Study On Weak Signal Detection Issue In Multi-Frequency NMR Logging System

Multi-frequency NMR logging method is one of the most advanced logging techniques nowadays. In following decades, it would still be wide used in oil exploration. To break through the technique blockade, it is of great importance to develop multi-frequency NMR logging instrument. In the NMR logging system development, the weak signal’s capture and process is very crucial. In the dissertation, the echo’s extraction and high efficient acquisition and noise filtering method in the echo string construction were discussed deeply. The main content of this paper was as below.(1) The design and implementation of weak signal amplifier which is required to work in high temperature environment is a key process in multi-frequency logging system. Because echo signal has a wide bandwidth, traditional point noise match method could not meet design target. Due to this, a wide band noise match method was proposed and a high gain high SNR amplifier had been designed. Logging experiments showed, it not only met the design specification but also provide a good foundation for the follow-up signal process.(2) Noise filtering maximum and signal loss minimum are the two aspects of a paradox. The tradeoff between the two issues is common problem to choose a filtering cutoff frequency. Based on the signal loss and residual noise power sum minimum principle, the choice of best filtering cutoff frequency was analyzed to get generalized SNR maximum. The quantitative standard to choose wavelet decomposition scale was established according to the echo’s characteristics. The result had been applied in inversion algorithm and get good performance.(3) The measurement deviation caused by the difference between calibration and logging temperature was analyzed. Based on the relation between environment temperature and transition energy, the temperature error mechanism was described. In addition, the model of temperature error was built through Bloch equation based on the twin-peak porosity model. Furthermore, a approximate temperature error suppression method was proposed according to the characteristic and mechanism of temperature deviation.(4) To improve the accuracy in ultra-deep NMR logging, short echo interval and long acquisition time should be adopted. Because of this, the signal process time decreased. To meet the real time requirement of T2 spectra measurement, a detection method based on compressed sensing was proposed to design a capture system dedicated for NMR echo signal. Experiments showed that the detection system gained good performance in NMR logging system which requires high quality result and has rigid demand in real time and low cost.