Research On Optimization Method Of NMR Data Acquisition Based On Real-time Feedback Strategy

Low-field nuclear magnetic resonance(NMR)technology has become an important research tool in engineering scenarios such as geophysical logging,multiphase fluid analysis,and laboratory measurement of porous media materials.In the past few decades,the continuously upgraded equipment,new observation modes,and advances in data interpretation methods have made significant progress in wellbore NMR technology.Standard T2 logging,dual TW logging,and dual TE logging can accurately evaluate reservoir porosity and identify fluids.However,these methods are static in nature and do not have the ability to adjust in real time during logging.Due to the unknown and wide distribution of relaxation properties of the samples to be measured,the traditional measurement mode characterized by preset parameters before measurement can no longer adapt to the new measurement requirements.This paper aims to break through the traditional measurement mode of NMR and propose a new measurement method that combines pulse excitation and sample characteristics in real-time measurement to achieve adaptive pulse sequence parameters,solving problems such as energy consumption,data redundancy,and low resolution caused by improper parameter settings.In terms of parameter optimization methods,focusing on the challenge of real-time adjustment of pulse sequence parameters for application scenarios mainly using wireline NMR logging tools and logging while drilling(LWD)NMR tools,analyzing the mechanism of sequence parameters on signal-to-noise ratio(SNR),a closed-loop control strategy is proposed to monitor changes in formation characteristics and determine sequence parameters based on real-time echo data during measurement.The strategy is built on the foundation of effectively estimating the relaxation characteristics of the formation to be measured,and uses various measures to shorten the data acquisition and processing time to improve the timeliness of parameter adjustment in mobile measurement state.In the software system,a data acquisition platform based on Appdesigner is developed to establish a real-time echo trains data and the optimal sequence parameter relationship,and real-time data interaction with the spectrometer is achieved through serial communication.Aiming at the time-consuming problem of relaxation time calculation by traditional inversion algorithms,a relaxation time estimation method based on Monte Carlo mathematical statistical method is proposed,which does not require complete echo trains and can accurately estimate relaxation time by using limited echo data uploaded by the spectrometer.Analyzing the effect of adaptive parameter adjustment on layers simulation data generated by building layer models on the software platform,and the simulation result shows that,using the data generated by the formation model on the software platform to analyze the effect of parameter adjustment.The simulation results show that,compared with the static parameter measurement method,the vertical resolution can be improved by about 1.7 times,the SNR can be increased by about 13 times,and the efficiency of observation sequence can be improved by about 116 times,and the power consumption can be reduced by 1/3.In the aspect of hardware system,dynamic parameter adjustment and SNR enhancement are two key technologies used to implement the adaptive method.The adaptive main control circuit and high-power transmission circuit are designed to realize dynamic adjustment of acquisition and excitation parameters.The simulation and relative measurement verify the realization of this function.The SNR enhancement technology includes optimization of RF pulses,digital filtering method,and acceleration of energy discharge circuit design.By designing an guassian shaped pulse with wide bandwidth,the amplitude of the echo signal can be increased to 1.2 times or more of that of the original signal,thus improving the SNR.From the perspective of reducing ringing noise,optimization of pulse sequence is used to suppress ringing caused by 90° and 180° pulses,and a new Q switch circuit is implemented to accelerate the leakage of residual energy from the antenna.When the Q value of the antenna is reduced to 1/5 of that during transmission,the recovery time of the antenna is reduced from 280μs during natural leakage to about 18μs,thus reducing the interference of antenna ringing noise to the echo signal.The pulse sequence parameter optimization method proposed for logging is also suitable for laboratory sample measurement,and based on this,a real-time parameter optimization method using variable TE pulse sequence is proposed.Continuous measurement experiments on various samples have shown that the adaptive method can reduce human intervention and improve the measurement efficiency and automation level of the instrument.