A Comprehensive Statistically-Based Method to Interpret Real-Time Flowing Measurements

Keita Yoshioka ; Pinan Dawkrajai ; Analis A. Romero ; Ding Zhu ; A. D. Hill ; Larry W. Lake

关键词: ACCURACY;    DIAGNOSIS;    ENERGY BALANCE;    FIBER OPTICS;    FLOW RATE;    FORECASTING;    GEOTHERMAL GRADIENTS;    MEASURING INSTRUMENTS;    STIMULATION;    TEMPERATURE MEASUREMENT;    THERMODYNAMIC PROPERTIES;    TRAJECTORIES;    WATER;   

DOI  :  10.2172/902505
RP-ID  :  None
PID  :  OSTI ID: 902505
Others  :  TRN: US200718%%73

学科分类：再生能源与代替技术

美国|英语

来源: SciTech Connect

【 摘 要 】

With the recent development of temperature measurement systems, continuous temperature profiles can be obtained with high precision. Small temperature changes can be detected by modern temperature measuring instruments such as fiber optic distributed temperature sensor (DTS) in intelligent completions and will potentially aid the diagnosis of downhole flow conditions. In vertical wells, since elevational geothermal changes make the wellbore temperature sensitive to the amount and the type of fluids produced, temperature logs can be used successfully to diagnose the downhole flow conditions. However, geothermal temperature changes along the wellbore being small for horizontal wells, interpretations of a temperature log become difficult. The primary temperature differences for each phase (oil, water, and gas) are caused by frictional effects. Therefore, in developing a thermal model for horizontal wellbore, subtle temperature changes must be accounted for. In this project, we have rigorously derived governing equations for a producing horizontal wellbore and developed a prediction model of the temperature and pressure by coupling the wellbore and reservoir equations. Also, we applied Ramey's model (1962) to the build section and used an energy balance to infer the temperature profile at the junction. The multilateral wellbore temperature model was applied to a wide range of cases at varying fluid thermal properties, absolute values of temperature and pressure, geothermal gradients, flow rates from each lateral, and the trajectories of each build section. With the prediction models developed, we present inversion studies of synthetic and field examples. These results are essential to identify water or gas entry, to guide flow control devices in intelligent completions, and to decide if reservoir stimulation is needed in particular horizontal sections. This study will complete and validate these inversion studies.