Recognition of mineralized belts and lithologic patterns in the Silver City-South Mountain region, Idaho, in terms of geochemical reconnaissance data

It seems unreasonable to use one population to fit the distribution of an element, and then to determine a threshold to separate anomalous data from background data in an analysis of geochemical data. Statistically, anomaly, background, and other geological categories may be represented by different component populations overlapping one another. Therefore, anomaly, background, and other geological categories should be distinguished from one another by distributions rather than by thresholds. This paper uses a method of decomposition of mixtures to identify observed distributions of five elements, obtained in a geochemical reconnaissance of the Silver City-South Mountain region, Idaho, into component populations. Observations have been assigned to populations and mapped; finally, these populations have been interpreted leading to recognition of both mineralized belts and lithologic patterns.during the period in which this study was carried out.     

Multivariate discriminant analysis of bioclastic turbidites

A piston core from the southern Blake Basin penetrated nine distinct bioclastic carbonate turbidites separated by pelagic terrigenous clay units. X-ray diffraction analysis of the carbonate mineralogy of the graded, laminated, and homogenous units of the individual turbidite units indicated a general loss of unstable carbonates in the homogenous unit beyond that contained in the lower two units. Univariate and multivariate statistical tests were employed to determine the significance of the changes and to determine if different units of a turbidite sequence could be consistently grouped by statistical methods. Principal components, discriminant function, and cluster analysis were used in the multivariate tests. The graded and laminated units were closely related in mineralogy with little significant differences. The mineralogy of the homogenous units was significantly different than that of the other two units except in one example. Cluster analysis generated five groupings of the samples with the end members consisting of graded and laminated units at one end and homogenous units at the other.     

利用模式识别技术识别致密砂岩含气层

准确识别致密砂岩含气层一直是测井解释工作所面临的一个难题，为准确识别致密砂岩含气储层，根据各种测井的响应特征，运用计算机模式识别技术进行气层综合识别。通过对实际资料处理与气层测试对比，气层识别的准确率可达到91％，储层划分的纵向误差均〈0．450m。     

Identification of a geological region for earthquakes using syntactic pattern recognition of seismograms

A relational database has been developed which permits the storage and retrieval of waveforms, together with essential parameters of events. The capability of the method is tested by applying it to broad-band records from the Geoscope Noumea station (New Caledonia).     

基于粗糙集的Logistic回归模型在矿井突水模式识别中的应用

矿井突水模式识别是一个非正态、非线性和高维数据处理问题,也是二分类问题。使用粗糙集属性约简算法对样本数据降维,建立Logistic回归模型,并利用粒子群算法对模型参数优化。该模型对建模样本突水模式识别正确率为90%,对测试样本突水模式识别正确率为100%,效果好于数据不降维的Logistic回归模型。该模型克服了线性回归分析解决二分类问题存在的不足,为矿井突水模式识别提供了一种新思路、新方法。     

基于模糊聚类分析和模糊模式识别的煤与瓦斯突出预测

煤与瓦斯突出发生的内在机理复杂,突出影响因素与突出事件之间的相关规律具不精确性和模糊性,使得基于经验的传统预测方法和基于数学建模的统计预测方法的应用受到很大限制。提出了采用模糊聚类分析与模糊模式识别方法相结合的煤与瓦斯突出区域预测方法。首先采用模糊聚类分析对煤与瓦斯突出的样本集合进行分类,建立不同程度的模糊模式,然后对待预测样本进行模糊模式识别,以此来预测待测样本的煤与瓦斯突出危险程度。实例验证表明,本法预测可靠。      

Semi-hierarchical correspondence cluster analysis and regional geochemical pattern recognition

Semi-hierarchical correspondence cluster analysis (SHCCA), firstly developed in this paper, extracts the main advantages of correspondence analysis, hierarchical and non-hierarchical cluster analysis, and unifies the R- and Q-mode cluster analysis of large data set. A systemic program to recognize the regional geochemical patterns is built up based on this method. With this program, the complex tasks for data interpretation can be achieved by simple processes, and important geochemical information can be displayed by a single diagram, i.e. the multivariate regional geochemical image. As one of the applied examples of this program, the regional geochemical pattern recognition for a shallow covered area around Tahe in Heilongjiang Province is introduced. The results show that many hidden geochemical patterns related to the lithologies, structures, ore-forming conditions and prospecting targets etc are revealed by the geochemical image, and that the main geochemical patterns are related with certain geological and gravitational patterns. By finding contrasts between geochemical patterns and geological or gravitational patterns, the SHCCA results assist the geological mapping in this area. Geochemical data obtained in Chinese regional geochemical exploration provides useful information regarding geology and minerals, and the method described in this paper provides a new way to examine this type of resource.     

基于模糊模式识别的地下水水质综合评价研究

地下水质量的优劣是影响水资源可利用性的一个重要方面,因此对地下水水质进行合理评价是水资源开发利用、保护的依据。本文根据水质评价的特殊性,就模糊模式识别模型进行了改进,将改进的模糊模式识别模型应用于江阴市地下水水质综合评价,将评价结果与基于熵权法赋权的模糊综合评价及传统模糊综合评价结果进行了对比分析。研究表明:模糊模式识别方法对地下水水质评价问题具有较高的数值稳定性和适用性,模糊模式识别法评价的水质级别趋于平均化、中间化,本文提出的模糊模式识别理论模型应用于典型案例地区地下水水质评价是有效可行的。     

基于粗糙集和模糊模型识别的斜坡危险性区划

为了在斜坡危险性区划中考虑岩体结构的控制作用,将粗糙集和模糊模型识别理论用于区域斜坡岩体结构识别,并结合信息量法对斜坡单元进行空间危险性预测。尝试在指标中考虑深部岩体结构特征和岩层变形构造（断层、岩层曲率）,将该方法应用于巴东新城区库岸斜坡危险性区划。结果表明：巴东新城区滑坡的主要影响因素有坡向和岩层倾向关系、坡角和岩层倾角关系、构造条件,可将斜坡分为3种结构类型。不同结构类型斜坡在危险性评价时各指标的影响程度或权重不同,可将巴东新城区划分为4个危险性等级,与现有滑坡比较验证了结果的合理性。     

模糊聚类实现岩性自动划分

利用测井数据中的自然伽玛、中子、声波和密度测井曲线所蕴含的岩性信息,用模糊聚类算法实现岩性的自动划分。该方法识别准确度高,可靠性强。通过对川西坳陷十八口井的实际应用,此方法在低孔低渗的致密碎屑岩岩性划分中取得了良好的效果。     

On intermediate-term prediction of strong earthquakes in the Himalayan arc region using pattern recognition algorithm M8

Seismicity of the Himalayan arc lying within the limits shown in figure 1 and covering the period 1964 to 1987 was scanned using M8 algorithm with a view to identifying the times of increased probabilities (TIPs) of the occurrence of earthquakes of magnitude greater than or equal to 7·0, during the period 1970 to 1987. In this period, TIPs occupy 18% of the space time considered. One of these precedes the only earthquake in this magnitude range which occurred during the period. Two numerical parameters used in the algorithm, namely the magnitude thresholds, had to be altered for the present study owing to incomplete data. Further monitoring of TIPs is however warranted, both for testing the predictive capability of this algorithm in the Himalayan region and for creating a base for the search of short-term precursors.     

Kohonen neural network and factor analysis based approach to geochemical data pattern recognition

Kohonen neural network (KNN) and factor analysis are applied to regional geochemical pattern recognition for a Pb–Zn–Mo–Ag mining area around Sheduolong in Qinghai Province, China. Prior to factor analysis, the geochemical data are classified by KNN. The results demonstrate that the 4-factor model accounted for 67% of the variation in the data. Factor F1, a Pb–Zn–Mo factor and Factor F4, an Au–Ag factor, correlates with monzonitic granite intrusions and particularly with Pb–Zn–Mo–Ag mineralization within those rocks. Factor F2, an As–Co factor, correlates with metamorphic rocks of paleoproterozoic Baishahe formation. Factor F3, a Bi–Cu factor, correlates with granodiorite intrusions. The factor score maps suggest a revised location of faults and their mineralization significance in coarse geological map. The approach not only effectively interprets the geological significance of the factors, but also reduces the area of exploration targets.     

花岗岩型铀矿铀地球化学场分形奇异值分解研究

介绍了分形奇异值分解方法的原理和实现过程,在桃山花岗岩型铀矿矿集区开展了应用试验,利用该方法将桃山地区1/5万铀地球化学场分解为噪声场、区域地质背景场和局部异常场,在提取隐伏铀矿弱信息方面取得了较好的应用效果。     

非线性回归法求解爆破振动速度衰减公式参数

准确分析场地爆破振动衰减规律是爆破工程设计的基本依据。通过考察爆破振动速度衰减公式中参数的线性回归方法和非线性回归方法,提出了线性残差平方和与非线性（亦即标准残差平方和）的概念,给出了求解衰减公式参数的非线性回归法,并详述了该方法的实现过程。结合工程实例,以标准残差平方和作为爆破振动实测数据与衰减公式拟合值偏差大小的判断依据,分析了线性和非线性回归分析方法得到的萨道夫斯基公式和其修正公式的标准残差平方和。分析结果表明,非线性回归分析方法的准确度明显高于线性回归分析方法;分别采用线性回归和非线性回归方法得到的萨道夫斯基公式和其修正公式的标准残差平方和非常接近,因此,采用两种形式的公式拟合爆破振动衰减规律都是可行的。     

Analysis of multivariate point distributions and chemical grouping of rocks

Large sets of rock compositions can be grouped by the analysis of corresponding point distributions in multidimensional space, where the separate dimensions represent the chemical variables. The point density around each composition is estimated in a small, multivariate, rectangular interval. Establishment of the identity of specimens contained in the interval, and systematic comparison of the point densities surrounding each of them, leads to the recognition of density maxima, which represent the statistical modes of the rock types present in the set. The remaining specimens by the same operations can be assigned to the groups formed. Experimental results are given for two sets, one comprising a wide variety of metasedimentary and metavolcanic rocks from the ore-bearing Skellefte district and adjacent parts of V?sterbotten, Sweden, and the other representing a less variable population of basic rocks from Norrbotten, Sweden. Linear discriminant analysis and existing geological information indicate that the groups obtained are statistically and geologically valid.     

基于动态聚类分析和模糊模式识别法的北京城区汛期降雨时空分布规律研究

以北京城区近十几年汛期50场暴雨过程为样本,利用动态聚类分析和模糊模式识别方法对单站雨型和降雨整体空间分布特征进行了研究,得到北京城区汛期最容易发生的雨型以及时空分布规律。结果表明,北京城区汛期主要发生前单峰型雨,峰值集中且极值雨量大,容易造成内涝积水。发生双峰型雨的次数较少,且极值雨量较小,对内涝积水影响相对较小。     

基于指数平滑法与回归分析相结合的滑坡预测

滑坡时间预报研究是滑坡研究中的一个热门课题。以实际监测数据为基础,把指数平滑法与非线性回归分析法结合起来;以滑坡的变形值和变形速率为判据,对滑坡进行时间失稳的动态跟踪预报。根据某滑坡的实际情况,对部分监测点位移进行了建模和预测,预测结果表明,该方法具有较高的精度,可以应用于实际工程。     

基于经验模态分解的航空重力测量动态误差分离

航空重力测量数据在测量的过程中很容易受到飞机动态运动的影响,飞机动态运动强时,航空重力测量数据的质量也随之降低,虽然经过数字滤波后可以将航空重力异常数据中的大部分噪声去除,但一部分与信号重叠的噪声还是无法被消除.利用经验模态分解对受飞机动态影响较大的一组实测数据进行深化处理.结果表明,在不影响航空重力异常数据分辨率的情况下,该方法很好地消除了由飞机动态运动引起的动态误差,使得航空重力测量的内符合精度由1.43mGal提升到了1.27mGal.     

应用广义S变换频谱分解技术识别松辽盆地三肇凹陷泉头组三-四段的河道砂体

松辽盆地三肇凹陷东部地区泉头组三-四段储层以河道砂岩为主,具有单层厚度薄、横向变化快等特点.本文将基于广义S变换的频谱分解技术应用于厚度为1～5 m的河道砂体的识别,取得了良好的效果.据此编制了研究区的河道砂体预测图,经钻井验证,证明它是对薄层河道砂体有较强识别能力的有效技术.     

鄂尔多斯盆地东部山西组山_2~3亚段砂岩判别图版、砂岩分布规律及成因探讨

勘探实践表明鄂尔多斯盆地东部山西组山32亚段含气性与岩性存在直接关系,石英砂岩储层往往是高产层。因此,寻找石英砂岩储层是该区勘探开发的重点。在岩心刻度测井的基础上,利用测井参数建立了3种类型砂岩的测井判别蛛网图版,并回归了石英相对百分含量与测井参数之间的关系式,利用此关系式对山32亚段砂岩类型进行识别,判识准确率达到80%。同时结合岩石薄片鉴定等资料,绘制了研究区砂岩类型平面分布图。单井结合平面图分析发现研究区存在3个环带状石英砂岩分布区域。从大地构造环境、物源、沉积环境等方面对该区山32亚段石英含量普遍较高和平面环带状分布原因进行了探讨,认为受海退影响的海岸线频繁变迁是形成石英砂岩分布的主要因素。