The Theoty And Application Study On Nonlinear Optimization Methods For Seismic Inversion

Seismic inversion plays a key role in geophysical prospecting. As most of geophysical inversions appear as objective function optimization with multi-extreme, which makes the conventional inversion methods based on linear or quasi-linear theory cause the solution to be optimized locally and unreliable. In this paper, the author presents a series of new methods for seismic inversion based on nonlinear optimization theory by making use of some latest research results of cross-subjects in leading edge, which are used to resolve the difficulties in petroleum exploration and development. This study has considerable academic value as well as wide prospects. In this paper, the main research works and the achievement obtained include the following contents: ?presents a hybrid optimization method combining genetic algorithm with simulated annealing by deeply analyzing and studying their advantage and disadvantage individually. The hybrid algorithm improved the searching performance in nonlinear global optimization, calculation efficiency and inversion accuracy in geophysical parameters inversion. ?To improve the low performance of existing network learning such as inflexibility of Topological structure designed ,simple regulation for weights obtained , being easy to be lost in local optimal solution and prediction with low performance, this paper presents a new way to train the neural network with genetic evolutionary strategy so as to make the linking weight, threshold , optimal structure adaptively evolve. ?By deeply study residual statics correction thought to be difficult in geophysics inversion, this paper presents a new approach to automatic residual statics using hybrid optimization, which brought satisfactory result when applied to real data of two areas ?To overcome the problem of existing reservoir prediction using seismic data, we developed the technology for nonlinear inversion and prediction of reservoir, which is successfully used in 3D seismic inversion and reservoir prediction for Darqi structure in Baiyunchagan depression and gives an accurate approach of submitting controlled reserves and selecting favorable targets for this area .?The first to present a new method for predicting formation pressure. ahead of bit. The method adopts the basic thought of lateral prediction of reservoir, combine logging and seismic data, builds the nonlinear mapping model of neural network between seismic attributes and sonic logging and then extrapolates sonic curves then predicts formation pressure ahead of bit. Great contribution has been done ~2 with this technique to successful drilling with safe warrant and low drilling cost for high temperature and pressure well DF 1-1-11 in Yingqiong basin.