【摘要】 核磁共振测井T2谱反演结果直接影响如孔隙度、渗透率、孔径分布等储层参数的计算和流体识别的准确性。给出了T2谱反演的线性方程组;利用矩阵奇异值分解法(SVD)求该方程组的解,通过对系数矩阵加阻尼项使得该方法数值解稳定,在布点数为11～128、信噪比大于25的情况下拟合精度较高,适用于高信噪比回波数据的反演,并且信噪比越高,反演的T2谱与构造谱的符合率越高。处理了大庆油田古89-47井1块岩心实验室NMR数据,结果表明,改进的SVD法可以快速、有效地反演核磁共振测井T2谱,奇异截止值对解谱效果影响小。利用迭代技术进行解的非负性约束,反演的T2谱和构造谱分布趋势一致,谱线光滑连续;大组分反演效果好,但小组分反演结果与构造谱相差较大,分辨率低;信噪比越高,反演所得的T2谱与构造谱的符合率越高。对无噪声理论回波数据、不同信噪比理论回波数据以及实验室岩心核磁共振测井实测资料进行处理并且与构造谱及实验室反演结果对比表明,该方法可以有效地反演核磁共振测井T2谱。更多还原

【Abstract】 The inversion of nuclear magnetic resonance(NMR)directly impacts accuracy of reservoir parameters(such as porosity,permeability,aperture distribution and so on)calculation and fluid identification.Given is system of linear equations of T2inversion and how to solve the equations using singular value decomposition.Adding damping factor to coefficient matrix makes numerical solution of the algorism stable.When T2values are 11to 128and SNRis higher than 25,the fitting accuracy is much better.The higher the SNR,the better the coincident rate between the inverted T2spectrum and structured spectrum.One core NMR data in lab from Gu-89-47well have been processed with above method,the result of which shows that the improved SVD method may quickly and effectively invert true NMR T2spectrum,and the singular cut-values have a little effect on the decomposed spectrum.Since the iteration technique is used for non-negative constraints of the solutions,distribution trend between the inverted T2spectrum and structured spectrum is very coincident,and spectral lines are more smooth and continuous.But,when the SNRis lower than 25,the inverted T2spectrum is not so coincident with the structured spectrum,its resolution is very poor.Processed are echo data of theoretical noise-free and different signal-to-noise ratios,as well as a laboratory measured core NMR data,which is compared with spectrum structure and inverted result of experimental laboratory.The processed and comparedresults show that this method can efficiently invert NMR T2spectrum to meet the needs of production,scientific research on NMR data processing.更多还原