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.     

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.     

Cartographic Symbol Design Considerations for the Space–Time Cube

The cartographic representation of geographic phenomena in the space–time cube comes with special challenges and opportunities when compared with two-dimensional maps. While the added dimension allows the display of attributes that vary with time, it is difficult to display rapidly varying temporal data given the limited display height. In this study, we adapt 2D cyclic point symbols to construct 3D surfaces designed along a helical path for the space–time cube. We demonstrate how these complex?3D helical surfaces can display detailed data, including data reported daily over 100 years and data reported in four-hour intervals over a year. To create the point symbols, each value is plotted along the curve of a helix, with each turn of the helix representing one year or week, respectively. The model is modified by varying the radii from the time axis to all points using the attribute value, in these cases maximum daily temperature and four-hourly ridership, and then creating a triangulated surface from the resulting points. Using techniques common to terrain representation, we apply hue and saturation to the surface based on attribute values, and lightness based on relief shading. Multiple surfaces can be displayed in a space–time cube with a consistent time interval facing the viewer, and the surfaces or viewer perspective can be rotated to display synchronized variations. We see this method as one example of how cartographic design can refine or enhance operations in the space–time cube.     

Bounding Cube:一种无线传感器网络节点三维定位算法

无线传感器网络经常会部署在三维区域内,但目前大部分节点定位方法仅考虑的是二维应用.针对无线传感器网络节点能量有限特点,提出1种三维节点定位算法bounding cube,研究算法的原理和实现方法,并进行仿真分析.仿真结果表明,在100 m×100 m×100 m的三维空间内随机部署400个节点,当已知节点密度>20%,通信半径分别为r=30 m,r=40 m,r=50 m时,相对定位误差均<40%,当已知节点密度>20%、通信半径>30 m时,一次定位比例可以达到100%.该算法的突出特点是方法简单、计算量小.     

新型珊瑚海水混凝土力学性能试验研究

为了解决全珊瑚海水混凝土(coral aggregate seawater concrete,简称CASC)的脆性问题,采用碱式硫酸镁水泥(basic magnesium sulfate cement,简称BMSC)为胶凝材料和剑麻纤维为增韧材料制备了一种新型全珊瑚海水混凝土(NCASC),系统测定了基本力学性能,并与普通硅酸盐水泥制备的CASC、碱式硫酸镁水泥砂石混凝土(basic magnesium sulfate cement concrete,简称BMSCC)、普通砂石混凝土(ordinary portland cement concrete,简称OPC)以及普通轻骨料混凝土(lightweight aggregate concrete,简称LAC)的力学性能进行对比。结果表明:立方体抗压强度(f_(cu),m)在15~35 MPa范围内的NCASC的轴心抗压强度(f_c,m)、劈裂抗拉强度(f_(sp),m)与f_(cu),m之间具有较显著的线性关系;对于f_(cu),m为15~35 MPa的混凝土,相同强度NCASC的f_c,m高于OPC、LAC及BMSCC,其f_c,m与f_(cu),m比值最大,大致在0.85~0.96之间,NCASC的f_(sp),m比OPC和LAC高,但比BMSCC低,且随着强度的提高,OPC与NCASC的f_(sp),m间的差距在增大,而LAC和BMSCC与NCASC的f_(sp),m间的差距在缩小;在强度等级C15~C55的范围中,NCASC和CASC的f_(sp),m、f_c,m与f_(cu),m之间的关系基本可以采用相同的线性回归方程来描述,利用这两个回归线性方程得到对应于标准强度等级的CASC和NCASC的f_(sp),m和f_c,m数据,为CASC力学性能研究与结构设计提供参考依据。     

面向"数字城市"多源数据的空间数据立方体空间度量研究

叙述了面向“数字城市”多源数据的空间数据立方体空间度量的基本定义;描述了空间度量的聚集概念,并结合具体的图例阐述了点状、线状、面状空间度量的聚集过程;解释了空间数据立方体维上钻、维下翻、维层次上钻、维层次下翻的空间度量聚集操作基本原理。     

Complex behaviour of a coal sample in a large scalein situ compression test

Summary A large scalein situ compression test of a laminated coal cube is described. The cube was uniformly loaded by a system of hydraulic jacks supplied simultaneously from one pump. At the same time both load and deformations were controlled. Deformations were measured by 60 longitudinal gauges located at the side surface of the cube in the regular net. Due to the heterogeneity of the rock the readings showed scatter. As a first approximation, the scattered data were fitted to the plane using the least square method. Orientations of the planes were analysed and show permanent relative movement between adjacent lamina indicating complex behaviour of the cube under loading. Detailed analysis of this behaviour indicated that the cube was subjected to both bending and twisting.