【摘要】 翁爱华 ,李舟波 ,王雪秋 ,陆敬安 ,莫修文 .基于回归 M-估计的核磁测井数据反演 .石油地球物理勘探 ,2 0 0 2 ,37(3) :2 5 8～ 2 6 1　　通过对核磁共振测井数据分析 ,发现数据误差可能不服从正态 Gauss分布 ,为此采用回归 M-估计 (RME)进行弛豫谱反演 ,克服常规正则化反演弛豫谱受非 Gauss分布数据误差的影响。回归 M-估计通过对较大的离群数据误差赋较小权 ,对较小的数据误差赋较大权 ,从而压制较大数据误差对总误差的影响 ,并通过迭代过程进一步克服非 Gauss分布数据误差对弛豫谱反演的影响。在核磁测井数据反演中 ,首先采用回归 M-估计求取经过初步修正的误差数据集 ,接着利用正则化方法对修正后的误差数据进行弛豫谱反演计算。实际观测数据计算表明 ,回归 M-估计和常规正则化反演方法结合 ,能提高弛豫谱估计精度和孔隙率计算效果。更多还原

【Abstract】 After analysis of real nuclear magnetic resonance logging data,it is found that some data error might not follow a normal Gauss distribution.Therefore,a regression M estimation (RME) was applied to relaxation spectra inversion,overcoming the effect of non Gaussian distribution data error on the relaxation spectra resulted from ordinary regularization inversion method.The regression M estimation suppressed the effect of large data errors on total errors by taking small right in large off group data errors and large right in small data errors and this influence can be further overcome by an iterative regression process.In the inversion of nuclear magnetic resonance logging data,first step is using RME to calculate error data set being preliminary modified,then using ordinary regularization method for relaxation spectra inversion in modified error data.The results of real data calculation show that combining RME with ordinary regularization inversion can improve the precision of relaxation spectra and the effect of calculated porosity.更多还原