First-break picking is the key step in seismic data processing for surveying undulate surfaces, and directly infl uences the precision of near-surface modeling and effects of static corrections. The current first-brea...First-break picking is the key step in seismic data processing for surveying undulate surfaces, and directly infl uences the precision of near-surface modeling and effects of static corrections. The current first-break auto-picking methods may fail when the signalto-noise ratio（SNR） is low for seismic data in the undulate area, and require labor and time intensive manual picking. This study develops an improved super-virtual interferometry（SVI） method that combines multichannel and multidomain quality control（MMQC） techniques to achieve auto-picked first breaks. The improved SVI method extends the SVI application to enhance the SNR for near-surface scattered waves for the first time, which allows for the SVI method to adapt to first breaks with complex raypaths by linear combination of refractions and near-surface scattered waves. Methods of inverse and multidomain interferometry are developed to effectively enhance the virtual records extracted by the SVI method. The deconvolution filter for waveforms is used to increase resolution and reduce false picks, while the MMQC technique is designed to auto-correct false picks and increase the stability of auto-picking first breaks. The robust technique developed in this study enables stable processing of large 3D seismic datasets. Higher quality results are obtained using the approach presented in this paper to actual field data from the mountain areas in western China, when compared to some commonly used commercial software.展开更多
This paper examines the distribution and structure of populations of a medicinal and culinary herb native to Armenia. As one of the first countries to join the Convention on Biological Diversity （CBD）, Armenia has a...This paper examines the distribution and structure of populations of a medicinal and culinary herb native to Armenia. As one of the first countries to join the Convention on Biological Diversity （CBD）, Armenia has a strong interest in assessing the biodiversity of its native flora and identifying threats to the conservation of these species, particularly those with economic value. Only limited information, however, is available at this time on the genetic biodiversity, population location, structure and size, and conservation status of most of these species. This paper reports the results of five consecutive years of field studies conducted in Armenia to 1） re-locate native populations of the important medicinal and culinary herb, Origanum vulgare L., 2） locate new populations, and 3） assess the growth pattern and dynamics of the populations. The quadrat sampling technique was used to identify key elements that determined population size and abundance. GPS maps of present and past population distributions were created. Particular habitat and environmental factors were identified as crucial to predicting the future conditions of these populations under the impact of global climate change. The research provides a baseline dataset that can be used for the development of further conservation strategies of this important medicinal and culinary species in Armenia.展开更多
基金supported by the National Basic Research Program of China(No.2013CB228602)the National Science and Technology Major Project of China(No.2011ZX05004-003)the National High Tech Research Program of China(No.2013AA064202)
文摘First-break picking is the key step in seismic data processing for surveying undulate surfaces, and directly infl uences the precision of near-surface modeling and effects of static corrections. The current first-break auto-picking methods may fail when the signalto-noise ratio（SNR） is low for seismic data in the undulate area, and require labor and time intensive manual picking. This study develops an improved super-virtual interferometry（SVI） method that combines multichannel and multidomain quality control（MMQC） techniques to achieve auto-picked first breaks. The improved SVI method extends the SVI application to enhance the SNR for near-surface scattered waves for the first time, which allows for the SVI method to adapt to first breaks with complex raypaths by linear combination of refractions and near-surface scattered waves. Methods of inverse and multidomain interferometry are developed to effectively enhance the virtual records extracted by the SVI method. The deconvolution filter for waveforms is used to increase resolution and reduce false picks, while the MMQC technique is designed to auto-correct false picks and increase the stability of auto-picking first breaks. The robust technique developed in this study enables stable processing of large 3D seismic datasets. Higher quality results are obtained using the approach presented in this paper to actual field data from the mountain areas in western China, when compared to some commonly used commercial software.
文摘This paper examines the distribution and structure of populations of a medicinal and culinary herb native to Armenia. As one of the first countries to join the Convention on Biological Diversity （CBD）, Armenia has a strong interest in assessing the biodiversity of its native flora and identifying threats to the conservation of these species, particularly those with economic value. Only limited information, however, is available at this time on the genetic biodiversity, population location, structure and size, and conservation status of most of these species. This paper reports the results of five consecutive years of field studies conducted in Armenia to 1） re-locate native populations of the important medicinal and culinary herb, Origanum vulgare L., 2） locate new populations, and 3） assess the growth pattern and dynamics of the populations. The quadrat sampling technique was used to identify key elements that determined population size and abundance. GPS maps of present and past population distributions were created. Particular habitat and environmental factors were identified as crucial to predicting the future conditions of these populations under the impact of global climate change. The research provides a baseline dataset that can be used for the development of further conservation strategies of this important medicinal and culinary species in Armenia.
