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基于改进的和声搜索算法的地面核磁共振反演

Research on Inversion of Surface Nuclear Magnetic Resonance Data by Improved Harmony Search Algorithm
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摘要 地面核磁共振反演能抽象为一个求解矩阵方程An=E的问题,A为与背景电阻率空间分布有关的核函数矩阵,E为测量信号的初始振幅值,n为带求解的含水量分布值,由于A和E都存在误差,为了提高n的求解精度和稳定性,构造了正则化-总体最小二乘模型,并将该模型转化为受条件约束的非线性优化问题,设计了改进的和声搜索算法以求解该问题,在含水层数大于激发脉冲矩数的欠定方程或者病态方程的求解中,该算法仍然适用。野外实测数据反演中,导电层电阻率分布情况来自垂向电测深勘探结果,观测信号的信噪比为6.9 d B,算法的反演结果含水量值的方均根为3.12%,法国Samovar v6.2反演软件反演结果含水量值的方均根为3.65%,两种反演结果均与钻探结果接近,但本文算法略显优势。 The inversion of surface nuclear magnetic resonance (SIX/MR) data can be abstracted as the solution of the matrix equation An = E, where A is a kernel function matrix, E is a initial amplitude sequence of the meas- ured data, n is the water content distributions sequence as unknowns. The precision of A mainly depends on esti- mating of resistivity distributions. Because of the intrinsic error existing in both A and E and the high condition number of A, a regularization-total least square (R-TLS) model of the SNMR inversion is proposed to improve the stability and accuracy of the inversion result. Then it is transformed into a constrained nonlinear optimization problem, the solution is found by an improved harmony search algorithm (IHS). Even though An = E being a highly underdetermined equation, the algorithm still works effectively in the simulation. SNMR has been used in combina- tion with Vertical Electrical Sounding (VES) in the field example. The results of the field example agree well the information from an in-site borehole under poor SNR ( SNR = 6. 9 dB) at the root mean square (RMS) 3.12%, which has slightly higher precision than the result of the inversion software Samovar v6. 2 (RMS = 3.65 % ).
作者 张海如 王国富 张法全 ZHANG Hai-ru WANG Guo-fu ZHANG Fa-quan(State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, P.R. China School of Information and Communication Engineering, Guilin University of Electronic Technology, Guilin 541004, P.R. China)
出处 《科学技术与工程》 北大核心 2016年第34期18-21,27,共5页 Science Technology and Engineering
基金 中国博士后科学基金资助项目(2016H0016) 国家自然科学基金项目(11434012 61371186 61362020) 国家自然科学基金国际(地区)合作与交流项目(41561144006)资助
关键词 地面核磁共振 正则化-总体最小二乘 非线性优化 和声搜索算法 垂向电测深 surface nuclear magnetic resonance regularization-total least square non-linear optimization harmony search algorithm vertical electrical sounding
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