再论矿床模型及分类

本文在综合前人资料的基础上概述了矿床模型的概念、研究现状、分类及其相互关系。矿床模型研究在８０年代掀起了高潮，在世界范围内，有关矿床模型的专著和文章大量出版及在各种地学刊物上刊登。矿床模型是描述一组矿床本质属性的系统有序的信息，是对整个矿床系统的简化、抽象和类比。因此，将一个完整的矿床系统分为特征描述，成因机制，找矿标志和经济评价四部分，由此分为四种模型亚类：描述性模型，成因模型，找矿模型和地质经济模型。这四种模型有交叉、重复，后面的模型是建立在前面模型基础之上的，如成因模型是建立在对矿床及其控矿条件等精确描述之上的模型，地质经济模型则建立在前面三种模型的基础之上。     

地磁场模型的计算和评述

评述了计算地磁场区域模型的各种数学方法,如:利用多项式方法可以计算地磁场的Taylor多项式模型和Legendre多项式模型,利用球冠谐和分析方法可以计算出磁场的冠谐模型。本文指出了建立区域模型各种方法的优缺点,指出球冠谐和分析方法是计算地磁场三维模型的好方法。     

大牛地气田无土相钻井液流变模式优选

大牛地气田无土相钻井液实例计算表明,赫巴模式的相关系数最大,残差平方和最小,其次是卡森模式、幂律模式,最差的是宾汉模式,建议优先选用赫巴模式。     

Recognizing Correlated Patterns from Remotely Sensed Images: A New Learning Rule Based on Spin Glass Theory

Classification of remotely sensed images is a rich research field wherein techniques from conventional statistics to recent developments such as Artificial Neural Network, Fuzzy logic etc. has wide applications. Conventionally remotely sensed image classification referred to pixel classification based on broad categories such as vegetation and water bodies. With the availability of high-resolution imageries, shape analysis of macro structures contained in images becomes an important and difficult task. Although conventional statistical pattern recognition techniques give a reasonable result, Artificial neural network methods seem to be giving better results. In this paper, we give a survey of feed-forward neural network used for shape classification and a Hopfield model with an improved learning rule, for a typical shape analysis problem.     

路基沉降预测的Usher模型应用研究

基于线性或近似线性加载情况下路基沉降过程和Usher曲线,将广泛用于经济和资源预测的Usher模型应用于路基沉降预测。对Usher模型微分方程式的分析表明,目前用于沉降预测的Logistic模型和Gompertz模型是Usher模型的两种简化形式,但Usher模型对于实际情况具有更强的适应性。阐述了Usher模型参数的计算方法,并结合某工程实例进行了计算分析,对比结果说明Usher模型用于沉降预测的效果较好,且比Logistic模型和Gompertz模型具有更高的预测精度,可供工程应用参考。     

Discrete-element, individual-based and agent-based models: Tools for interdisciplinary enquiry in geography?

Discrete-element, individual-based and agent-based modelling techniques represent the interactions of individuals or entities with one another and their environments by sets of computational rules. These methods are now being used in geophysics, ecology, zoology, and increasingly in the social sciences. A characteristic is that the “agents” are embedded in an environment with which they interact, so that joint evolution of physical, ecological and socio-economic systems can be studied; this makes them of interest in integrated geographical investigation. Of particular interest is the fact that they allow the study of macro-scale emergent behaviour generated by multiple individual actions. Discrete techniques have the potential to create integrated models that cross disciplines. Similar computational methods can be employed to control the spatial search process, deal with irregular or changing boundaries, and to track the evolution of systems where preservation of heterogeneity across space and time is important. The complex series of feedbacks between the different types of system can thus be modelled within a single computational framework. Humans modelled in this way as “agents” can allow the collective effect of many interacting individuals to generate emergent structures at the community scale. The structural characteristics of their social and natural environments will influence their behaviour, while at the same time constituting emergent consequences of their actions. The principal challenge of the latter is to find those sets of rules that represent the beliefs and desires of real human agents, accurately reflecting the cultural context, while allowing us to explore the social and economic limitations of agents to take action. This paper reviews and illustrates discrete methods applicable to a range of geographical enquiries, and with particular reference to individual- and agent-based methods, assesses the rich diversity of approaches that must be combined to take full advantage of their potential to explore interactions of social and environmental processes.     

基于遗传算法的新安江模型日模拟参数优选研究

在概念性水文模型的参数率定中,目前还没有一个传统优化方法能够提供保证足够高效和稳定性的算法。为了克服传统优化方法中局部收敛性的缺点,近年来利用遗传算法通过计算机准确稳定地进行概念性水文模型的参数优选的尝试得到越来越多的重视和发展。目前优选水文模型待定参数,大多是从次洪模型的方面去讨论,有关日模拟模型的遗传算法参数优选讨论的较少。本文系统分析了基于遗传算法的新安江模型日模拟参数的自动优选,同时针对遗传算法在模型参数众多的情况下时间效率低下问题,通过利用新安江模型参数分层原理与模型参数敏感性分析对优选结果影响,提出一套简化的日模型参数遗传算法优选方案。经过流域模拟检验,该优选方案可行,运行效率高,可以作为类似模型遗传算法参数率定快速、有效的方案。     

滑坡空间预测数学模型的对比及其应用

滑坡灾害空间预测经历了从定性-半定量-定量、从确定性-非确定性-概率论的发展过程,其中预测模型的建立、预测方法的选取是滑坡空间预测的核心过程,关系到预测结果的最终确定.讨论了信息量模型、信息-物元模型、信息-神经网络模型的预测流程和关键技术问题,将这3种非确定性数学模型运用于万州安乐寺古滑坡区的滑坡危险性预测中,并对3种模型的预测结果进行了对比分析,指出3种预测数学模型的优劣及其应用中需注意的问题,对比研究表明3种模型均不失为滑坡空间预测中较为有效的数学模型.     

Conditioning Channel Meanders to Well Observations

Assessment of uncertainty in the performance of fluvial reservoirs often requires the ability to generate realizations of channel sands that are conditional to well observations. For channels with low sinuosity this problem has been effectively solved. When the sinuosity is large, however, the standard stochastic models for fluvial reservoirs are not valid, because the deviation of the channel from a principal direction line is multivalued. In this paper, I show how the method of randomized maximum likelihood can be used to generate conditional realizations of channels with large sinuosity. In one example, a Gaussian random field model is used to generate an unconditional realization of a channel with large sinuosity, and this realization is then conditioned to well observations. Channels generated in the second approach are less realistic, but may be sufficient for modeling reservoir connectivity in a realistic way. In the second example, an unconditional realization of a channel is generated by a complex geologic model with random forcing. It is then adjusted in a meaningful way to honor well observations. The key feature in the solution is the use of channel direction instead of channel deviation as the characteristic random function describing the geometry of the channel.     

分布式水文模型构建理论与方法述评

回顾了分布式水文模型的发展历程,分析总结了分布式水文模型的构建理论与方法,并对其关键内核——“物理基础”的含义做了深入而新颖的分析。分析了两类当前比较活跃的模型——分布式物理模型与分布式概念性模型中存在的问题及发展前景,并探讨了综合二者之长的具有物理基础的松散型分布式水文模型的构建思路,以及学者们期待中的基于确定性与随机性耦合的分布式水文模型。     

河流—地下水水流模型研究进展

收集前人研究成果,归纳河流—地下水水流模型的解析模型和数值模型,分析河流—地下水水流模型的模拟中影响最敏感的因素,讨论河流污染质入渗到含水层后对含水介质渗透性能的影响,河流—地下水模型最主要的问题在于河流参数的求取和河流的处理,分析河流—地下水水流模型研究存在的问题。     

论矿床成矿模式

成矿模式是对矿床赋存的地质环境、内外部特征、控矿因素、矿化的时空演化规律、矿化标志、成矿物质来源、成因机理和找矿标志的高度综合描述和解释,将复杂多变的成矿作用和地质现象上升为成矿学的地质理论,并用文字、图表予以表达,使人们对同类或一组相似矿床的成矿特征有一个完整的概念,从整体上深化对矿床的认识。按成矿单元的差异和勘查要求,将成矿模式分为区域的、矿床的成矿模式和找矿模型三部分。并列出了建立各类模式(型)的具体内容。     

Grade and Tonnage Model of Contact Metasomatic Copper Deposit in China

INTRODUCTIONSystematic exploration theory is an important aspect ofquantitative prediction and exploration assessment of m ineralresources.Recently,the three- stage quantitative evaluation ofmineral resources (China Mineral Information ResearchInstitute,1996 ;Zhao,1995 ) is widely carried out in the West.The three- stage prediction and evaluation includes:1findingpracticable prospect area on the basis of analyzing m etallogenicgeological setting,2 establishing grade- tonnage model oftar…     

关于找矿模型的探讨

矿床类型是建立各类矿床模型的地质前提,矿床模型的应用方向是建立模型的关键,经验模型与理论模型交叉与融合是建立矿床模型的核心.这3条是矿床模型研究中必须坚持的原则,也是建立找矿模型的重要原则.它基本明确了找矿模型的定位和建设方向.所谓找矿模型,不管其成熟度如何,均以经验模型与理论模型的各类信息的兼收并蓄为基础,以找矿为目...     

基于EMD组合模型的径流多尺度预测

受全球气候变化与人类活动影响,径流序列愈发呈现出非稳态与非线性特征,为降低由此而引发的预报误差,充分发挥不同模型对提高径流预测精度的优势,针对传统径流预报模型的单一性,以干旱区典型内陆河玛纳斯河为例,采用经验模态分解(EMD)提取径流序列中具有物理含义的信号,得到不同时间尺度的多个固有模态函数(IMF)及1个趋势项,利...     

An SMP critical state model for methane hydrate‐bearing sands

Mechanical properties of methane hydrate‐bearing soils are complex. Their behavior undergoes a significant change when hydrates dissociate and become methane gas. On the other hand, methane hydrates are ice‐like compounds and, depending on the hydrate accumulation habits and the degree of hydrate saturation, may cement soil particles into stronger and stiffer soils. A new constitutive model is proposed that is capable of capturing essential characteristics of hydrate‐bearing soils. The core of the model includes the spatial mobilized plane concept; a transformed stress, t_ij; the critical state; and the subloading framework. The proposed model gives soil responses due to stress changes or hydrate saturation changes or both. The performance of the model has been found satisfactory, over a range of hydrate saturation and confining pressures, using triaxial test data from laboratory‐synthesized samples and from field samples extracted from Nankai Trough, Japan. Copyright © 2015 John Wiley & Sons, Ltd.     

资源定量评价发展方向展望

未来的资源定量评价希望能够评估未发现矿产资源的量、价值并对其进行定位预测, 以能够表达矿产资源的经济潜力和不确定性.近年来金属价格的长期下跌提出了对更大型的矿床的需求.敏感度分析表明了减少评价中不确定性和风险的最有效途径是降低有关吨位估计因素的不确定性.到目前为止, 在评价中所有可能造成误差的因素中, 那些与吨位估计误差有关的因素是最重要的.鉴于吨位模型的绝对重要地位以及矿床模型是吨位最有效的预测手段, 正确地选择矿床模型是控制误差最重要的途径.地表大部分地区被大面积裸露的岩石和沉积物所覆盖.由于很多出露地表的矿床已经被发现, 人们开始把注意力转向盖层下面岩石可能显露的矿化信息上.这些区域的资源评价必需依靠对其周边地区的外推、地下覆盖岩石新的地质填图或者通过在其他成功勘探区获得的经验进行类推.盖层对评价的不确定性以及评价的方法与程序都具有深远的影响, 因为地下地质现象的不可见性和地球物理方法所获得的是一种被削弱了的信息.许多早期的评价方法都是基于从那些出露地表的矿床中总结出的地球化学和地球物理变量之间的关系而进行的, 而现在我们同样需要研究基于地下隐伏矿床的勘探经验.矿床模型在资源定量评价中的重要地位基于以下两个原因: (1) 大多数矿床类型具有明显不同的品位和吨位分布; (2) 不同的矿床类型出现在不同的地质背景中, 而这种背景可从地质图中进行区分.在综合利用地质、矿产、地球物理和地球化学等地学信息进行资源评价及矿床勘探中, 矿床模型起着至关重要的作用.品位和吨位模型以及定量描述、经济和矿床密度模型的发展将有利于减少这些新的评价的不确定性.      

Comparison of machine learning models for gully erosion susceptibility mapping

Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory,especially in the Northern provinces.A number of studies have been recently undertaken to study this process and to predict it over space and ultimately,in a broader national effort,to limit its negative effects on local communities.We focused on the Bastam watershed where 9.3% of its surface is currently affected by gullying.Machine learning algorithms are currently under the magnifying glass across the geomorphological community for their high predictive ability.However,unlike the bivariate statistical models,their structure does not provide intuitive and quantifiable measures of environmental preconditioning factors.To cope with such weakness,we interpret preconditioning causes on the basis of a bivariate approach namely,Index of Entropy.And,we performed the susceptibility mapping procedure by testing three extensions of a decision tree model namely,Alternating Decision Tree(ADTree),Naive-Bayes tree(NBTree),and Logistic Model Tree(LMT).We dichotomized the gully information over space into gully presence/absence conditions,which we further explored in their calibration and validation stages.Being the presence/absence information and associated factors identical,the resulting differences are only due to the algorithmic structures of the three models we chose.Such differences are not significant in terms of performances;in fact,the three models produce outstanding predictive AUC measures(ADTree=0.922;NBTree=0.939;LMT=0.944).However,the associated mapping results depict very different patterns where only the LMT is associated with reasonable susceptibility patterns.This is a strong indication of what model combines best performance and mapping for any natural hazard-oriented application.     

土体非线弹性-塑性本构模型

把本质上属于亚弹性本构模型,在岩土工程界广为应用的Duncan-Chang模型与服从Drucker-PragerMohr-Column屈服准则的弹塑性本构模型相结合,推出了非线弹性-塑性的组合本构模型,以克服经典的弹塑性模型不能考虑岩土材料在塑性屈服前的非线性行为以及一般的Duncan-Chang模型不适用于应力水平接近于屈服或破坏状态等缺点。所建议的本构模型简单实用,能较好地综合利用工程地质勘察资料和常规的土工试验数据。针对实际边坡具体地层条件的分析表明,该模型及其非线性析算法的正确性和可行性,而且在岩土工程方面具有广泛的实际应用价值。     

计算区段控制浓度的合理定量化模型研究

对污染物实施总量控制已经成为我国防止水环境恶化、实现水资源可持续利用的主要战略手段之一。本文就总量控制工作进行了理论探讨，从理论上提出了控制平均浓度和最大浓度两种情况下的排污等效模型。同时对计算区段控制浓度的确定进行了定量化模型研究。该模型简便易操作、实用性强，具有一定的理论意义和实用价值。