核磁共振弛豫信号的多指数反演及应用

Application of Multi-exponential Inversion of NMR Relaxation Signal

利用核磁共振正演模拟信号对比分析了奇异值分解(SVD)算法和迭代Tikhonov正则化方法两种反演算法在不同布点数、不同布点方式、不同信噪比下核磁共振弛豫谱的反演结果。反演结果表明,SVD算法适合于信噪比较高(SNR>50)的数据反演;迭代Tikhonov正则化方法适应于信噪比较低的数据反演。利用两种算法对核磁共振测井回波串数据进行反演,取得了良好的应用效果。

The NMR numerical simulation signals were used to compare and analyze NMR relaxation spectral inversion results by singular value decomposition(SVD)and iterative Tikhonov regularization method under the conditions of different numbers of pre-assigned relaxation bins,different modes of pre-assigned relaxation bins and different SNR.The results of the study indicate that SVD algorithm is suitable for the high signal-noise ratio(SNR> 50);iterative Tikhonov regularization method is suitable for the lower signal-noise ratio of data inversion.Nuclear magnetic resonance logging data are inversed by the two algorithms with good application effect.