In the multi-wave and multi-component seismic exploration,shear-wave will be split into fast wave and slow wave,when it propagates in anisotropic media. Then the authors can predict polarization direction and density ...In the multi-wave and multi-component seismic exploration,shear-wave will be split into fast wave and slow wave,when it propagates in anisotropic media. Then the authors can predict polarization direction and density of crack and detect the development status of cracks underground according to shear-wave splitting phenomenon. The technology plays an important role and shows great potential in crack reservoir detection. In this study,the improved particle swarm optimization algorithm based on shrinkage factor is combined with the Pearson correlation coefficient method to obtain the fracture azimuth angle and density. The experimental results show that the modified method can improve the convergence rate,accuracy,anti-noise performance and computational efficiency.展开更多
The bioavailability of 22 heavy metals was investigated at 19 sampling sites in Tieguanyin tea garden in Anxi County,Fujian Province,southeastern China.Heavy metal concentrations were determined by inductively coupled...The bioavailability of 22 heavy metals was investigated at 19 sampling sites in Tieguanyin tea garden in Anxi County,Fujian Province,southeastern China.Heavy metal concentrations were determined by inductively coupled plasma-mass spectrometry(ICP-MS)and evaluated by geo-accumulation index(I_(geo)).Dilute nitric acid extraction was used to evaluate biological activity.Cu,Pb,and Cd were highly bioavailable and most easily absorbed by tea trees.Heavy metal bioavailability in the surface soil was as the ratio of the effective state to the total amount.Cd had the highest I_(geo)values,and the respective samples and sites were classified as moderately/strongly contaminated.Cd element is considered the main factor of heavy metal pollution in the tea garden in Anxi.The other heavy metals studied were present in lower concentrations;thus,the samples were classified as uncontaminated or slightly contaminated.展开更多
The distribution of sedimentary microfacies in the eighth member of the Shihezi formation（the H8 member） in the Sul4 3D seismic test area was investigated.A Support Vector Machine（SVM） model was introduced for the...The distribution of sedimentary microfacies in the eighth member of the Shihezi formation（the H8 member） in the Sul4 3D seismic test area was investigated.A Support Vector Machine（SVM） model was introduced for the first time as a way of predicting sandstone thickness in the study area.The model was constructed by analysis and optimization of measured seismic attributes.The distribution of the sedimentary microfacies in the study area was determined from predicted sandstone thickness and an analysis of sedimentary characteristics of the area.The results indicate that sandstone thickness predictions in the study area using an SVM method are good.The distribution of the sedimentary microfacies in the study area has been depicted at a fine scale.展开更多
Concentrations of heavy metals in 74 sediment samples from the Fenghe River, which originates from the north of the Qinling Mountains and flows through Xi'an, Shaanxi Province, China, were characterized by employi...Concentrations of heavy metals in 74 sediment samples from the Fenghe River, which originates from the north of the Qinling Mountains and flows through Xi'an, Shaanxi Province, China, were characterized by employing geographic information system(GIS)mapping, fuzzy synthetic assessment, and multivariate statistical analysis to determine the enrichment characteristics of heavy metals as well as their potential risks of pollution to sediments. Al, Cd, and Co were the major pollutants, with a high enrichment factor(EF) value. Heavy metal concentrations from samples near the paper plant were maintained at a high level. Significant enrichment of Al, Ba, Cr, Ni, Pb, and Co was found in the midstream and downstream, while high concentration of Cu occurred in the headwater stream. Based on the cluster and principal component analyses, sediment metals mainly came from the paper plants, agronomic practices, natural sources, and tourism, with a contribution of 51.59%, 23.01%, 14.21%, and 9.88%, respectively. Sediment pollution assessment explored using fuzzy theory based on the entropy method and toxicity coefficient showed that 26, 32, and 11 sites fell into Class III(slightly polluted), Class IV(moderately polluted), and Class V(heavily polluted), respectively, and their scores of membership degree in the polluted level were on the rise, suggesting a relatively high degree of sediment metal pollution in the study area. Closely related to the excessive industrial and agricultural applications, metal pollution in sediment is necessary to be addressed in the Fenghe River.展开更多
文摘In the multi-wave and multi-component seismic exploration,shear-wave will be split into fast wave and slow wave,when it propagates in anisotropic media. Then the authors can predict polarization direction and density of crack and detect the development status of cracks underground according to shear-wave splitting phenomenon. The technology plays an important role and shows great potential in crack reservoir detection. In this study,the improved particle swarm optimization algorithm based on shrinkage factor is combined with the Pearson correlation coefficient method to obtain the fracture azimuth angle and density. The experimental results show that the modified method can improve the convergence rate,accuracy,anti-noise performance and computational efficiency.
基金supported by the National Science Foundation of China(21177043,21377042)the National Science Foundation of Fujian Province(2015J01147)+1 种基金Fujian Provincial Key Laboratory of Ecology-Toxicological Effects and Control for Emerging Contaminants(PY16006)the Research Program of Science and Technology of Quanzhou City Government(2012Z86,2014Z130)
文摘The bioavailability of 22 heavy metals was investigated at 19 sampling sites in Tieguanyin tea garden in Anxi County,Fujian Province,southeastern China.Heavy metal concentrations were determined by inductively coupled plasma-mass spectrometry(ICP-MS)and evaluated by geo-accumulation index(I_(geo)).Dilute nitric acid extraction was used to evaluate biological activity.Cu,Pb,and Cd were highly bioavailable and most easily absorbed by tea trees.Heavy metal bioavailability in the surface soil was as the ratio of the effective state to the total amount.Cd had the highest I_(geo)values,and the respective samples and sites were classified as moderately/strongly contaminated.Cd element is considered the main factor of heavy metal pollution in the tea garden in Anxi.The other heavy metals studied were present in lower concentrations;thus,the samples were classified as uncontaminated or slightly contaminated.
基金Financial support for this work,provided by the Major National Science and Technology Special Projects(No.2008ZX05008)
文摘The distribution of sedimentary microfacies in the eighth member of the Shihezi formation（the H8 member） in the Sul4 3D seismic test area was investigated.A Support Vector Machine（SVM） model was introduced for the first time as a way of predicting sandstone thickness in the study area.The model was constructed by analysis and optimization of measured seismic attributes.The distribution of the sedimentary microfacies in the study area was determined from predicted sandstone thickness and an analysis of sedimentary characteristics of the area.The results indicate that sandstone thickness predictions in the study area using an SVM method are good.The distribution of the sedimentary microfacies in the study area has been depicted at a fine scale.
基金supported by the National Natural Science Foundation of China(Nos.41030744 and 41173123)
文摘Concentrations of heavy metals in 74 sediment samples from the Fenghe River, which originates from the north of the Qinling Mountains and flows through Xi'an, Shaanxi Province, China, were characterized by employing geographic information system(GIS)mapping, fuzzy synthetic assessment, and multivariate statistical analysis to determine the enrichment characteristics of heavy metals as well as their potential risks of pollution to sediments. Al, Cd, and Co were the major pollutants, with a high enrichment factor(EF) value. Heavy metal concentrations from samples near the paper plant were maintained at a high level. Significant enrichment of Al, Ba, Cr, Ni, Pb, and Co was found in the midstream and downstream, while high concentration of Cu occurred in the headwater stream. Based on the cluster and principal component analyses, sediment metals mainly came from the paper plants, agronomic practices, natural sources, and tourism, with a contribution of 51.59%, 23.01%, 14.21%, and 9.88%, respectively. Sediment pollution assessment explored using fuzzy theory based on the entropy method and toxicity coefficient showed that 26, 32, and 11 sites fell into Class III(slightly polluted), Class IV(moderately polluted), and Class V(heavily polluted), respectively, and their scores of membership degree in the polluted level were on the rise, suggesting a relatively high degree of sediment metal pollution in the study area. Closely related to the excessive industrial and agricultural applications, metal pollution in sediment is necessary to be addressed in the Fenghe River.
