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nonlinear amplitude inversion using a hybrid quantum genetic algorithm and the exact zoeppritz equation

Petroleum Science 2022年第3期19卷 1048-1064页

作者： Ji-Wei Cheng Feng Zhang Xiang-Yang Li College of Geophysics State Key Laboratory of Petroleum Resources and ProspectingChina University of Petroleum(Beijing)Beijing102249China British Geological Survey EdinburghUK

The amplitude versus offset/angle(AVO/AVA)inversion which recovers elastic properties of subsurface media is an essential tool in oil and gas exploration.In general,the exact Zoeppritz equation has a relatively high accuracy in modelling the reflection coefficients.However,amplitude inversion based on it is highly nonlinear,thus,requires Nonlinear inversion techniques like the genetic algorithm(GA)which has been widely applied in seismology.The quantum genetic algorithm(QGA)is a variant of the GA that enjoys the advantages of quantum computing,such as qubits and superposition of states.It,however,suffers from limitations in the areas of convergence rate and escaping local minima.To address these shortcomings,in this study,we propose a hybrid quantum genetic algorithm(HQGA)that combines a self-adaptive rotating strategy,and operations of quantum mutation and catastrophe.While the selfadaptive rotating strategy improves the flexibility and efficiency of a quantum rotating gate,the operations of quantum mutation and catastrophe enhance the local and global search abilities,respectively.Using the exact Zoeppritz equation,the HQGA was applied to both synthetic and field seismic data inversion and the results were compared to those of the GA and QGA.A number of the synthetic tests show that the HQGA requires fewer searches to converge to the global solution and the inversion results have generally higher accuracy.The application to field data reveals a good agreement between the inverted parameters and real logs.

关键词： Nonlinear inversion AVO/AVA inversion Hybrid quantum genetic algorithm(HQGA)

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An improved differential evolution algorithm for Nonlinear inversion of earthquake dislocation

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Geodesy and Geodynamics 2014年第4期5卷 49-56页

作者： Zhou Yu Nie Zhaosheng Jia zhige Institute of Seismology China Earthquake Administration Key Laboratory of Earthquake Geodesy China Earthquake Administration China University of Geosciences

Geophysical inversion for earthquake dislocation source model from the observed crustal deformation field is a nonlinear multimodal problem. Although a lot of nonlinear algorithms have been developed, scientists are pursuing a rapid and accurate method to achieve more stable inversion solutions. Differential evolution, an improved Genetic Evolution algorithm, is implemented to solve the problem. The algorithm is fulfilled by Python 2.7 and tested for the 2004 Mw6.0 Parkfield earthquake, the 2009 Mw6.3 L＇ aquila earthquake, and a virtual MwT.3 earthquake. The inversion results demonstrate that the differential evolution algorithm is not only simple and straightforward to implement, but also robust with impressive precision even if all the 9 model parameters are loosely constrained.

关键词： earthquake dislocation Nonlinear inversion differential evolution coseismic deformation GPS

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Nonlinear inversion for Complex Resistivity Method Based on QPSO-BP Algorithm

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Open Journal of Geology 2021年第10期11卷 494-508页

作者： Weixin Zhang Jinsuo Liu Le Yu Biao Jin School of Resources and Geosciences China University of Mining and Technology Xuzhou China Anhui Construction Engineering Testing and Research Institute Hefei China

The significant advantage of the complex resistivity method is to reflect the abnormal body through multi-parameters, but its inversion parameters are more than the resistivity tomography method. Therefore, how to effectively invert these spectral parameters has become the focused area of the complex resistivity inversion. An optimized BP neural network (BPNN) approach based on Quantum Particle Swarm Optimization (QPSO) algorithm was presented, which was able to improve global search ability for complex resistivity multi-parameter Nonlinear inversion. In the proposed method, the nonlinear weight adjustment strategy and mutation operator were used to enhance the optimization ability of QPSO algorithm. Implementation of proposed QPSO-BPNN was given, the network had 56 hidden neurons in two hidden layers (the first hidden layer has 46 neurons and the second hidden layer has 10 neurons) and it was trained on 48 datasets and tested on another 5 synthetic datasets. The training and test results show that BP neural network optimized by the QPSO algorithm performs better than the BP neural network without initial optimization on the inversion training and test models, and the mean square error distribution is better. At the same time, a double polarized anomalous bodies model was also used to verify the feasibility and effectiveness of the proposed method, the inversion results show that the QPSO-BP algorithm inversion clearly characterizes the anomalous boundaries and is closer to the values of the parameters.

关键词： Complex Resistivity Finite Element Method Nonlinear inversion QPSO-BP Algorithm 2.5D Numerical Simulation

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Zoeppritz-based AVO inversion using an improved Markov chain Monte Carlo method

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Petroleum Science 2017年第1期14卷 75-83页

作者： Xin-Peng Pan Guang-Zhi Zhang Jia-Jia Zhang Xing-Yao Yin School of Geosciences China University of Petroleum(Huadong) Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and Technology

The conventional Markov chain Monte Carlo （MCMC） method is limited to the selected shape and size of proposal distribution and is not easy to start when the initial proposal distribution is far away from the target distribution. To overcome these drawbacks of the conventional MCMC method, two useful improvements in MCMC method, adaptive Metropolis （AM） algorithm and delayed rejection （DR） algorithm, are attempted to be combined. The AM algorithm aims at adapting the proposal distribution by using the generated estimators, and the DR algorithm aims at enhancing the efficiency of the improved MCMC method. Based on the improved MCMC method, a Bayesian amplitude versus offset （AVO） inversion method on the basis of the exact Zoeppritz equation has been developed, with which the P- and S-wave velocities and the density can be obtained directly, and the uncertainty of AVO inversion results has been estimated as well. The study based on the logging data and the seismic data demonstrates the feasibility and robustness of the method and shows that all three parameters are well retrieved. So the exact Zoeppritz-based Nonlinear inversion method by using the improved MCMC is not only suitable for reservoirs with strong-contrast interfaces and longoffset ranges but also it is more stable, accurate and antinoise.

关键词： Adaptive Metropolis （AM） algorithm Delayed rejection （DR） algorithm Bayesian AVOinversion Exact Zoeppritz Nonlinear inversion

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Study on crustal,lithospheric and asthenospheric thickness beneath the Qinghai-Tibet Plateau and its adjacent areas

Study on crustal,lithospheric and asthenospheric thickness b...

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中国科学院地质与地球物理研究所2007学术年会

作者：张雪梅 Institute of Geology and Geophysics Chinese Academy of Sciences

Based on the results of pure dispersions of Rayleigh wave tomography in the Qinghai-Tibet Plateau and its adjacent areas,taking S wave velocities from previous linear inversion as the initial model,using the simulated annealing algorithm,a nonlinear simultaneous inversion has been carried out for S wave velocity and thickness of different layers,including the crust,the lithosphere and the asthenosphere. The results indicate:The crustal thickness shows strong correlation with geology structures sketched by the sutures and major faults.The crust is very thick in the Qinghai-Tibet Plateau,varying from 60 km to 80 km.The lithospheric thickness in the Qinghai-Tibet Plateau is thinner(130-160 km) than its adjacent areas.And two blocks can be recognized,divided by an NNE strike boundary running between 90°E-92°E Inside the plateau.Its asthenosphere is relatively thick,varies from 150 km to 230 km,and the thickest area is located in the western Qiangtang.India has a thinner crust(32-38 km),a thicker lithosphere of 190 km and a rather thin asthenosphere of only 60 km.Sichuan and Tarim basins have the crust thickness less than 50 km.Their lithospheres are thicker than the Qinghai-Tibet Plateau, and their asthenospheres are thinner.A discussion has been made on the character and formation mechanism of the typical crust-mantle transition zone in the western Qiangtang block.

关键词： Qinghai-Tibet Plateau lithospheric thickness asthenospheric thickness Nonlinear inversion seismic tomography

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