow but also variations in heat transfer induced by completion hardware along a casing string such as clamps and blast protectors. The completion effects are mathematically incorporated into the thermal model. The developed interpretation method is applied for two different field cases. The estimated flow profiles are compared with several completion parameters such as injection rate, injected fluid loading, proppant loading and so on. The statistical analysis illustrates that high injection rate would be one of the primary design parameters to maximize the fracture stimulation performance in those field cases. As demonstrated in this study, the evaluation of fracture stimulation design based on the downhole temperature interpretation would be an essential approach to optimize it.