The uses of distributed temperature survey (DTS) data [electronic resource]
Keywords: Energy Resources Engineering

Temperature change plays an important role in many downhole processes, and temperature measurements have long been used to monitor the performance of producing wells, evaluate water-injection profiles and diagnose the effectiveness of fracture jobs, etc. However, for many years, the utilization of downhole temperature measurement was largely over-shadowed by other measurements obtained through sophisticated suites of logging tools. However, the development of fiber-optic technology has helped a resurgence of interest in temperature measurement. One characteristic of fiber-optic temperature measurement is that it is capable of measuring multiple points simultaneously. The fiber-optic tool used to measure temperature is called a Distributed Temperate Survey (DTS), which measures temperature along the whole interval covered by the fiber. In our study, we explored approaches of how to interpret DTS data. The significant contributions of this work include: 1. Building a wellbore/reservoir coupled thermal model The need to interpret wellbore temperature profiles measured by Distributed Temperature Sensors (DTS) requires a correspondingly sophisticated type of well model. To be specific, this model should be capable of predicting pressure and temperature distributions under a nonisothermal, multicomponent and multiphase production scenario. In our model, wellbore pressure and temperature were solved separately and then coupled by iteration. Accuracy was assured by the following three ways: a. Using the drift flux model to predict multiphase flow pressure; b. Fluid PVT properties were obtained by solving Equations of State, which is more accurate than the values obtained by averaging or mixing rules; c. Using numerical methods to solve the heat transfer between wellbore and formation, avoiding the assumption of an invariant relaxation length. This model was verified by comparing with several previously published models. 2. Estimating flowrate profile from temperature profile measurement Measuring flowrate profile can be a challenging job for traditional single-point flowrate measurement tools, and it becomes very unreliable especially for multi- phase flow and complex well geometries. However, temperature profile provides an alternative approach for measuring flowrate profiles. As the temperature in the wellbore is influenced by the properties and flowrate of the inflows from different entry points, measured temperature can be used to estimate flowrate. Therefore, the DTS data are very valuable for estimating flowrate profiles. In our study, we used two different inverse methods separately. Although the philosophy and performance of these two methods are different, both succeed in estimating flowrate profile from the temperature profile. The multiphase case was also considered, in which we found that it requires more input information than just temperature data to achieve a good estimate of flowrate profile. 3. Evaluating formation properties Temperature is also a function of formation properties, and thus it can be used to evaluate the formation. We found that temperature data are more sensitive to the properties in the near-well formation than pressure data. This finding is confirmed by our study on several different cases of single-layer reservoirs. Furthermore, multilayer and horizontal wells, both of which have multiple entry points in the well, were also studied. Finally, a successful analysis of a real case was helpful to verify our findings.