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51.
ODP204航次天然气水合物的可能有利储层——浊积层 总被引:3,自引:1,他引:3
为了解岩性在天然气水合物分布中的作用, 利用岩矿鉴定、扫描电镜和能谱法对ODP204航次的 4个站位 10个钻孔共计 115个沉积物样品进行分析, 发现沉积物中矿物成分基本相近, 以粘土矿物为主, 含少量以石英为主的陆源碎屑。样品中含有丰富的硅藻和有孔虫等微体化石, 可形成硅藻粘土—硅藻土、有孔虫硅藻土或凝灰质硅质生物粘土。石英碎屑大多呈棱角状, 粒径小、含量少, 同时, 样品中可见透镜体、团块或旋涡状层状结构以及杂乱堆积的斑杂构造。上述特征表明沉积物为含有大量深海或半深海的浊流沉积物或其夹层。由于钻井岩心中有相当部分的天然气水合物样品分布在上述沉积物中, 推断这些浊流沉积物很可能是ODP204航次天然气水合物的有利储层。 相似文献
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对河北大麻坪宝石级橄榄石物理化学及宝石学特征进行研究后,初步提出矿床成因模式,对于相似地区的碱性玄武岩地区的橄榄石宝石矿床的勘探有指导意义。 相似文献
55.
平差系统的模型误差及其识别方法研究 总被引:2,自引:0,他引:2
论述了模型误差影响参数估值的一些理论问题,指出了随机模型误差和函数模型误差之间的相互作用和转化。为讨论平差系统最优模型的选取,给出了与现有文献将模型误差纳入平差系统的思路不同的一个估计和识别模型误差的理论基础公式,由此导出了相应的实用公式,给出了平差系统模型的优选方法。 相似文献
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Some theory problems affecting parameter estimation are discussed in this paper. Influence and transformation between errors
of stochastic and functional models is pointed out as well. For choosing the best adjustment model, a formula, which is different
from the literatures existing methods, for estimating and identifying the model error, is proposed. On the basis of the proposed
formula, an effective approach of selecting the best model of adjustment system is given.
Project supported by the Open Research Fund Program of the Key Laboratory of Geospace Environment and Geodesy, Ministry of
Education, Wuhan University (No. 905276031-04-10). 相似文献
58.
Trevor Quinn A.-Xing Zhu James E. Burt 《International Journal of Applied Earth Observation and Geoinformation》2005,7(4):324-338
Hydro-ecological modelers often use spatial variation of soil information derived from conventional soil surveys in simulation of hydro-ecological processes over watersheds at mesoscale (10–100 km2). Conventional soil surveys are not designed to provide the same level of spatial detail as terrain and vegetation inputs derived from digital terrain analysis and remote sensing techniques. Soil property layers derived from conventional soil surveys are often incompatible with detailed terrain and remotely sensed data due to their difference in scales. The objective of this research is to examine the effect of scale incompatibility between soil information and the detailed digital terrain data and remotely sensed information by comparing simulations of watershed processes based on the conventional soil map and those simulations based on detailed soil information across different simulation scales. The detailed soil spatial information was derived using a GIS (geographical information system), expert knowledge, and fuzzy logic based predictive mapping approach (Soil Land Inference Model, SoLIM). The Regional Hydro-Ecological Simulation System (RHESSys) is used to simulate two watershed processes: net photosynthesis and stream flow. The difference between simulation based on the conventional soil map and that based on the detailed predictive soil map at a given simulation scale is perceived to be the effect of scale incompatibility between conventional soil data and the rest of the (more detailed) data layers at that scale. Two modeling approaches were taken in this study: the lumped parameter approach and the distributed parameter approach. The results over two small watersheds indicate that the effect does not necessarily always increase or decrease as the simulation scale becomes finer or coarser. For a given watershed there seems to be a fixed scale at which the effect is consistently low for the simulated processes with both the lumped parameter approach and the distributed parameter approach. 相似文献
59.
钉土相互作用的剪滞力理论分析 总被引:6,自引:2,他引:6
在深基坝支护设计中 ,对钉土作用机理存在着许多模糊认识。为此 ,本文在一定假设条件下 ,建立了钉土相互作用的剪滞力模型 ;结合实例分析对模型进行了验证 ,并对钉土相互作用机理进行了分析. 相似文献
60.
This work presents a novel neural network‐based approach to detect structural damage. The proposed approach comprises two steps. The first step, system identification, involves using neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The partial derivatives of the outputs with respect to the inputs of the NSIN, which identifies the system in a certain undamaged or damaged state, have a negligible variation with different system errors. This loosely defined unique property enables these partial derivatives to quantitatively indicate system damage from the model parameters. The second step, structural damage detection, involves using the neural damage detection network (NDDN) to detect the location and extent of the structural damage. The input to the NDDN is taken as the aforementioned partial derivatives of NSIN, and the output of the NDDN identifies the damage level for each member in the structure. Moreover, SDOF and MDOF examples are presented to demonstrate the feasibility of using the proposed method for damage detection of linear structures. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献