Prestack stochastic inversion based on the quantum annealing Metropolis-Hastings algorithm
Zhang Guangzhi1,2, Zhao Chen1, Tu Qicui3, Liu Jiang3, Zhang Jiajia1,2, Pei Zhonglin1
1. China University of Petroleum(East China), Qingdao, Shandong 266580, China; 2. Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266071, China; 3. Shanghai Branch of CNOOC, Ltd., Shanghai 200030, China
Abstract：The conventional MH(Metropolis-Hastings) algorithm is a common stochastic inversion method.It can get a lot of samples from the posterior distribution to obtain more reliable parameter estimation and uncertainty information of inversion results.But the MH algorithm cannot fully search on it for more complex parameter space.For this purpose we propose a prestack stochastic inversion based on the quantum annealing MH algorithm to improve the computational efficiency and stability of the inversion.Tests on synthetic and real data show that the proposed method has higher convergence efficiency than the conventional MH algorithm.
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