Although the wellbore is in a nonisothermal environment, heat transfer between the fluid in the wellbore and the formation is often ignored and temperature is usually assumed constant in data interpretation, which will lead to misunderstanding of the pressure profile. In this work, wavelet transform and a nonlinear-regression-analysis method were used to study the relationships between downhole temperature, pressure, and flow rate. A nonisothermal wellbore model was established that is capable of predicting temperature, pressure, flow rate, and liquid-fraction profiles under multirate and multiphase production scenarios.
Introduction
In order to monitor the downhole production and injection conditions, as well as make decisions for well-performance optimization, the dynamic temperature data acquired from permanent downhole gauges (PDGs) and distributed-temperature sensors (DTSs) are often interpreted widely.
In this paper, first, the relationships among bottomhole-pressure (BHP), -temperature (BHT), and flow-rate data were analyzed briefly by use of wavelet transform and nonlinear regression. Next, a nonisothermal wellbore model with complex structure was derived theoretically step by step.
