内蒙古白音郭勒地区地球化学异常提取方法对比研究

勘查地球化学的基础性问题是如何合理地提取地球化学异常下限,这是影响勘查地球化学在矿产勘查中效果的主要因素。利用SPSS软件,通过含量对数频率直方图,结合偏度、峰度检验法检验元素的含量分布型式,发现研究区的Cu、Ag、Pb、Zn元素不服从正态或对数正态分布,而呈现多峰态、高丛集的多重分形特征。采用传统的统计学方法、85%累计频率法、含量-总量多重分形法提取相关元素地球化学异常,并进行对比研究。研究结果表明,基于元素空间分布及含量分布规律的含量-总量多重分形方法,有效克服了传统方法的局限,比较客观地反映研究区的地球化学异常信息,是研究地球化学异常比较合理的方法。     

区域地球化学异常空间分形结构及其意义——以浙江省诸暨地区区域地球化学数据为例

区域地球化学数据既具有确定性的特征 ,又具有随机性的特征 ,从而地球化学异常的空间分布具有标度不变性的特征 ,即空间分形结构。本文运用元素含量 等值线面积模型、元素含量的周长与面积模型 ,查明区域地球化学异常分形结构 ,初步探讨了其形成机制 ,并讨论了元素含量与等值线面积的空间分形模型用于划分地球化学异常与背景的意义。     

区域地球化学异常空间分形结构及其意义：以浙江省诸暨地区区域地？…

区域地球化学数据既具有确定性的特征,又具有随机性的特征,从而地球化学异常的空间分布具有标度不变性的特征,即空间分形结构。本文运用元素含量－等值线面积模型、元素含量的周长与面积模型,查明区域地球化学异常分形结构,初步探讨了其形成机制,并讨论了元素含量与等值线面积的空间分形模型用于划分地球化学异常与背景的意义。     

区域地球化学异常空间分形结构及其意义--以浙江省诸暨区域地球化学数据为例

区域地球化学数据既具有确定性的特征,又具有随机性的特征,从而地球化学异常的空间分布具有标度不变性的特征,即空间分形结构.本文运用元素含量-等值线面积模型、元素含量的周长与面积模型,查明区域地球化学异常分形结构,初步探讨了其形成机制,并讨论了等值线含量与面积的空间分形模型用于划分地球化学异常与背景的意义.     

分形奇异(特征)值分解方法与地球物理和地球化学异常重建

地球物理和地球化学异常是找矿的重要依据.地球物理和地球化学异常取决于地层、构造在成矿时间上的多样性与空间上排列、叠置的复杂性.地层、构造因素是构造、岩浆、沉积与成矿地球化学等多种动力学过程的综合反映.这些岩石和构造的因素以及动力过程相互渗透和影响决定了最终地质、地球物理与地球化学场.本文提出的在GIS环境下实现的分形奇异值分解(MSVD) 异常重建方法, 不仅可以提取地球物理和地球化学等异常, 而且能够进一步刻画其中的线性和环状构造、细微的局部纹理结构特征.该方法首先对地球物理和地球化学等网格数据进行二维矩阵的奇异值分解, 之后用左特征向量矩阵与右特征向量矩阵的直积构造一个正交完备基.地球物理和地球化学二维数据可以投影到该正交基上, 其投影系数是矩阵的奇异值.在该正交完备空间的某些子空间上对地球物理和地球化学等数据进行滤波.为了选择子空间, 本文定义了上述正交完备基中的能谱密度、能谱半径(或尺度) 与能量测度.在此基础上与空间域及频率域类比, 探讨了能量测度与能谱密度呈现分形(fractal和bifractal) 规律.利用分形关系的间断点, 设计分形奇异值重建算子, 实现对地球物理和地球化学异常的分解.以加拿大NovaScotia南部布格重力异常与As地球化学异常为例, 采用MSVD方法分解Au、Wu -Sn -U等已知矿有关的地球化学异常.发现重建异常能很好地用于解释已知矿点的分布规律.重建的地球化学异常显现了地球化学中的线状和环状异常; 重建的布格重力异常有效勾勒出原图中不易发现的纹理结构, 这些纹理结构可以合理地解释已知矿点在侵入岩体内及其周围的分布规律.应用实例表明, 该方法不仅可以从起因复杂的异常中区分出背景、异常场, 还可以识别代表了成矿源岩、流体、运移通道、赋存空间等异常因素引起的纹理、结构与构造特征.同时实现了GIS环境下交互可视化的MSVD处理与解释系统, 增强了地质异常定量分析的实用性与可操作性.      

分形理论在东天山金矿预测中的应用

地球科学研究的众多事物以及现象都是错综复杂的，表现为不规则性和非线性的特点。如何从这种复杂的特点中找到其中所隐含的规律或某种确定性的量，成为地球科学研究的一个重大难题。对于传统的研究方法来说，只能定性或简单地刻画自然界中广泛存在的无序、混乱、不规则和不光滑的复杂现象，无法进一步对其进行探讨。但是非线性理论和方法的提出，为揭示隐藏于混乱复杂现象中的精细结构以及定量地刻画描述它们，提供了理论方法基础。众多地质学者运用分形理论对成矿元素含量的空间分布、矿床分布的分形特征以及构造分布的分形特征都进行了有益而深入的研究。在前人研究的基础上，文章利用分形理论对东天山地区的金矿资源进行预测。     

广东庞西垌地区地球化学组合异常识别与提取

为了解地球化学元素空间组合分布规律,采用因子泛克里格法构建组合模型用于识别组合地球化学异常,使用分形滤波技术强化弱异常并分离异常与背景.将组合异常模型和分形滤波技术用于钦杭结合带南段庞西垌地区1∶5万水系沉积物地球化学数据进行处理分析,目的在于寻求地球化学致矿异常,寻找未知矿床.研究结果表明,根据组合变量提取出的组合异...     

青海阿尔茨托山地区地球化学（异常）场的多重分形研究

以研究区成矿地质背景为基础，将其划分为4个地球化学区，从多重分形理论出发，应用“元素含量—面积”模型方法，对各区主要成矿元素的地球化学(异常)场进行分析研究。结果表明，由于地质构造背景和化探元素富集的成因机理不同，各区元素地球化学(异常)场具有两种不同的多重分形特征模式：只有两个无标度区的简单多重分形模式和有两个以上无标度区的高丛集多重分形模式，具有相同成因的元素组合具有相似的多重分形特征。在此基础上．探讨了各区元素的成矿富集规律和空间分布特征，进而划分了地球化学背景和异常，经检验对比，证明了该方法的有效性和实用性。     

基于MAPGIS的含量-面积分形法确定元素异常下限及圈定异常区:以湖南阳明山地区为例

地球化学元素的异常下限值确定是地球化学中重要的问题之一,目前还没有一个完善的具有科学依据的计算方法。传统的化探异常下限值计算是以元素含量或元素含量的对数值呈正态分布这一假设为基础的,而事实上地球化学元素含量的空间分布是极其复杂的。研究表明,地球化学景观可能是一个具有低维吸引子的混沌系统,元素的地球化学背景值和异常具有各自独立的幂指数关系,由此导致了一种多重分形分布,可以利用元素的分形分布求出其异常下限。对湖南省阳明山地区的化探水系采样分析数据采用分区的处理方法,根据每个区内数据的分布特征采用分形和传统方法混合应用来确定异常下限,勾绘出Sn元素异常图,与单独采用传统方法相对比收到了良好的异常圈定效果。根据新方法确定的元素异常下限所圈定的异常区与已知矿点高度拟合。     

多维分形理论和地球化学元素分布规律

多维分形模型不仅采用常规的低阶矩统计, 而且采用高阶矩统计对多维分形分布进行度量, 从而能较细致地刻划正常值以及异常值.地球化学元素的正常值往往服从统计学中的大数定量, 即满足正态分布或对数正态分布, 然而异常值会服从分形分布(Preato).介绍了多维分形领域中的最新发展以及在地球化学研究中特别是研究超常元素空间分布和富集规律中的应用.结果表明, 通常的统计方法只对应于多维分形围绕均值周围的局部特征.为了有效地研究异常值的分布和富集规律, 建议采用高阶矩统计方法和多维分形方法, 并给出了两种分析地球化学元素, 并突出异常值贡献的方法.这些方法不仅可应用于研究微量元素的空间分布和富集规律, 而且可以区分地球化学背景与矿化有关的异常值.还介绍了该方法在对加拿大B.C.省西北部Mitchell-Sulphurets地区金铜矿化蚀变带研究中的应用.      

Dimensional Reduction of Pattern-Based Simulation Using Wavelet Analysis

A pattern-based simulation technique using wavelet analysis is proposed for the simulation (wavesim) of categorical and continuous variables. Patterns are extracted by scanning a training image with a template and then storing them in a pattern database. The dimension reduction of patterns in the pattern database is performed by wavelet decomposition at certain scale and the approximate sub-band is used for pattern database classification. The pattern database classification is performed by the k-means clustering algorithm and classes are represented by a class prototype. For the simulation of categorical variables, the conditional cumulative density function (ccdf) for each class is generated based on the frequency of the individual categories at the central node of the template. During the simulation process, the similarity of the conditioning data event with the class prototypes is measured using the L ₂-norm. When simulating categorical variables, the ccdf of the best matched class is used to draw a pattern from a class. When continuous variables are simulated, a random pattern is drawn from the best matched class. Several examples of conditional and unconditional simulation with two- and three- dimensional data sets show that the spatial continuity of geometric features and shapes is well reproduced. A comparative study with the filtersim algorithm shows that the wavesim performs better than filtersim in all examples. A full-field case study at the Olympic Dam base metals deposit, South Australia, simulates the lithological rock-type units as categorical variables. Results show that the proportions of various rock-type units in the hard data are well reproduced when similar to those in the training image; when rock-type proportions between the training image and hard data differ, the results show a compromise between the two.     

Artificial neural network study of observed pattern of scour depth around bridge piers

An artificial neural networks (ANN) model is developed to study the observed pattern of local scour at bridge piers using an FHWA (Federal Highway Administration) data set composed of 380 measurements at 56 bridges in 13 states. Various ANN estimates of observed pier scour depth on different choices of input variables are examined. Reducing the number of variables from 14 to 9 has negligible effect on the coefficient of determination, R², (0.73 vs. 0.72). Further sensitivity analysis indicates that pier scour depth can be estimated using only four variables: pier shape and skew, flow depth and velocity with a coefficient of determination of 0.81, suggesting that inclusion of some variables actually diminishes the quality of ANN predictions of short term observed pattern of scour. The ANN estimates indicate that flow depth and flow velocity make up 66% of the coefficient of determination.     

A new method for the construction and optimization of quadrangular adaptive well pattern

A proper well pattern will have considerable effects on the oil field production, with the ultimate recovery of hydrocarbon enhanced and the water production rate reduced. Comparing with triangular well pattern, quadrangular well pattern has more advantages in some cases and has broader application prospects. However, constructing an optimal quadrangular well pattern is more complicated and has not gain enough research. Facing this situation, a new method of constructing quadrangular adaptive well pattern is proposed in this paper. This quadrangular adaptive well pattern is generated using frontal Delaunay quad-mesh generation method. Boundaries, faults, and existing wells can be constrained and treated as control variables to determine the well spacing, a gradient-based algorithm coupled with reservoir numerical simulator is used to optimize the well pattern. Comparing to conventional regular well pattern, the new well pattern will adjust its shape according to the heterogeneity in different parts of the reservoir, achieving the optimal effect using fewest wells. Two different examples are applied to demonstrate the proposed methodology. The results show that the method proposed can be successfully applied to the construction and optimization of well pattern for large-scale reservoirs and improve the ultimate recovery significantly.     

Mapping soil erodibility from composed data set in Sele River Basin, Italy

Evaluation of soil erodibility is an important task for Mediterranean lands, in which fertility and crop yield are significantly affected by soil erosion. The soil physicochemical parameters affecting soil erodibility are highly variable in space and, as for many other environmental variables, sample measurements are generally not enough for assessing its spatial variability with an acceptable level of uncertainty at the scales of practical interest. This study illustrates the procedure applied for estimating the pattern of soil erodibility across the Sele Basin (Southern Italy), where soil properties have been measured on a limited number of sparse samples. Sampled data were integrated with other sparse data estimated by local regression functions, which relate soil erodibility to auxiliary variables, such as terrain attributes and land system class memberships. Sampled and estimated data were merged in a composed data set to assess the spatial pattern of soil erodibility by ordinary kriging. The proposed approach offers effective spatial predictions, and it is exportable to regions where financial costs for soil sampling are not feasible.     

Fast FILTERSIM Simulation with Score-based Distance

FILTERSIM is a pattern-based multiple-point geostatistical algorithm for modeling both continuous and categorical variables. It first groups all the patterns from a training image into a set of pattern classes using their filter scores. At each simulation location, FILTERSIM identifies the training pattern class closest to the local conditioning data event, then samples a training pattern from that prototype class and pastes it onto the simulation grid. In the original FILTERSIM algorithm, the selection of the closest pattern class is based on the pixel-wise distance between the prototype of each training pattern class and the local conditioning data event. Hence, FILTERSIM is computationally intensive for 3D simulations, especially with a large and pattern-rich training image. In this paper, a novel approach is proposed to accelerate the simulation process by replacing that pixel-wise distance calculation with a filter score comparison, which is the difference between the filter score of local conditioning data event and that of each pattern prototype. This score-based distance calculation significantly reduces the CPU consumption due to the tremendous data dimension reduction. The results show that this new score based-distance calculation can speed up FILTERSIM simulation by a factor up to 10 in 3D applications.     

Consistent seasonal snow cover depth and duration variability over the Western Himalayas (WH)

Precipitation in solid form, i.e., snow, during winter season over the Western Himalayas (WH) leads to the build-up of seasonal snow cover. Seasonal snow cover build-up (snow cover depth and duration) largely depends on atmospheric variables such as temperature, precipitation, radiation, wind, etc. Integrated (combined) influence of atmospheric variables on seasonal snow cover gets reflected in terms of spatial and temporal variability in seasonal snow cover build-up pattern. Hence spatial and temporal variability of seasonal snow cover build-up can serve as a good indicator of climate change in high altitude mountainous regions like the WH. Consistent seasonal snow cover depth and duration, delay days and early melt days of consistent seasonal snow cover at 11 stations spread across different mountain ranges over the WH were analyzed. Mean, maximum and percentiles (25th, 50th, 75th, 90th and 95th) of consistent seasonal snow cover depth and duration show decline over the WH in the recent past 2–3 decades. Consistent seasonal snow cover is found to melt early and snow cover build-up pattern is found to show changes over the WH. Decline in consistent seasonal snow cover depth, duration and changing snow cover build-up pattern over the WH in recent decades indicate that WH has undergone considerable climate change and winter weather patterns are changing in the WH.     

夯管锤的优化设计

论述了夯管锤优化变量的选取和约束条件的建立，并运用计算机仿真技术获得了夯管锤优化目标函数的计算方法，在此基础上运用复形调优法对YH300型夯管锤进行了优化设计，使夯管锤的性能得到显提高。     

Kinetics of dissolution of mechanically comminuted rock-forming oxides and silicates—I. Deformation and dissolution of quartz under laboratory conditions

The extensive evidence on the properties of ground quartz such as grain morphology and adherence and subsurface structural damage shows a consistent pattern, interpretable in terms of the competing processes of fracture and of local plastic deformation.The well-documented pattern of dissolution of ground quartz in aqueous solutions is also consistent. At large undersaturations and constant other environmental variables, the apparent dissolution rate of ground quartz decreases exponentially with the increasing thickness of the equivalent dissolved disturbed layer, and the rate of release of adherent tiny fragments shows roughly the same dependence on the latter. At small undersaturations distribution of solubilities also needs to be considered.     

Numerical classification of geologic patterns characterized by binary variables

An iterative method of adaptive pattern recognition is used to allocate unclassified individuals to an a priori classification. The model is similar in form to a linear discriminant function, but the coefficient vector is determined by iteration. The method can be used with binary data, and with variables whose statistical distributions are not normal; it is therefore a useful technique for geologists.     

风积砂质高浓度胶凝充填材料性能与粉煤灰掺量关系分析

充填材料是决定煤炭充填开采效益、效率、效果的最主要因素。为了掌握风积砂质高浓度胶凝充填材料的性能变化规律,本文以粉煤灰的质量掺入比作为变量,试验研究和理论分析了粉煤灰对该充填材料性能的影响规律。结果表明,粉煤灰的适量添加可以提高充填材料的强度,大掺量导致强度相对降低; 泌水率随着粉煤灰掺量的增大总体上呈减小趋势,较大掺量试样泌水速率相对较低; 分层度随着粉煤灰掺量的增大线性降低; 凝结时间随着粉煤灰掺量增大呈现指数增大; 坍落度总体上随粉煤灰掺量的升高而增大,但大掺量会使其出现相对降低。分析认为,适量粉煤灰的掺入,使风积砂质高浓度胶凝充填材料的颗粒粒度、水分分布和水泥分散均匀,而使材料的强度和输送性能适度改变,但掺量过大会稀释胶结料和改变颗粒相对级配而导致性能下降。