Research And Design Of Test System On Downhole High Temperature Gas Sensor

With the development of mud logging technology,the importance of gas detection technology on downhole while drilling is more and more prominent.Gas sensor is an important tool of while drilling gas detection,and it is necessary to test its performance.While the traditional manual testing methods not only have the low test efficiency and great error in data acquisition,but also have the poor instantaneity and reliability.Therefore,according to the specific situation in the process of well drilling,a test system on downhole high temperature combustible gas sensor is designed and developed,based on the research of various kinds of sensors and selecting catalytic combustion type gas sensor as the sensor of downhole combustible gas detection.The software test system can complete the sensor output signal acquisition,storage and display,and can draw the sensor output characteristic curve under different temperature,different concentrations according to need,and achieve the purpose of visual display of gas sensor output.The software test system lay the foundations for the analysis and calibration of gas sensor in downhole high temperature gas detection.In the thesis,combining iteration method used in the low test temperature condition with the method of BP neural network which have better prediction effect in the high test temperature condition to compensate temperature of high temperature gas sensor considering the gas sensor output affected by temperature produces larger error,and finally realize the performance testing,calibration and correction function of gas sensor of downhole high-temperature combustible gas detection.For the problem of gas sensor signal effected by external environmental factors,such as mud flushing,drill rotating during transmission resulted to a lot of noise in the signal of the mouth of the well,the noise sources,particularly the noise signal of the drill string vibration and mud pump which influence gas sensor output signal are analyzed in the paper.According to the characteristics of these two main noise sources,and comparing the applicable scope of different noise processing methods,the method of Short-time Fourier transform and wavelet filtering are proposed respectively used to process the noise of the mud pump and drill string vibration in the gas sensor output signal.And furthermore,the noise suppression effect of processing the noise of mud pump and drill string vibration with the above two methods is verified through MATLAB simulation.Finally,gas sensor output signal is simulated and function modules of the test system are validated through the simulation software.In addition,the effectiveness and accuracy of iteration method and BP neural network which are combined with to compensate temperature is verified.The result shows that the software test system can realize the function of each module and effectively reduce the error of sensor output signal in the high temperature,and can achieve the purpose of calibrating gas sensor.