Multiscale Quantum Genetic Algorithm and Its Application to Magnetotelluric Data Inversion
A new inversion algorithm of Multiscale Quantum Genetic Algorithm (MQGA) has been developed for nonlinear inversion of Magnetotelluric (MT) data. MQGA employs qubits as presentations of chromosomes and uses multiscale strategy to accelerate the convergence rate. The quantum rotation gate is used to update populations in MQGA. According to its application to the synthetic Magnetotelluric data, MQGA has the advantages of faster convergence rate and higher accuracy than that of the traditional genetic algorithm. The inversion results of field MT data near a drill agree with the geological structure and seismic profile, which implies that the MQGA is effective and efficient for the nonlinear inversion of MT data and can be applied to other geophysical global optimization problems.
Multiscale Quantum Genetic Algorithm Magnetotelluric Nonlinear Inversion Global Optimization
Hongming Luo Jiaying Wang Xueming Shi Peimin Zhu
key laboratory of exploration technologies for oil and gas resources (Yangtze University), Ministry the Institute of Geophysics and Geomatics, China University of Geosciences,Wuhan 430074 China the Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074 China
国际会议
武汉
英文
2007-09-21（万方平台首次上网日期，不代表论文的发表时间）