Distributed temperature sensing (DTS) is an enabling technology for fracture diagnosis and multiphase flow measurement in unconventional areas. DTS data analysis includes the warm-back stage and production stage analysis. The warm-back stage analysis can provide the slurry flow and proppant allocation. The production stage analysis can be applied to flow profiling and fracture characterization. The objective of our DTS data analysis approach is to provide an integrated quantitative diagnosis of effectiveness of staged fracturing, and hydraulic and natural fractures with the full-physics model, which will benefit the fracturing operation design and decision-making process in the unconventional reservoir. In this work, we developed a comprehensive numerical forward model for DTS data analysis. Our model includes reservoir and wellbore models. Also, the flow and thermal models are fully coupled. A thermal embedded discrete fracture model (Thermal EDFM) is developed to handle the thermal modeling of complex fracture networks. The DTS analysis with our model provides a high-resolution solution since the fracture diagnosis and flow profiling are performed for each fracture. With this analysis, we obtain a deeper understanding of the effectiveness of the field hydraulic fracturing operation. Although numerous simulators are developed for DTS data analysis, relatively few existing models can handle the full-physics such as complex fracture geometry and multiphase flow. Our inverse model provides an improved DTS data match result. Our model is more rigorous than the prior models to simulate and match the field DTS data.

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