In Rayleigh wave exploration,the inversion of dispersion curves is a crucial step for obtaining subsurface stratigraphic information,characterized by its multi-parameter and multi-extremum nature.Local optimization al...In Rayleigh wave exploration,the inversion of dispersion curves is a crucial step for obtaining subsurface stratigraphic information,characterized by its multi-parameter and multi-extremum nature.Local optimization algorithms used in dispersion curve inversion are highly dependent on the initial model and are prone to being trapped in local optima,while classical global optimization algorithms often suffer from slow convergence and low solution accuracy.To address these issues,this study introduces the Osprey Optimization Algorithm(OOA),known for its strong global search and local exploitation capabilities,into the inversion of dispersion curves to enhance inversion performance.In noiseless theoretical models,the OOA demonstrates excellent inversion accuracy and stability,accurately recovering model parameters.Even in noisy models,OOA maintains robust performance,achieving high inversion precision under high-noise conditions.In multimode dispersion curve tests,OOA effectively handles higher modes due to its efficient global and local search capabilities,and the inversion results show high consistency with theoretical values.Field data from the Wyoming region in the United States and a landfill site in Italy further verify the practical applicability of the OOA.Comprehensive test results indicate that the OOA outperforms the Particle Swarm Optimization(PSO)algorithm,providing a highly accurate and reliable inversion strategy for dispersion curve inversion.展开更多
With the continuous improvement of the accuracy of geodetic deformation data,the inversion of seismic source parameters puts forward a higher demand for nonlinear inversion algorithms.In this research,an improved Spar...With the continuous improvement of the accuracy of geodetic deformation data,the inversion of seismic source parameters puts forward a higher demand for nonlinear inversion algorithms.In this research,an improved Sparrow Search Algorithm(SSA)is proposed for the seismic source parameter inversion problem.By replacing the original population generation in the improved algorithm with Latin hypercubic sampling,the Sparrow Search Algorithm reduces the repetition of samples in the population initialization.Subsequently,the algorithm introduces adaptive weights in the discoverer generation phase of the sparrow algorithm and combines the Levy flight strategy to make the algorithm more comprehensive and improve the search accuracy during the whole iteration process.Therefore,the improved Latin hypercube-based sparrow search algorithm(ILHSSA)has better advantages in terms of iterative convergence speed and stability.In order to verify the performance of ILHSSA,the basic genetic algorithm(GA)and sparrow search algorithm(SSA)are examined and compared with ILHSSA by simulated earthquakes of two different earthquake types.The simulation experiments show that the improved algorithm ILHSSA outperforms SSA in accuracy and stability.Compared with the GA algorithm,ILHSSA can achieve the same inversion accuracy as GA,and it even surpasses GA in inversion speed and the inversion results of some parameters,demonstrating better stability.Finally,the improved algorithm is used for the 2017 Bodrum-Cos earthquake and the 2016 Amatrice earthquake in Italy.The inversion results all reflect the practicality and reliability of the improved algorithm.展开更多
The intelligent optimization of a multi-objective evolutionary algorithm is combined with a gradient algorithm. The hybrid multi-objective gradient algorithm is framed by the real number. Test functions are used to an...The intelligent optimization of a multi-objective evolutionary algorithm is combined with a gradient algorithm. The hybrid multi-objective gradient algorithm is framed by the real number. Test functions are used to analyze the efficiency of the algorithm. In the simulation case of the water phantom, the algorithm is applied to an inverse planning process of intensity modulated radiation treatment （IMRT）. The objective functions of planning target volume （PTV） and normal tissue （NT） are based on the average dose distribution. The obtained intensity profile shows that the hybrid multi-objective gradient algorithm saves the computational time and has good accuracy, thus meeting the requirements of practical applications.展开更多
Combining the adaptive shrinkage genetic algorithm in the feasible region with the imaging of apparent vertical conductance differential, we have inverted the TEM conductive thin layer. The result of the inversion dem...Combining the adaptive shrinkage genetic algorithm in the feasible region with the imaging of apparent vertical conductance differential, we have inverted the TEM conductive thin layer. The result of the inversion demonstrates that by adaptive shrinkage in the feasible region, the calculation speed accelerates and the calculation precision improves. To a certain extent, in this method we surmount the transient electromagnetic sounding equivalence and reduced equivalence scope. Comparison of the inverted result with the forward curve clearly shows that we can image the conductive thin layer.展开更多
For density inversion of gravity anomaly data, once the inversion method is determined, the main factors affecting the inversion result are the inversion parameters and subdivision scheme. A set of reasonable inversio...For density inversion of gravity anomaly data, once the inversion method is determined, the main factors affecting the inversion result are the inversion parameters and subdivision scheme. A set of reasonable inversion parameters and subdivision scheme can, not only improve the inversion process efficiency, but also ensure inversion result accuracy. The gravity inversion method based on correlation searching and the golden section algorithm is an effective potential field inversion method. It can be used to invert 2D and 3D physical properties with potential data observed on flat or rough surfaces. In this paper, we introduce in detail the density inversion principles based on correlation searching and the golden section algorithm. Considering that the gold section algorithm is not globally optimized. we present a heuristic method to ensure the inversion result is globally optimized. With a series of model tests, we systematically compare and analyze the inversion result efficiency and accuracy with different parameters. Based on the model test results, we conclude the selection principles for each inversion parameter with which the inversion accuracy can be obviously improved.展开更多
This paper presents a new algorithm based on the power inversion （PI） and the linearly constrained minimum variance （LCMV）. This algorithm is capable of adjusting the weights of the antenna array in real time to r...This paper presents a new algorithm based on the power inversion （PI） and the linearly constrained minimum variance （LCMV）. This algorithm is capable of adjusting the weights of the antenna array in real time to respond to and improve the global positioning system （GPS） received signals coming from the desired directions and at the same time to highly suppress the jammers coming from the other directions. The simulation is performed for fixed and moving jammers. It indicates that this structure can give deeper nulls, more than 115 dB depths for fixed jammers and more than 94 dB depths for moving jammers.展开更多
The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and e...The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and efficiently: simulated annealing, genetic, particle swarm optimization, and ant colony optimization. Using both noise-free and noise-added synthetic data, it is demonstrated that all four intelligent algorithms can perform self-potential data inversion effectively. During the numerical experiments, the model distribution in search space, the relative errors of model parameters, and the elapsed time are recorded to evaluate the performance of the inversion. The results indicate that all the intelligent algorithms have good precision and tolerance to noise. Particle swarm optimization has the fastest convergence during iteration because of its good balanced searching capability between global and local minimisation.展开更多
To reduce the computational complexity of matrix inversion, which is the majority of processing in many practical applications, two numerically efficient recursive algorithms （called algorithms I and II, respectively...To reduce the computational complexity of matrix inversion, which is the majority of processing in many practical applications, two numerically efficient recursive algorithms （called algorithms I and II, respectively） are presented. Algorithm I is used to calculate the inverse of such a matrix, whose leading principal minors are all nonzero. Algorithm II, whereby, the inverse of an arbitrary nonsingular matrix can be evaluated is derived via improving the algorithm I. The implementation, for algorithm II or I, involves matrix-vector multiplications and vector outer products. These operations are computationally fast and highly parallelizable. MATLAB simulations show that both recursive algorithms are valid.展开更多
At present, near-surface shear wave velocities are mainly calculated through Rayleigh wave dispersion-curve inversions in engineering surface investigations, but the required calculations pose a highly nonlinear globa...At present, near-surface shear wave velocities are mainly calculated through Rayleigh wave dispersion-curve inversions in engineering surface investigations, but the required calculations pose a highly nonlinear global optimization problem. In order to alleviate the risk of falling into a local optimal solution, this paper introduces a new global optimization method, the shuffle frog-leaping algorithm （SFLA）, into the Rayleigh wave dispersion-curve inversion process. SFLA is a swarm-intelligence-based algorithm that simulates a group of frogs searching for food. It uses a few parameters, achieves rapid convergence, and is capability of effective global searching. In order to test the reliability and calculation performance of SFLA, noise-free and noisy synthetic datasets were inverted. We conducted a comparative analysis with other established algorithms using the noise-free dataset, and then tested the ability of SFLA to cope with data noise. Finally, we inverted a real-world example to examine the applicability of SFLA. Results from both synthetic and field data demonstrated the effectiveness of SFLA in the interpretation of Rayleigh wave dispersion curves. We found that SFLA is superior to the established methods in terms of both reliability and computational efficiency, so it offers great potential to improve our ability to solve geophysical inversion problems.展开更多
This paper discusses the inversion of velocity structure and hypocenters location in the Beijing Tianjin Tangshan Zhangjiakou area by genetic algorithm. The hypocenters location of sele...This paper discusses the inversion of velocity structure and hypocenters location in the Beijing Tianjin Tangshan Zhangjiakou area by genetic algorithm. The hypocenters location of selected earthquakes and crustal structure of this area are obtained using the travel time data of local earthquakes acquired by the Telemetered Seismic Network of Northern China. The mean and standard residuals of hypocenter location acquired by this method are much less than those provided by the report of respective earthquakes. The crustal structure of the first and the second layers obtained interpret the outline of the plain and mountain area in the region successfully and the crustal structure of the third layer nearly coincides with the Moho discontinuity obtained by artificial seismic sounding. These show the genetic algorithm is effective to the inversion of hypocenter location and three dimensional velocity structure.展开更多
Random vibration control is aimed at reproducing the power spectral density(PSD)at specified control points.The classical frequency-spectrum equalization algorithm needs to compute the average of the multiple frequenc...Random vibration control is aimed at reproducing the power spectral density(PSD)at specified control points.The classical frequency-spectrum equalization algorithm needs to compute the average of the multiple frequency response functions(FRFs),which lengthens the control loop time in the equalization process.Likewise,the feedback control algorithm has a very slow convergence rate due to the small value of the feedback gain parameter to ensure stability of the system.To overcome these limitations,an adaptive inverse control of random vibrations based on the filtered-X least mean-square(LMS)algorithm is proposed.Furthermore,according to the description and iteration characteristics of random vibration tests in the frequency domain,the frequency domain LMS algorithm is adopted to refine the inverse characteristics of the FRF instead of the traditional time domain LMS algorithm.This inverse characteristic,which is called the impedance function of the system under control,is used to update the drive PSD directly.The test results indicated that in addition to successfully avoiding the instability problem that occurs during the iteration process,the adaptive control strategy minimizes the amount of time needed to obtain a short control loop and achieve equalization.展开更多
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 a...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.展开更多
Viscoelastic parameters are becoming more important and their inversion algorithms are studied by many researchers. Genetic algorithms are random, self-adaptive, robust, and heuristic with global search and convergenc...Viscoelastic parameters are becoming more important and their inversion algorithms are studied by many researchers. Genetic algorithms are random, self-adaptive, robust, and heuristic with global search and convergence abilities. Based on the direct VSP wave equation, a genetic algorithm （GA） is introduced to determine the viscoelastic parameters. First, the direct wave equation in frequency is expressed as a function of complex velocity and then the complex velocities estimated by GA inversion. Since the phase velocity and Q-factor both are functions of complex velocity, their values can be computed easily. However, there are so many complex velocities that it is difficult to invert them directly. They can be rewritten as a function of Co and C∞ to reduce the number of parameters during the inversion process. Finally, a theoretical model experiment proves that our algorithm is exact and effective.展开更多
Smooth constraint is important in linear inversion, but it is difficult to apply directly to model parameters in genetic algorithms. If the model parameters are smoothed in iteration, the diversity of models will be g...Smooth constraint is important in linear inversion, but it is difficult to apply directly to model parameters in genetic algorithms. If the model parameters are smoothed in iteration, the diversity of models will be greatly suppressed and all the models in population will tend to equal in a few iterations, so the optimal solution meeting requirement can not be obtained. In this paper, an indirect smooth constraint technique is introduced to genetic inversion. In this method, the new models produced in iteration are smoothed, then used as theoretical models in calculation of misfit function, but in process of iteration only the original models are used in order to keep the diversity of models. The technique is effective in inversion of surface wave and receiver function. Using this technique, we invert the phase velocity of Raleigh wave in the Tibetan Plateau, revealing the horizontal variation of S wave velocity structure near the center of the Tibetan Plateau. The results show that the S wave velocity in the north is relatively lower than that in the south. For most paths there is a lower velocity zone with 12-25 km thick at the depth of 15-40 km. The lower velocity zone in upper mantle is located below the depth of 100 km, and the thickness is usually 40-80 km, but for a few paths reach to 100 km thick. Among the area of Ando, Maqi and Ushu stations, there is an obvious lower velocity zone with the lowest velocity of 4.2-4.3 km/s at the depth of 90-230 km. Based on the S wave velocity structures of different paths and former data, we infer that the subduction of the Indian Plate is delimited nearby the Yarlung Zangbo suture zone.展开更多
With the continuous development of full tensor gradiometer （FTG） measurement techniques, three-dimensional （3D） inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processin...With the continuous development of full tensor gradiometer （FTG） measurement techniques, three-dimensional （3D） inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processing and interpretation of large-scale high-precision data, the use of the graphics processing unit process unit （GPU） and preconditioning methods are very important in the data inversion. In this paper, an improved preconditioned conjugate gradient algorithm is proposed by combining the symmetric successive over-relaxation （SSOR） technique and the incomplete Choleksy decomposition conjugate gradient algorithm （ICCG）. Since preparing the preconditioner requires extra time, a parallel implement based on GPU is proposed. The improved method is then applied in the inversion of noise- contaminated synthetic data to prove its adaptability in the inversion of 3D FTG data. Results show that the parallel SSOR-ICCG algorithm based on NVIDIA Tesla C2050 GPU achieves a speedup of approximately 25 times that of a serial program using a 2.0 GHz Central Processing Unit （CPU）. Real airbome gravity-gradiometry data from Vinton salt dome （south- west Louisiana, USA） are also considered. Good results are obtained, which verifies the efficiency and feasibility of the proposed parallel method in fast inversion of 3D FTG data.展开更多
We propose a bio-optical inversion model that retrieves the absorption contributions of phytoplankton and colored detrital matter(CDM),as well as the phytoplankton size classes(PSCs),from total minus water absorption ...We propose a bio-optical inversion model that retrieves the absorption contributions of phytoplankton and colored detrital matter(CDM),as well as the phytoplankton size classes(PSCs),from total minus water absorption spectra.The model is based on three-component separation of phytoplankton size structure and a genetic algorithm.The model performance was tested on two independent datasets(the NASA bio-Optical Marine Algorithm Dataset(NOMAD) and the northern South China Sea(NSCS) dataset).The relationships between the estimated and measured values were strongly linear,especially for aCDM(412),and the Root Mean Square Error(RMSE) of the CDM exponential slope(SCDM) was relatively low.Next,the inversion model was directly applied to in-situ total minus water absorption spectra determined by an underwater meter during a cruise in September 2008,to retrieve the phytoplankton size structure in the seawater.By comparing the measured and retrieved chlorophyll a concentrations,we demonstrated that total and size-specific chlorophyll a concentrations could be retrieved by the model with relatively high accuracy.Finally,we applied the bio-optical inversion model to investigate changes in phytoplankton size structure induced by an anti-cyclonic eddy in the NSCS.展开更多
As geological exploration conditions become increasingly complex, meeting the requirements of precise geological exploration necessitates the development of a controlled-source audio magnetotelluric (CSAMT) inversion ...As geological exploration conditions become increasingly complex, meeting the requirements of precise geological exploration necessitates the development of a controlled-source audio magnetotelluric (CSAMT) inversion method that considers anisotropy to improve the effectiveness of inversion accuracy and interpretation accuracy of data. This study is based on the 3D fi nite-diff erence forward modeling of axis anisotropy using the reciprocity theorem to calculate the Jacobian matrix by applying the search method to automatically search for the Lagrange operator. The aim is to establish inversion iteration equations to achieve the axis anisotropic Occam's 3D inversion of tensor CSAMT in data space. Further, we obtain an underground axis anisotropic 3D geoelectric model by inverting the impedance data of tensor CSAMT. Two synthetic data examples show that using the isotropic tensor CSAMT algorithm to directly invert data in anisotropic media can generate false anomalies, leading to incorrect geological interpretations. Meanwhile, the proposed anisotropic inversion algorithm can eff ectively improve the accuracy of data inversion in anisotropic media. Further, the inversion examples verify the eff ectiveness and stability of the algorithm.展开更多
The use of geodetic observation data for seismic fault parameters inversion is the research hotspot of geodetic inversion, and it is also the focus of studying the mechanism of earthquake occurrence. Seismic fault par...The use of geodetic observation data for seismic fault parameters inversion is the research hotspot of geodetic inversion, and it is also the focus of studying the mechanism of earthquake occurrence. Seismic fault parameters inversion has nonlinear characteristics, and the gradient-based optimizer(GBO) has the characteristics of fast convergence speed and falling into local optimum hardly. This paper applies GBO algorithm to simulated earthquakes and real LuShan earthquakes in the nonlinear inversion of the Okada model to obtain the source parameters. The simulated earthquake experiment results show that the algorithm is stable, and the seismic source parameters obtained by GBO are slightly closer to the true value than the multi peak particle swarm optimization(MPSO). In the 2013 LuShan earthquake experiment, the root mean square error between the deformation after forwarding of fault parameters obtained by the introduced GBO algorithm and the surface observation deformation was 3.703 mm, slightly better than 3.708 mm calculated by the MPSO. Moreover, the inversion result of GBO algorithm is better than MPSO algorithm in stability. The above results show that the introduced GBO algorithm has a certain practical application value in seismic fault source parameters inversion.展开更多
基金sponsored by China Geological Survey Project(DD20243193 and DD20230206508).
文摘In Rayleigh wave exploration,the inversion of dispersion curves is a crucial step for obtaining subsurface stratigraphic information,characterized by its multi-parameter and multi-extremum nature.Local optimization algorithms used in dispersion curve inversion are highly dependent on the initial model and are prone to being trapped in local optima,while classical global optimization algorithms often suffer from slow convergence and low solution accuracy.To address these issues,this study introduces the Osprey Optimization Algorithm(OOA),known for its strong global search and local exploitation capabilities,into the inversion of dispersion curves to enhance inversion performance.In noiseless theoretical models,the OOA demonstrates excellent inversion accuracy and stability,accurately recovering model parameters.Even in noisy models,OOA maintains robust performance,achieving high inversion precision under high-noise conditions.In multimode dispersion curve tests,OOA effectively handles higher modes due to its efficient global and local search capabilities,and the inversion results show high consistency with theoretical values.Field data from the Wyoming region in the United States and a landfill site in Italy further verify the practical applicability of the OOA.Comprehensive test results indicate that the OOA outperforms the Particle Swarm Optimization(PSO)algorithm,providing a highly accurate and reliable inversion strategy for dispersion curve inversion.
基金funded by the National Natural Science Foundation of China(42174011).
文摘With the continuous improvement of the accuracy of geodetic deformation data,the inversion of seismic source parameters puts forward a higher demand for nonlinear inversion algorithms.In this research,an improved Sparrow Search Algorithm(SSA)is proposed for the seismic source parameter inversion problem.By replacing the original population generation in the improved algorithm with Latin hypercubic sampling,the Sparrow Search Algorithm reduces the repetition of samples in the population initialization.Subsequently,the algorithm introduces adaptive weights in the discoverer generation phase of the sparrow algorithm and combines the Levy flight strategy to make the algorithm more comprehensive and improve the search accuracy during the whole iteration process.Therefore,the improved Latin hypercube-based sparrow search algorithm(ILHSSA)has better advantages in terms of iterative convergence speed and stability.In order to verify the performance of ILHSSA,the basic genetic algorithm(GA)and sparrow search algorithm(SSA)are examined and compared with ILHSSA by simulated earthquakes of two different earthquake types.The simulation experiments show that the improved algorithm ILHSSA outperforms SSA in accuracy and stability.Compared with the GA algorithm,ILHSSA can achieve the same inversion accuracy as GA,and it even surpasses GA in inversion speed and the inversion results of some parameters,demonstrating better stability.Finally,the improved algorithm is used for the 2017 Bodrum-Cos earthquake and the 2016 Amatrice earthquake in Italy.The inversion results all reflect the practicality and reliability of the improved algorithm.
基金Supported by the National Basic Research Program of China ("973" Program)the National Natural Science Foundation of China (60872112, 10805012)+1 种基金the Natural Science Foundation of Zhejiang Province(Z207588)the College Science Research Project of Anhui Province (KJ2008B268)~~
文摘The intelligent optimization of a multi-objective evolutionary algorithm is combined with a gradient algorithm. The hybrid multi-objective gradient algorithm is framed by the real number. Test functions are used to analyze the efficiency of the algorithm. In the simulation case of the water phantom, the algorithm is applied to an inverse planning process of intensity modulated radiation treatment （IMRT）. The objective functions of planning target volume （PTV） and normal tissue （NT） are based on the average dose distribution. The obtained intensity profile shows that the hybrid multi-objective gradient algorithm saves the computational time and has good accuracy, thus meeting the requirements of practical applications.
文摘Combining the adaptive shrinkage genetic algorithm in the feasible region with the imaging of apparent vertical conductance differential, we have inverted the TEM conductive thin layer. The result of the inversion demonstrates that by adaptive shrinkage in the feasible region, the calculation speed accelerates and the calculation precision improves. To a certain extent, in this method we surmount the transient electromagnetic sounding equivalence and reduced equivalence scope. Comparison of the inverted result with the forward curve clearly shows that we can image the conductive thin layer.
基金supported by Specialized Research Fund for the Doctoral Program of Higher Education of China(20110022120004)the Fundamental Research Funds for the Central Universities
文摘For density inversion of gravity anomaly data, once the inversion method is determined, the main factors affecting the inversion result are the inversion parameters and subdivision scheme. A set of reasonable inversion parameters and subdivision scheme can, not only improve the inversion process efficiency, but also ensure inversion result accuracy. The gravity inversion method based on correlation searching and the golden section algorithm is an effective potential field inversion method. It can be used to invert 2D and 3D physical properties with potential data observed on flat or rough surfaces. In this paper, we introduce in detail the density inversion principles based on correlation searching and the golden section algorithm. Considering that the gold section algorithm is not globally optimized. we present a heuristic method to ensure the inversion result is globally optimized. With a series of model tests, we systematically compare and analyze the inversion result efficiency and accuracy with different parameters. Based on the model test results, we conclude the selection principles for each inversion parameter with which the inversion accuracy can be obviously improved.
文摘This paper presents a new algorithm based on the power inversion （PI） and the linearly constrained minimum variance （LCMV）. This algorithm is capable of adjusting the weights of the antenna array in real time to respond to and improve the global positioning system （GPS） received signals coming from the desired directions and at the same time to highly suppress the jammers coming from the other directions. The simulation is performed for fixed and moving jammers. It indicates that this structure can give deeper nulls, more than 115 dB depths for fixed jammers and more than 94 dB depths for moving jammers.
基金Project(41574123)supported by the National Natural Science Foundation of ChinaProject(2015zzts250)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(2013FY110800)supported by the National Basic Research Scientific Program of China
文摘The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and efficiently: simulated annealing, genetic, particle swarm optimization, and ant colony optimization. Using both noise-free and noise-added synthetic data, it is demonstrated that all four intelligent algorithms can perform self-potential data inversion effectively. During the numerical experiments, the model distribution in search space, the relative errors of model parameters, and the elapsed time are recorded to evaluate the performance of the inversion. The results indicate that all the intelligent algorithms have good precision and tolerance to noise. Particle swarm optimization has the fastest convergence during iteration because of its good balanced searching capability between global and local minimisation.
文摘To reduce the computational complexity of matrix inversion, which is the majority of processing in many practical applications, two numerically efficient recursive algorithms （called algorithms I and II, respectively） are presented. Algorithm I is used to calculate the inverse of such a matrix, whose leading principal minors are all nonzero. Algorithm II, whereby, the inverse of an arbitrary nonsingular matrix can be evaluated is derived via improving the algorithm I. The implementation, for algorithm II or I, involves matrix-vector multiplications and vector outer products. These operations are computationally fast and highly parallelizable. MATLAB simulations show that both recursive algorithms are valid.
基金supported by the National Natural Science Foundation of China(No.41374123)
文摘At present, near-surface shear wave velocities are mainly calculated through Rayleigh wave dispersion-curve inversions in engineering surface investigations, but the required calculations pose a highly nonlinear global optimization problem. In order to alleviate the risk of falling into a local optimal solution, this paper introduces a new global optimization method, the shuffle frog-leaping algorithm （SFLA）, into the Rayleigh wave dispersion-curve inversion process. SFLA is a swarm-intelligence-based algorithm that simulates a group of frogs searching for food. It uses a few parameters, achieves rapid convergence, and is capability of effective global searching. In order to test the reliability and calculation performance of SFLA, noise-free and noisy synthetic datasets were inverted. We conducted a comparative analysis with other established algorithms using the noise-free dataset, and then tested the ability of SFLA to cope with data noise. Finally, we inverted a real-world example to examine the applicability of SFLA. Results from both synthetic and field data demonstrated the effectiveness of SFLA in the interpretation of Rayleigh wave dispersion curves. We found that SFLA is superior to the established methods in terms of both reliability and computational efficiency, so it offers great potential to improve our ability to solve geophysical inversion problems.
文摘This paper discusses the inversion of velocity structure and hypocenters location in the Beijing Tianjin Tangshan Zhangjiakou area by genetic algorithm. The hypocenters location of selected earthquakes and crustal structure of this area are obtained using the travel time data of local earthquakes acquired by the Telemetered Seismic Network of Northern China. The mean and standard residuals of hypocenter location acquired by this method are much less than those provided by the report of respective earthquakes. The crustal structure of the first and the second layers obtained interpret the outline of the plain and mountain area in the region successfully and the crustal structure of the third layer nearly coincides with the Moho discontinuity obtained by artificial seismic sounding. These show the genetic algorithm is effective to the inversion of hypocenter location and three dimensional velocity structure.
基金Program for New Century Excellent Talents in Universities Under Grant No.NCET-04-0325
文摘Random vibration control is aimed at reproducing the power spectral density(PSD)at specified control points.The classical frequency-spectrum equalization algorithm needs to compute the average of the multiple frequency response functions(FRFs),which lengthens the control loop time in the equalization process.Likewise,the feedback control algorithm has a very slow convergence rate due to the small value of the feedback gain parameter to ensure stability of the system.To overcome these limitations,an adaptive inverse control of random vibrations based on the filtered-X least mean-square(LMS)algorithm is proposed.Furthermore,according to the description and iteration characteristics of random vibration tests in the frequency domain,the frequency domain LMS algorithm is adopted to refine the inverse characteristics of the FRF instead of the traditional time domain LMS algorithm.This inverse characteristic,which is called the impedance function of the system under control,is used to update the drive PSD directly.The test results indicated that in addition to successfully avoiding the instability problem that occurs during the iteration process,the adaptive control strategy minimizes the amount of time needed to obtain a short control loop and achieve equalization.
基金supported by the National Natural Science Foundation of China(U19B6003,42122029)the Strategic Cooperation Technology Projects of CNPC and CUPB(ZLZX 202003)partially supported by SEG/WesternGeco Scholarship,SEG Foundation/Chevron Scholarship,and SEG/Norman and Shirley Domenico Scholarship
文摘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.
文摘Viscoelastic parameters are becoming more important and their inversion algorithms are studied by many researchers. Genetic algorithms are random, self-adaptive, robust, and heuristic with global search and convergence abilities. Based on the direct VSP wave equation, a genetic algorithm （GA） is introduced to determine the viscoelastic parameters. First, the direct wave equation in frequency is expressed as a function of complex velocity and then the complex velocities estimated by GA inversion. Since the phase velocity and Q-factor both are functions of complex velocity, their values can be computed easily. However, there are so many complex velocities that it is difficult to invert them directly. They can be rewritten as a function of Co and C∞ to reduce the number of parameters during the inversion process. Finally, a theoretical model experiment proves that our algorithm is exact and effective.
基金State Natural Science Foundation (49874021).Contribution No. 01FE2002, Institute of Geophysics, China Seismological Bureau.
文摘Smooth constraint is important in linear inversion, but it is difficult to apply directly to model parameters in genetic algorithms. If the model parameters are smoothed in iteration, the diversity of models will be greatly suppressed and all the models in population will tend to equal in a few iterations, so the optimal solution meeting requirement can not be obtained. In this paper, an indirect smooth constraint technique is introduced to genetic inversion. In this method, the new models produced in iteration are smoothed, then used as theoretical models in calculation of misfit function, but in process of iteration only the original models are used in order to keep the diversity of models. The technique is effective in inversion of surface wave and receiver function. Using this technique, we invert the phase velocity of Raleigh wave in the Tibetan Plateau, revealing the horizontal variation of S wave velocity structure near the center of the Tibetan Plateau. The results show that the S wave velocity in the north is relatively lower than that in the south. For most paths there is a lower velocity zone with 12-25 km thick at the depth of 15-40 km. The lower velocity zone in upper mantle is located below the depth of 100 km, and the thickness is usually 40-80 km, but for a few paths reach to 100 km thick. Among the area of Ando, Maqi and Ushu stations, there is an obvious lower velocity zone with the lowest velocity of 4.2-4.3 km/s at the depth of 90-230 km. Based on the S wave velocity structures of different paths and former data, we infer that the subduction of the Indian Plate is delimited nearby the Yarlung Zangbo suture zone.
基金the Sub-project of National Science and Technology Major Project of China(No.2016ZX05027-002-003)the National Natural Science Foundation of China(No.41404089)+1 种基金the State Key Program of National Natural Science of China(No.41430322)the National Basic Research Program of China(973 Program)(No.2015CB45300)
文摘With the continuous development of full tensor gradiometer （FTG） measurement techniques, three-dimensional （3D） inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processing and interpretation of large-scale high-precision data, the use of the graphics processing unit process unit （GPU） and preconditioning methods are very important in the data inversion. In this paper, an improved preconditioned conjugate gradient algorithm is proposed by combining the symmetric successive over-relaxation （SSOR） technique and the incomplete Choleksy decomposition conjugate gradient algorithm （ICCG）. Since preparing the preconditioner requires extra time, a parallel implement based on GPU is proposed. The improved method is then applied in the inversion of noise- contaminated synthetic data to prove its adaptability in the inversion of 3D FTG data. Results show that the parallel SSOR-ICCG algorithm based on NVIDIA Tesla C2050 GPU achieves a speedup of approximately 25 times that of a serial program using a 2.0 GHz Central Processing Unit （CPU）. Real airbome gravity-gradiometry data from Vinton salt dome （south- west Louisiana, USA） are also considered. Good results are obtained, which verifies the efficiency and feasibility of the proposed parallel method in fast inversion of 3D FTG data.
基金Supported by the Key Projects of the National Natural Science Foundation of China(Nos.41076014,U0933005,41176035,40906022,41206029)
文摘We propose a bio-optical inversion model that retrieves the absorption contributions of phytoplankton and colored detrital matter(CDM),as well as the phytoplankton size classes(PSCs),from total minus water absorption spectra.The model is based on three-component separation of phytoplankton size structure and a genetic algorithm.The model performance was tested on two independent datasets(the NASA bio-Optical Marine Algorithm Dataset(NOMAD) and the northern South China Sea(NSCS) dataset).The relationships between the estimated and measured values were strongly linear,especially for aCDM(412),and the Root Mean Square Error(RMSE) of the CDM exponential slope(SCDM) was relatively low.Next,the inversion model was directly applied to in-situ total minus water absorption spectra determined by an underwater meter during a cruise in September 2008,to retrieve the phytoplankton size structure in the seawater.By comparing the measured and retrieved chlorophyll a concentrations,we demonstrated that total and size-specific chlorophyll a concentrations could be retrieved by the model with relatively high accuracy.Finally,we applied the bio-optical inversion model to investigate changes in phytoplankton size structure induced by an anti-cyclonic eddy in the NSCS.
基金supported by Heilongjiang Province Basic Research Business Expenses for Universities Heilongjiang University Special Fund Project (Grant No. 2023-KYYWF-1494)the Natural Science Foundation of Jiangxi Province (Grant No. 20212BAB213023)。
文摘As geological exploration conditions become increasingly complex, meeting the requirements of precise geological exploration necessitates the development of a controlled-source audio magnetotelluric (CSAMT) inversion method that considers anisotropy to improve the effectiveness of inversion accuracy and interpretation accuracy of data. This study is based on the 3D fi nite-diff erence forward modeling of axis anisotropy using the reciprocity theorem to calculate the Jacobian matrix by applying the search method to automatically search for the Lagrange operator. The aim is to establish inversion iteration equations to achieve the axis anisotropic Occam's 3D inversion of tensor CSAMT in data space. Further, we obtain an underground axis anisotropic 3D geoelectric model by inverting the impedance data of tensor CSAMT. Two synthetic data examples show that using the isotropic tensor CSAMT algorithm to directly invert data in anisotropic media can generate false anomalies, leading to incorrect geological interpretations. Meanwhile, the proposed anisotropic inversion algorithm can eff ectively improve the accuracy of data inversion in anisotropic media. Further, the inversion examples verify the eff ectiveness and stability of the algorithm.
基金the National Natural Science Foundation of China(Nos.42174011and 41874001).
文摘The use of geodetic observation data for seismic fault parameters inversion is the research hotspot of geodetic inversion, and it is also the focus of studying the mechanism of earthquake occurrence. Seismic fault parameters inversion has nonlinear characteristics, and the gradient-based optimizer(GBO) has the characteristics of fast convergence speed and falling into local optimum hardly. This paper applies GBO algorithm to simulated earthquakes and real LuShan earthquakes in the nonlinear inversion of the Okada model to obtain the source parameters. The simulated earthquake experiment results show that the algorithm is stable, and the seismic source parameters obtained by GBO are slightly closer to the true value than the multi peak particle swarm optimization(MPSO). In the 2013 LuShan earthquake experiment, the root mean square error between the deformation after forwarding of fault parameters obtained by the introduced GBO algorithm and the surface observation deformation was 3.703 mm, slightly better than 3.708 mm calculated by the MPSO. Moreover, the inversion result of GBO algorithm is better than MPSO algorithm in stability. The above results show that the introduced GBO algorithm has a certain practical application value in seismic fault source parameters inversion.
