实景三维模型在铁路工程勘察设计方面应用愈发广泛,但在模型可视化过程中的失真现象和纹理贴图被倾斜摄影测量外业环境限制问题较为突出,严重制约实景三维模型的实际效果和应用范围。通过将实景三维模型从常用OSGB格式转化为便于编辑的...实景三维模型在铁路工程勘察设计方面应用愈发广泛,但在模型可视化过程中的失真现象和纹理贴图被倾斜摄影测量外业环境限制问题较为突出,严重制约实景三维模型的实际效果和应用范围。通过将实景三维模型从常用OSGB格式转化为便于编辑的OBJ格式,并在其数据框架内新建PBR(Physically Based Rendering)材质,以提升模型整体的真实度,最终在OSG(Open Scene Graph)内完成可视化渲染;过程中提出融合实拍照片优化PBR材质的参数设定和按地物材质特性分类的方法来进一步提升实景三维模型的纹理效果;分析OSG引擎内光照模型,选择最匹配铁路工程实际情况和当天作业条件的光照模型应用,在不改变已有数据结构的基础上,突破倾斜摄影作业环境对实景三维模型最终可视化成果质量的桎梏。该方法在既有铁路工程不同部位的实景三维模型上进行验证,结果表明,该技术可有效提升实景三维模型的可视化效果及表达真实度,具备一定的推广应用价值。展开更多
[Objective] The purpose was to research the distribution characteristics of Tamarix species above-ground biomass of Tarim River＇s middle reaches and to find out best-fit linear-regression model of Tamarix species in ...[Objective] The purpose was to research the distribution characteristics of Tamarix species above-ground biomass of Tarim River＇s middle reaches and to find out best-fit linear-regression model of Tamarix species in this area.[Method] By dint of the most common sampling method PCQ,five samples in the middle reaches of Tarim River were collected.The best-fit linear-regression model of Tamarix species of this area was set up,based on the fieldwork and the model of Evangelista and obtained the distribution rules of Tamarix species of Tarim River＇s middle reaches.[Result] The result indicated that this model fitted for the estimation of aboveground biomass of the study area.According to the distribution rules of aboveground biomass,it was clear that underground water was the major element which decided the distribution of aboveground biomass.[Conclusion] The study provided theoretical basis for the calculation of biomass of Tamarix.展开更多
What are the anomalous seismic reflection bodies at depths of over 6000m？Are they reefs or igneous rock？This is a difficult problem for seismic techniques,but the GMES technique can handle it .The GMES technique is ...What are the anomalous seismic reflection bodies at depths of over 6000m？Are they reefs or igneous rock？This is a difficult problem for seismic techniques,but the GMES technique can handle it .The GMES technique is a joint exploration technique combining gravity,magnetic,electrical,and seismic techniques.The specific procedure is to conduct a 2D interface-constrained CEMP inversion using 2D seismic and log data followed by a property parameter inversion of the anomalous bodics using gravity and seismic data by the stripping technique.We then estimate the physical properties ofthe anomalous bodies,such as density,susceptibility,resistivity,velocity,and etc.to deduce the geological features of the bodies and provide a basis for drilling decisions.The work in the TZ area reported in this paper shows the applicability of the technique.展开更多
Porosity is one of the most important properties of oil and gas reservoirs. The porosity data that come from well log are only available at well points. It is necessary to use other method to estimate reservoir porosi...Porosity is one of the most important properties of oil and gas reservoirs. The porosity data that come from well log are only available at well points. It is necessary to use other method to estimate reservoir porosity.Seismic data contain abundant lithological information. Because there are inherent correlations between reservoir property and seismic data,it is possible to estimate reservoir porosity by using seismic data and attributes.Probabilistic neural network is a powerful tool to extract mathematical relation between two data sets. It has been used to extract the mathematical relation between porosity and seismic attributes. Firstly,a seismic impedance volume is calculated by seismic inversion. Secondly,several appropriate seismic attributes are extracted by using multi-regression analysis. Then a probabilistic neural network model is trained to obtain a mathematical relation between porosity and seismic attributes. Finally,this trained probabilistic neural network model is implemented to calculate a porosity data volume. This methodology could be utilized to find advantageous areas at the early stage of exploration. It is also helpful for the establishment of a reservoir model at the stage of reservoir development.展开更多
The successful estimation of formation pressures （or formation pore gradient） is fundamental and the basis for many engineering works including drilling and oilfield development planning. Common log data are used fo...The successful estimation of formation pressures （or formation pore gradient） is fundamental and the basis for many engineering works including drilling and oilfield development planning. Common log data are used for formation pressure calculation. Modern techniques for pressure prediction have several disadvantages, notably, incorrect account of the downhole nonsteady thermal field and clay mineral composition. We propose a way to overcome listed shortcomings： a technique for thermal field proper account while formation pressure estimation and a petrophysical model, which reflects relationships between clay minerals composition and rock properties, derived from log data.展开更多
文摘实景三维模型在铁路工程勘察设计方面应用愈发广泛,但在模型可视化过程中的失真现象和纹理贴图被倾斜摄影测量外业环境限制问题较为突出,严重制约实景三维模型的实际效果和应用范围。通过将实景三维模型从常用OSGB格式转化为便于编辑的OBJ格式,并在其数据框架内新建PBR(Physically Based Rendering)材质,以提升模型整体的真实度,最终在OSG(Open Scene Graph)内完成可视化渲染;过程中提出融合实拍照片优化PBR材质的参数设定和按地物材质特性分类的方法来进一步提升实景三维模型的纹理效果;分析OSG引擎内光照模型,选择最匹配铁路工程实际情况和当天作业条件的光照模型应用,在不改变已有数据结构的基础上,突破倾斜摄影作业环境对实景三维模型最终可视化成果质量的桎梏。该方法在既有铁路工程不同部位的实景三维模型上进行验证,结果表明,该技术可有效提升实景三维模型的可视化效果及表达真实度,具备一定的推广应用价值。
基金Supported by Sino-German Cooperation Program(PP[2007]3086)~~
文摘[Objective] The purpose was to research the distribution characteristics of Tamarix species above-ground biomass of Tarim River＇s middle reaches and to find out best-fit linear-regression model of Tamarix species in this area.[Method] By dint of the most common sampling method PCQ,five samples in the middle reaches of Tarim River were collected.The best-fit linear-regression model of Tamarix species of this area was set up,based on the fieldwork and the model of Evangelista and obtained the distribution rules of Tamarix species of Tarim River＇s middle reaches.[Result] The result indicated that this model fitted for the estimation of aboveground biomass of the study area.According to the distribution rules of aboveground biomass,it was clear that underground water was the major element which decided the distribution of aboveground biomass.[Conclusion] The study provided theoretical basis for the calculation of biomass of Tamarix.
文摘What are the anomalous seismic reflection bodies at depths of over 6000m？Are they reefs or igneous rock？This is a difficult problem for seismic techniques,but the GMES technique can handle it .The GMES technique is a joint exploration technique combining gravity,magnetic,electrical,and seismic techniques.The specific procedure is to conduct a 2D interface-constrained CEMP inversion using 2D seismic and log data followed by a property parameter inversion of the anomalous bodics using gravity and seismic data by the stripping technique.We then estimate the physical properties ofthe anomalous bodies,such as density,susceptibility,resistivity,velocity,and etc.to deduce the geological features of the bodies and provide a basis for drilling decisions.The work in the TZ area reported in this paper shows the applicability of the technique.
文摘Porosity is one of the most important properties of oil and gas reservoirs. The porosity data that come from well log are only available at well points. It is necessary to use other method to estimate reservoir porosity.Seismic data contain abundant lithological information. Because there are inherent correlations between reservoir property and seismic data,it is possible to estimate reservoir porosity by using seismic data and attributes.Probabilistic neural network is a powerful tool to extract mathematical relation between two data sets. It has been used to extract the mathematical relation between porosity and seismic attributes. Firstly,a seismic impedance volume is calculated by seismic inversion. Secondly,several appropriate seismic attributes are extracted by using multi-regression analysis. Then a probabilistic neural network model is trained to obtain a mathematical relation between porosity and seismic attributes. Finally,this trained probabilistic neural network model is implemented to calculate a porosity data volume. This methodology could be utilized to find advantageous areas at the early stage of exploration. It is also helpful for the establishment of a reservoir model at the stage of reservoir development.
文摘The successful estimation of formation pressures （or formation pore gradient） is fundamental and the basis for many engineering works including drilling and oilfield development planning. Common log data are used for formation pressure calculation. Modern techniques for pressure prediction have several disadvantages, notably, incorrect account of the downhole nonsteady thermal field and clay mineral composition. We propose a way to overcome listed shortcomings： a technique for thermal field proper account while formation pressure estimation and a petrophysical model, which reflects relationships between clay minerals composition and rock properties, derived from log data.
