分频混色技术在高精度地震解释中的应用

分频解释技术已经越来越多的应用到地震储层预测和油藏描述中,成为地震解释的一种常规技术手段,分频解释技术中分频RGB颜色融合显示方法因其独有的视觉效果也开始受到关注.本文介绍了分频混色技术在高精度地震解释中的应用以及在应用过程中应注意的几点问题,包括优选高精度频谱分解方法、RGB颜色融合技术应用中频率选择的原则等.在此基础上,进一步探讨了分频数据RGB混色方法能有效解决地震沉积学中地层切片精度不满足薄储层预测的问题.RGB颜色融合显示方法能充分发掘高精度地震数据宽频的优势,得到精度更高的储层预测结果.     

关于主题旅游协作网络建设的探讨——以"霞客行"旅游网络为例

旅游协作是旅游系统本身的要素关联,是其客观属性和发展的必然。主题旅游协作是以某一个主题为"红线",将相关旅游要素组织起来形成一个旅游协作组织形式。目前关于旅游协作研究中很少涉及主题旅游协作。文中以"霞客行"旅游网络计划为例,讨论了名人故居旅游地开发中,重视物质性遗产开发,忽略非物质性品牌利用所导致的"大品牌,小产品"的问题,提出了利用虚实结合手法,通过主题品牌运作,构建综合性主题旅游协作网络的构想。旨在通过一个产品网络、一个市场网络、一个学术网络和一个虚拟网络的运作来充分发挥徐霞客品牌的纽带作用,以此推动相关主题旅游地协作单位之间的产品共享和市场共享,从而实现协作体系的效益最大化。     

离子液体调控溶剂热合成TiO2纳米颗粒及紫外-可见光催化降解性能

以钛酸四丁酯(TEOS)、去离子水为原料,离子液体1-丁基-3-甲基四氟硼酸咪唑盐([Bmim]BF4)为表面活性剂,通过溶剂热法制备了锐钛矿相TiO2纳米颗粒。用X-射线衍射仪(XRD)、扫描电镜(SEM)、紫外-可见吸收光谱仪(UV-Vis)对产物的晶相、形貌和光学性能进行表征。为了评估光催化活性,并以甲基橙水溶液为研究对象,在紫外光照射下分析不同照射时间下光降解效率。结果表明,离子液体、去离子水和钛酸四丁酯的体积比为1.3∶1∶1.3时,反应所得到的TiO2具有较高光催化活性,明显优于未添加离子液体的产品,这一结果可归因于其具有较大的比表面积。     

济南市破损山体治理方法优化探讨

破损山体治理在全国范围内缺少成熟可借鉴的经验,该文通过对济南已完成的58座破损山体治理方案的研究,总结出如何选取破损山体最合理的治理方法,为类似地区破损山体治理方法的选取提供了理论依据。     

深海沉积物分类与命名的参数指标和主成分分析

对于南海中部(118个表层沉积物样,水深82~4 420 m)、东部(106个表层沉积物样,水深700~4 508 m)海域的表层沉积物的粒度资料按小于200 m,200~2 000 m,大于2 000 m水深段对水深、平均粒径、黏土含量进行统计分析,结果表明从陆架到陆坡再到深海,平均粒径和黏土含量随水深增加呈非常有规律的变化;把大于2 000 m水深区域再细分为大于2 500 m,大于3 000 m,大于3 500 m,结果表明平均粒径和黏土含量随水深增加几乎无变化,在南海中部水深大于2 000 m海域平均粒径为3.39~3.54μm,黏土平均含量为54.91%~55.47%;在南海东部水深大于2 000 m海域平均粒径为3.25~3.37μm,黏土平均含量为53.91%~54.56%。研究表明2 000 m水深具有划分深海沉积物的指示意义。南海中部水深大于2 000 m海域黏土平均含量为55.19%,平均粒径为3.39μm;在南海东部水深大于2 000 m海域黏土平均含量为53.91%,平均粒径为3.37μm;在南海中部、东部水深大于2 000 m海域平均粒径均小于4μm,黏土平均含量均大于50%,表明深海沉积物粒度特征是平均粒径小于4μm和黏土平均含量大于50%。黏土含量是非生物组分的代表和划分深海沉积物类型的一个独立参数,钙质生物和硅质生物组分是另外两个独立参数。南海东部海域表层沉积物中55种元素总含量为47.50%,硅、铝、钛、钠、钾、磷、钙、镁、铁、锰十种主元素含量为47.03%,其他45种元素含量为0.47%,虽然沉积物来源复杂、成因不同,但沉积物化学主成分并不复杂,主要由前10种主元素和氧元素组成。沉积物主元素铝、钙、硅分别富集于黏土、钙质沉积、硅质沉积中。通过建立沉积物生源组分与碳酸钙、三氧化二铝、二氧化硅的量化关系,可把碳酸钙、生物二氧化硅作为钙质生物和硅质生物的两个替代参数。     

西天山东塔尔别克金矿区安山岩LA-ICP-MS锆石U-Pb年代学、元素地球化学与岩石成因

东塔尔别克金矿区位于西天山吐拉苏盆地内阿希金矿区南侧,构造上属于伊犁-中天山微板块与准噶尔板块之间的博罗科努早古生代岛弧带西段。东塔尔别克矿区出露有一些安山岩,这些岩石具有典型高镁安山岩特征,如高硅（SiO₂=58.94%~63.85%),具有较高的MgO含量(3.75%~6.59%)和Mg^#(58~69)、高的Cr（94.2×10^-6~241×10^-6）、和Ni（54.5×10^-6~126 ×10^-6）含量,以及低的FeO^T/MgO比值。除了Sr含量略微偏低（235×10^-6~696×10^-6）之外,这些岩石基本显示了埃达克岩的地球化学特征：高的Al₂O₃（15.39%~16.65%）,低Y（9.86×10^-6~14.9×10^-6）含量,以及高的Sr/Y比值(23.8~48.1),无Eu异常,Nb、Ta、Ti亏损等。LA-ICP-MS锆石U-Pb测年结果显示安山岩的年龄为347.2±1.6Ma,为早石炭世。安山岩富集Rb、Th、U 等大离子亲石元素,相对亏损Nb、Ta、Ti等高场强元素,轻重稀土元素分馏明显,具有俯冲带岛弧岩浆的特征。东塔尔别克安山岩可能形成于岛弧环境中,并可能由俯冲的晚古生代北天山洋洋壳以及少量上覆沉积物熔融形成,产生的熔体在上升过程中与地幔橄榄岩发生了相互作用. 熔体-地幔相互作用对区内金矿的形成具有重要意义。     

山东喀斯特景观旅游资源及其开发利用

山东广大的石灰岩山地、丘陵区蕴藏着丰富的喀斯特景观旅游资源,其主要形态类型包括: 形态奇特的喀斯特山体、残存的喀斯特剥蚀面、幽深的喀斯特谷地、众多的溶洞、奇异的石灰岩景石(石牙形态)及喀斯特泉群。本文对这些景观形态作了较详细的描述,就其旅游开发利用价值作了评析。文中还对山东喀斯特景观旅游开发的现状及存在的问题作了简要介绍和分析,并针对存在的问题提出了几点建议。     

The Q value variations in the preparing pro－cess of rock rupture

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Bayesian approach to contaminant source characterization in water distribution systems: adaptive sampling framework

Bayesian analysis can yield a probabilistic contaminant source characterization conditioned on available sensor data and accounting for system stochastic processes. This paper is based on a previously proposed Markov chain Monte Carlo (MCMC) approach tailored for water distribution systems and incorporating stochastic water demands. The observations can include those from fixed sensors and, the focus of this paper, mobile sensors. Decision makers, such as utility managers, need not wait until new observations are available from an existing sparse network of fixed sensors. This paper addresses a key research question: where is the best location in the network to gather additional measurements so as to maximize the reduction in the source uncertainty? Although this has been done in groundwater management, it has not been well addressed in water distribution networks. In this study, an adaptive framework is proposed to guide the strategic placement of mobile sensors to complement the fixed sensor network. MCMC is the core component of the proposed adaptive framework, while several other pieces are indispensable: Bayesian preposterior analysis, value of information criterion and the search strategy for identifying an optimal location. Such a framework is demonstrated with an illustrative example, where four candidate sampling locations in the small water distribution network are investigated. Use of different value-of-information criteria reveals that while each may lead to different outcomes, they share some common characteristics. The results demonstrate the potential of Bayesian analysis and the MCMC method for contaminant event management.     

Scale matching of multiscale digital elevation model (DEM) data and the Weather Research and Forecasting (WRF) model: a case study of meteorological simulation in Hong Kong

It is becoming easier to combine geographical data and dynamic models to provide information for problem solving and geographical cognition. However, the scale dependencies of the data, model, and process can confuse the results. This study extends traditional scale research in static geographical patterns to dynamic processes and focuses on the combined scale effect of multiscale geographical data and dynamic models. The capacity for topographical expression under the combined scale effect was investigated by taking multiscale topographical data and meteorological processes in Hong Kong as a case study. A meteorological simulation of the combined scale effect was evaluated against data from Hong Kong Observatory stations. The experiments showed that (1) a digital elevation model (DEM) using 3 arc sec data with a 1 km resolution Weather Research and Forecasting (WRF) model gives better topographical expression and meteorological reproduction in Hong Kong; (2) a fine-scale model is sensitive to the resolution of the DEM data, whereas a coarse-scale model is less sensitive to it; (3) better topographical expression alone does not improve weather process simulation; and (4) uncertainty arising from a scale mismatch between the DEM data and the dynamic model may account for 38 % of the variance in certain meteorological variables (e.g., temperature). This case study gives a clear explanation of the significance and implementation of scale matching for multiscale geographical data and dynamic models.