Identifying geospatial services across heterogeneous taxonomies

Geospatial services with different functions are assembled together to solve complex problems. Different taxonomies are developed to categorize these services into classes. As differences in granularity and semantics exist among these taxonomies, the identification of services across different taxonomies has become a challenge. In this paper, an approach to identify geospatial services across heterogeneous taxonomies is proposed. Using formal concept analysis, existing heterogeneous taxonomies are decomposed into semantic factors and their various combinations. With these semantic factors, a super taxonomy is established to integrate the original heterogeneous taxonomies. Finally, with the super taxonomy as a cross-referencing system, geospatial services with classes in original taxonomies are identifiable across taxonomies. Experiments in service registries and a social media-based spatial-temporal analysis project are presented to illustrate the effectiveness of this approach.     

断层EDF技术在复杂断块构造研究中的应用

复杂断块构造具有断层复杂,小断层广泛发育,断层识别难度大,储层分布及连通性复杂,地震成像不清、资料品质较差等特征。对于此类问题,常规地震资料无法满足断层解释精度要求。提出了一种新的断层EDF解释性处理技术,将地震资料处理与解释融为一体,以提高资料的信噪比和断层的识别能力。断层EDF解释性处理技术是利用扩散滤波和中值倾角滤波相结合的断层增强滤波方法来提高资料的信噪比,突出断层和地层的接触关系,再在滤波后的地震资料数据体上进行分频处理,选择最佳成像频带,突出识别不同规模的断层。通过在涠洲A油田的应用,取得了良好的效果。     

Laboratory Simulation of the Formation Process of Surface Geochemical Anomalies Applied to Hydrocarbon Exploration

The formation mechanisms and processes of geochemical anomalies used as proxies in surface geochemistry exploration (SGE) have not been well understood. Previous studies cannot realize 3D measurement of microseeping hydrocarbons from reservoirs to the surface, which made it difficult to understand the features and pathways of deep hydrocarbon microseepages. Understanding the processes of hydrocarbon microseepages will contribute to the acceptance and effectiveness of surface geochemistry. Based on a simplified geological model of hydrocarbon microseepages, including hydrocarbon reservoir, direct caprock, overlying strata and Quaternary sediments, this work established a 3D experimental system to simulate the mechanisms and processes of deep hydrocarbon microseepes extending to the surface. The dispersive halos of microseeping hydrocarbons in the subsurface were adequately described by using this 3D experimental system. Results indicate that different migration patterns of hydrocarbons above the point gas source within the simulated caprock and overlying strata can be reflected by the ratio of i-butane to n-butane (i-C4/n-C4), which follow diffusion and infiltration (buoyancy) mechanisms. This is not the case for vertical measurement lines far from the point gas source. A vertical gas flow in the form of a plume was found during hydrocarbon microseepage. For sampling methods, the high-density grid sampling is favorable for delineating prospecting targets. Hydrocarbon infiltration or buoyancy flow occurs in the zones of infiltration clusters, coupling with a diffusion mechanism at the top of the water table and forming surface geochemical anomalies. These results are significant in understanding hydrocarbon microseepage and interpreting SGE data.     

Magnetic Influences of Cement Dust on Soil in Industrial Area and Its Environmental Implications

To monitor environmental implications of cement dust on soil in industrial area, magnetic parameters and mineral compositions were measured by the samples of the cement dust, cement factory dustfall, cement, coal ash, topsoil of green space in the factory and topsoil outside the factory. Results showed that the major magnetic minerals in the samples were magnetite, the magnetic mineral particle size of cement dust, dustfall, cement and coal ash was coarse Multi-Domian (MD) and Pseudo-Single-Domain (PSD). As topsoil of green space in the factory and topsoil outside the factory were polluted by cement dust, their magnetic properties had been obviously changed; the concentration of magnetic minerals elevated and particle size became coarser. The magnetic parameters (χ_fd,χ_ARM/χ,χ_ARM/SIRM) value can reflect the pollution level of the soil, the lower its value was, the more serious soil was polluted. X-ray diffraction results showed that the mineral compositions of the topsoil of green space in the factory and topsoil outside the factory were quartz and calcite, which were the same as cement dust. Magnetic parameters combination characteristics of topsoil can monitor the soil environmental changes in cement industry area.     

Regional debris flow susceptibility analysis based on principal component analysis and self-organizing map: a case study in Southwest China

A method was developed to analyze the susceptibilities of 541 regional basins affected by debris flows at the Wudongde Dam site in southwest China. Determining susceptibility requires information on source material quantity and occurrence frequency. However, the large number of debris flows can hinder the individual field investigation in a each small basin. Factors that may trigger debris flows can be identified using remotely sensed interpretation information. Susceptibility analysis can then be conducted based on these factors. In this study, SPOT5 satellite imagery, digital elevation models (DEM), a lithology distribution map, and rainfall monitoring data were used to identify 12 debris flow trigger factors: basin relief ratio, slope gradient in the initiation zone, drainage density, downslope curvature of the main channel, vegetation coverage, main channel aspect, topographic wetness index, Melton’s ruggedness number, lithology, annual rainfall, form factor, and cross-slope curvature of the transportation zone. Principal component analysis was used to obtain the eight principal components of these factors that contribute to susceptibility results. Then, a self-organizing map method was adopted to analyze the principal components, which resulted in a debris flow susceptibility classification. Field validation of 26 debris flow basins was used to evaluate the errors of the susceptibility classification, as well as assess the causes of such errors. The study found that principle component analysis and self-organizing map methodologies are good predictors of basin susceptibility to debris flows.