Application of Spectral Decomposition to Detection of Fracture-Cavity Carbonate Reservoir Beds in the Tahe Oiifieid, Tarim Basin, NW China

Ordovician fracture-cavity carbonate reservoir beds are the major type of producing formations in the Tahe oilfield, Tarim Basin. The seismic responses of these beds clearly changes depending on the different distance of the fracture-cavity reservoir bed from the top of the section. The seismic reflection becomes weak or is absent when the fracture-cavity reservoir beds are less than 20 ms below the top Ordovician. The effect on top Ordovician reflection became weaker with deeper burial of fracture-cavity reservoir beds but the developed deep fracture-cavity reservoir beds caused stronger reflection in the interior of the Ordovician. This interior reflection can be divided into strong long-axis, irregular and bead string reflections, and was present 80 ms below the top Ordovician. Aimed at understanding reflection characteristics, the spectral decomposition technique, which uses frequency to ＂tune-in＂ bed thickness, was used to predict Ordovician fracture-cavity carbonate formations in the Tahe oilfield. Through finely adjusting the processing parameters of spectral decomposition, it was found that the slice at 30 Hz of the tuned data cube can best represent reservoir bed development. Two large N-S-trending strong reflection belts in the mid-western part of the study area along wells TK440- TK427-TK417B and in the eastern part along wells TK404-TK409 were observed distinctly on the 30 Hz slice and 4-D time-frequency data cube carving. A small N-S trending reflection belt in the southern part along wells T403-TK446B was also clearly identified. The predicted reservoir bed development area coincides with the fracture-cavities connection area confirmed by drilling pressure testing results. Deep karst cavities occur basically in three reservoir bed-development belts identified by the Ordovician interior strong reflection. Spectral decomposition proved to be a useful technique in identifying fracture-cavity reservoir beds.     

C1相干算法及其在三维地震资料处理解释中的应用

C1相干算法是计算每道的横测线和相邻纵测线的互相关，依据相干值来判断地层和岩性的横向不均匀性。根据互相关原理，提出了相干体算法中二维和三维C1算法的内容及其具体实现。通过对实际三维地震资料的处理，结合已知地质资料，证明C1相干技术在三维地震资料的断层解释方面有着明显的效果。     

方差体技术在地震勘探中的应用

三维地震数据体反映了地下一个规则网格的反射情况。当遇到地下有断层或某个局部区域地层不连续变化时，一些地震道的反射特征就会与附近地震道出现差异而导致地震首局部的不连续性。三维方差体技术就是求取三维数据体所有样点的方差值来反映这种不连续性信息。通过该技术在济宁2号井某采区的实际应用，可看出，方差体技术在三维地震信息的自动拾取以及提高地震资料解释成果精度等方面有明显优势，对断层、陷落柱有良好的自动识别能力。     

Development of Geological Data Warehouse

Data warehouse (DW), a new technology invented in 1990s, is more useful for integrating and analyzing massive data than traditional database. Its application in geology field can be divided into 3 phrases: 1992-1996, commercial data warehouse (CDW) appeared; 1996-1999, geological data warehouse (GDW) appeared and the geologists or geographers realized the importance of DW and began the studies on it, but the practical DW still followed the framework of DB; 2000 to present, geological data warehouse grows, and the theory of geo-spatial data warehouse (GSDW) has been developed but the research in geological area is still deficient except that in geography. Although some developments of GDW have been made, its core still follows the CDW-organizing data by time and brings about 3 problems: difficult to integrate the geological data, for the data feature more space than time; hard to store the massive data in fifferent levels due to the same reason; hardly support the spatial analysis if the data are organized by time as CDW does. So the GDW should be redesigned by organizing data by scale in order to store mass data in different levels and synthesize the data in different granularities, and choosing space control points to replace the former time control points so as to integrate different types of data by the method of storing one type data as one layer and then to superpose the layers. In addition, data cube, a wide used technology in CDW, will be no use in GDW, for the causality among the geological data is not so obvious as commercial data, as the data are the mixed result of many complex rules, and their analysis needs the special geological methods and software; on the other hand, data cube for mass and complex geo-data will devour too much store space to be practical. On this point, the main purpose of GDW may be fit for data integration unlike CDW for data analysis.     

预警地震在地震预测中的意义

对新疆1970-2002年地震资料以不同范围、不同震级进行全时空扫描。结果表明，新疆台网监测能力较好地区绝大多数6级以上地震前地震活动关联图较为清晰。提出了预警地震的概念，认为预警地震在短临预报方面有一定的作用。     

Research relevance, 'knowledge transfer' and the geographies of CASE studentship collaboration

The Co-operative Awards in Science and Engineering (CASE) studentship programme of the UK Research Councils provide one example of wider efforts internationally to encourage so-called 'knowledge transfer' and thereby harness publicly supported university research more closely to the goals of national competitiveness, regional economic development and local regeneration. In this paper we describe the implications of how the various UK research councils have interpreted the objectives and beneficiaries of 'knowledge transfer', both for the relative opportunities available to human and physical geographers for collaboration through CASE and for the sorts of values that their research must serve. Then, we draw on unpublished data from the Economic and Social Research Council (ESRC) to explore the geographies of CASE studentship allocation and participation. The broad regional and institutional patterns of participation we describe have important implications for ongoing debates in the UK about research selectivity and the role of the university as an engine of local development, while the striking disciplinary patterns of CASE participation, and in particular the overwhelming success of geographers in this competitive programme, provide an opportunity to reassess claims about whether and for whom geographical research is relevant.     

Site characterization model using least‐square support vector machine and relevance vector machine based on corrected SPT data (Nc)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N_c), N values have been corrected (N_c) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three‐dimensional site characterization model, the function N_c=N_c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N_c value, is to be approximated in which N_c value at any half‐space point in Bangalore can be determined. The first algorithm uses least‐square support vector machine (LSSVM), which is related to a ridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel‐based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright © 2009 John Wiley & Sons, Ltd.     

高光谱影像概率分类向量机分类方法研究

从分析基于支持向量机和相关向量机的高光谱影像分类方法的优势和不足出发,将基于概率分类向量机的方法用于高光谱影像分类试验。在贝叶斯理论框架下,概率分类向量机为基函数权值引入截断Gauss先验概率分布,使得不同类别的基函数权值具有不同符号的先验分布,并利用EM算法进行参数推断,得到足够稀疏的概率模型,弥补了相关向量机选取错误类别的样本作为相关向量的不足,从而有效地提高了模型的分类精度和稳定性。OMIS和PHI影像分类试验表明,概率分类向量机能够很好地应用在高光谱影像分类。     

应用数字航道航标信息提高航标测绘效率

通过研究"数字航道"动态监测平台中航标的各项信息与航标测绘数据的关联性,实现航标数据共享,优化现阶段航道维护性中航标测绘的工作方式和流程,从而实现利用数字航道航标信息提升航道测绘工作效率和质量,降低航道维护测量成本。     

Cartographic Design and the Space–Time Cube

This paper reports on the results of an empirical evaluation that aimed to define the effectiveness and efficiency of different visual variables in depicting the Space–Time Cube’s (STC) content. Existing STC applications demonstrate that the most used visual variables are size and colour hue. Less is known, however, about their usability metrics. The research sets design criteria for STC contents, such as space–time paths, based on the cartographic design theory. The visual variables colour hue, colour value, colour saturation, size and orientation have been applied in two different use case studies. Besides, to support the three-dimensional visual environment, depth cues such as shading and transparency were considered too. User tests have been executed based on real-world problems with particular attention for the visualization strategy and data complexity. The outcomes revealed the most efficient and effective visual variables to represent data of various complexities in the STC.