Abstract：Seismic data inversion is a typical nonlinear inverse problem,and its object functions are multiextremal functions. Therefore,ordinary iterative optimization method are often restricted by local convergence.Homotopic neural optimization theory and its algorithm described in this paper can make nonlinear multiextremal object functions converge fast to global extremum,so it is an effective inversion method. This inversion method is combined with both adjacent trace crosscorrelation and stratum data restriction to jointly derive high-resolution lithology parameters from logging data under restriction of seismic data. Theoretical and real resalts prove this method feasible.
刘舒考, 刘雯林, 郑晓东, 李勇根. 同伦神经优化理论及其在地震反演中的应用[J]. 石油地球物理勘探, 1998, 33(6): 758-768.
Liu Shukao, Liu Wenlin, Zheng Xiaodong, Li Yonggen. Homotopic neural optimization theory and its application to seismic inversion. OGP, 1998, 33(6): 758-768.
