In marine seismic exploration, ocean-bottom cable techniques accurately record the multicomponent seismic wavefield; however, the seismic wave propagation in fluid–solid media cannot be simulated by a single wave equ...In marine seismic exploration, ocean-bottom cable techniques accurately record the multicomponent seismic wavefield; however, the seismic wave propagation in fluid–solid media cannot be simulated by a single wave equation. In addition, when the seabed interface is irregular, traditional finite-difference schemes cannot simulate the seismic wave propagation across the irregular seabed interface. Therefore, an acoustic–elastic forward modeling and vector-based P-and S-wave separation method is proposed. In this method, we divide the fluid–solid elastic media with irregular interface into orthogonal grids and map the irregular interface in the Cartesian coordinates system into a horizontal interface in the curvilinear coordinates system of the computational domain using coordinates transformation. The acoustic and elastic wave equations in the curvilinear coordinates system are applied to the fluid and solid medium, respectively. At the irregular interface, the two equations are combined into an acoustic–elastic equation in the curvilinear coordinates system. We next introduce a full staggered-grid scheme to improve the stability of the numerical simulation. Thus, separate P-and S-wave equations in the curvilinear coordinates system are derived to realize the P-and S-wave separation method.展开更多
Deoxyribonucleic acid（ DNA） microarray gene expression data has been widely utilized in the field of functional genomics,since it is helpful to study cancer,cells,tissues,organisms etc.But the sample sizes are relat...Deoxyribonucleic acid（ DNA） microarray gene expression data has been widely utilized in the field of functional genomics,since it is helpful to study cancer,cells,tissues,organisms etc.But the sample sizes are relatively small compared to the number of genes,so feature selection is very necessary to reduce complexity and increase the classification accuracy of samples. In this paper,a completely newimprovement over particle swarm optimization（ PSO） based on fluid mechanics is proposed for the feature selection. This newimprovement simulates the spontaneous process of the air from high pressure to lowpressure,therefore it allows for a search through all possible solution spaces and prevents particles from getting trapped in a local optimum. The experiment shows that,this newimproved algorithm had an elaborate feature simplification which achieved a very precise and significant accuracy in the classification of 8 among the 11 datasets,and it is much better in comparison with other methods for feature selection.展开更多
The targets, importance, difficulties, strategies, general function frame and technology frame of Petroleum DrillingFluid Engineering Design Expert Ssytem(PDFEDES) were discussed. A brief introduction to the special d...The targets, importance, difficulties, strategies, general function frame and technology frame of Petroleum DrillingFluid Engineering Design Expert Ssytem(PDFEDES) were discussed. A brief introduction to the special domain and application cases of the PDFEDES are given. A good prospect of artificial intelligence application in petroleum exploration engineering is presented.展开更多
基金financially supported by the Natural Science Foundation of China(No.41774133)the Open Funds of SINOPEC Key Laboratory of Geophysics(No.wtyjy-wx2017-01-04)National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2016ZX05024-003-011)
文摘In marine seismic exploration, ocean-bottom cable techniques accurately record the multicomponent seismic wavefield; however, the seismic wave propagation in fluid–solid media cannot be simulated by a single wave equation. In addition, when the seabed interface is irregular, traditional finite-difference schemes cannot simulate the seismic wave propagation across the irregular seabed interface. Therefore, an acoustic–elastic forward modeling and vector-based P-and S-wave separation method is proposed. In this method, we divide the fluid–solid elastic media with irregular interface into orthogonal grids and map the irregular interface in the Cartesian coordinates system into a horizontal interface in the curvilinear coordinates system of the computational domain using coordinates transformation. The acoustic and elastic wave equations in the curvilinear coordinates system are applied to the fluid and solid medium, respectively. At the irregular interface, the two equations are combined into an acoustic–elastic equation in the curvilinear coordinates system. We next introduce a full staggered-grid scheme to improve the stability of the numerical simulation. Thus, separate P-and S-wave equations in the curvilinear coordinates system are derived to realize the P-and S-wave separation method.
基金Supported by the National Natural Science Foundation of China(61472161,61402195,61502198)
文摘Deoxyribonucleic acid（ DNA） microarray gene expression data has been widely utilized in the field of functional genomics,since it is helpful to study cancer,cells,tissues,organisms etc.But the sample sizes are relatively small compared to the number of genes,so feature selection is very necessary to reduce complexity and increase the classification accuracy of samples. In this paper,a completely newimprovement over particle swarm optimization（ PSO） based on fluid mechanics is proposed for the feature selection. This newimprovement simulates the spontaneous process of the air from high pressure to lowpressure,therefore it allows for a search through all possible solution spaces and prevents particles from getting trapped in a local optimum. The experiment shows that,this newimproved algorithm had an elaborate feature simplification which achieved a very precise and significant accuracy in the classification of 8 among the 11 datasets,and it is much better in comparison with other methods for feature selection.
文摘The targets, importance, difficulties, strategies, general function frame and technology frame of Petroleum DrillingFluid Engineering Design Expert Ssytem(PDFEDES) were discussed. A brief introduction to the special domain and application cases of the PDFEDES are given. A good prospect of artificial intelligence application in petroleum exploration engineering is presented.
