Implementation Of Broadband Nuclear Magnetic Resonance Measurement And Control Software System

Broadband untuned NMR detection methods for complex oil and gas reservoirs have attracted the attention of scholars at home and abroad.Research on broadband untuned technology has achieved some results,but there is no practical and feasible solution,and it is not suitable for downhole detection.It is still a hotspot in the field of nuclear magnetic resonance logging.In order to realize the rapid and accurate multi-dimensional NMR detection of complex oil and gas reservoirs,the research on the mechanism of wide-band tuneless high-power transmission and multi-frequency weak echo signal with high SNR reception and multi-frequency pulse train measurement has become an urgent theoretical problem in the international NMR logging field.In this paper,the research on the broadband NMR measurement and control software system is carried out.Based on the analysis of the basic principles of NMR and the characteristics of the echo signal,the design and development of the overall scheme of the measurement and control system is completed.In addition,through the inverse calculation of the echo train signal measured by the detector,the relationship between the analytical relaxation time and the porosity structure is obtained,and the permeability,saturation and fluid type in the porous medium can be obtained.However,the signal-to-noise ratio of the echo train signal directly affects the accuracy of the relaxation time of the echo signal,so the signal-to-noise ratio of the echo signal needs to be improved by various means.Therefore,this paper proposes a nuclear magnetic resonance signal denoising method based on H?CEEMD improved threshold.Fractional Gaussian noise(f Gn)is used to model the NMR signal noise,and various noises can be effectively removed by estimating the Hurst parameter of f Gn.In this paper,the proposed method is compared with the wavelet threshold noise reduction method and EMD threshold noise reduction method widely used in logging signal noise reduction,and the measured data is processed.The superiority of the proposed method is verified from the two aspects of signal-to-noise ratio and T2 spectrum inversion results.