Abstract
Relevance Heat transfer and signal transmission processes in remote temperature monitoring systems for deep geothermal wells are considered. The study focuses on the dynamic characteristics of submersible sensors and the influence of 3-kilometer communication line parameters on measurement accuracy under extreme operating conditions. Aim of research The aim of the work is to develop and verify a comprehensive multiphysical model of a borehole temperature probe to estimate the adaptation time of sensors to the ambient temperature and to minimize distortion of the measuring signal during its transmission to the surface. Research methods The finite element method was used to build a full-scale 3D model in COMSOL Multiphysics. The research is based on coupling heat transfer interfaces with electrical circuit interfaces to account for resistive and capacitive parameters of the cable line. Adaptive mesh refinement up to 1 mm was applied in sensor contact zones. Scientific novelty A complex multiphysics approach to modeling downhole systems has been developed, allowing for simultaneous consideration of the thermal inertia of sensor protective sleeves and electrical losses in the communication line. For the first time, the quantitative dependence of measurement signal delay on the geometric and physical parameters of the «steel – fluid – rock» system at depths up to 3000 m in transient mode is shown. Results Dependences of the thermal stabilization time for sensors placed at various points of the bottom-hole zone were obtained. It has been established that modeling in the 3600 s interval is sufficient to capture the complete transient process and bring the system to thermal equilibrium. Signal transmission stability from deep-water nodes to the surface receiver was verified, considering the voltage drop in the copper cable. The proposed model allows for the identification of dynamic errors caused by the design of the thermometric probe. Implementing an intelligent approach to monitoring data analysis makes it possible to reduce measurement uncertainty by 15–20 %. The research results can be applied in designing high-precision control systems for geothermal resources.