| With the rapid growth of China’s economy,people’s demand for energy has significantly increased,leading to an annual increase in China’s oil consumption.Temperature logging,as a simple and efficient logging tool,is usually used to divide underground temperature profiles.If oil or gas is produced in the production well of an oil well,the temperature at the current production location will suddenly rise;If water or other liquids are injected into a water injection well,the temperature at the current injection location will suddenly drop.Therefore,if precise and rapid delineation of the underground profile is not possible,it may not only lead to energy waste and environmental pollution,but also damage the health of workers in the oil field area and major explosion accidents.In actual logging engineering,different sizes of temperature sensors and logging speeds are often chosen,which leads to inconsistency between the temperature reflected by the instrument and the actual temperature when the logging speed does not match the size of the sensor itself.Therefore,the collaborative optimization of parameters between logging speed and sensor size in well temperature measurement systems is of great research significance.This article takes existing platinum resistance temperature sensors as the research object.In response to the problem of dynamic errors in the temperature measurement process of platinum thermistors,the oil bath method is adopted to obtain their temperature sensing time constants at different temperatures,diameters,and lengths,and their mathematical models are obtained.The influence of their length and diameter on the temperature sensing time constant is analyzed.In response to the problem that velocity measurement often affects the real-time performance of sensor temperature measurement in well temperature measurement,a correlation function is established to obtain the relationship expression between the temperature,temperature sensing time constant,and logging velocity parameters.A simulation model of the entire temperature measurement system is established based on the Matlab/Simulink platform.The temperature measurement is conducted on the same layer of oil and water wells with abnormal temperature inflection points as the experimental site,and the experimental results are substituted into the simulation model,A collaborative optimization study was conducted on the relationship between logging velocity and sensor size in a well temperature measurement system using a combination of simulation and on-site experiments.The experimental and simulation results show that the diameter and length of the sensor have an impact on its temperature sensing time constant,and its length has a greater impact on the temperature sensing time constant.In addition,the temperature sensing time constant is basically around 3 to 4.5 s;The temperature curves corresponding to different logging speeds also vary,and at different speeds,the temperature difference at the same location shows a certain linear relationship with the change of speed,with a temperature difference generally between 0.01 and 0.06 ℃;During the down testing process,the faster the speed,the later the temperature inflection point position is,and the simulated data has decreased by 0.03-0.1m compared to before.The simulated data is also closer to the temperature inflection point position data at 300m/h.To sum up,different sensor sizes will lead to different temperature sensing time constants,and different speeds will lead to different temperatures at the same location.Therefore,this paper effectively solves the problem that different speeds and sensors in the temperature measurement system lead to different measured temperatures and actual temperatures,which can further improve the detection accuracy and efficiency of temperature inflection points under different temperature profiles,Multiple parameters of the underground temperature profile measurement system have been optimized through mutual collaboration. |
PDF Full Text Request