基于不同测井曲线参数集的支持向量机岩性识别对比

对测井曲线提取的不同参数值,进行支持向量机(support vector machines,SVM)岩性识别对比,找出适合于岩性识别的测井参数集。利用取心段岩心和测井资料,依据M-N值法、曲线重叠法和测井曲线特征值法等3种常用的岩性识别方法,提取能够用于岩性识别的测井曲线参数值,再利用支持向量机进行岩性识别,将识别结果进行对比,按照误差最小原则,找出适合于岩性识别的测井参数集。结果显示,M-N值法、曲线重叠法和测井曲线特征值法3种不同的测井参数集在岩性识别时,测井曲线特征值法和重叠法误差最小,可优先作为识别的基础数据。      

基于RCGA的PPC模型在化探异常识别与提取中的应用

为了进行地球化学异常的识别与提取,针对化探数据的特点,本文提出了一种将高维降维技术——投影寻踪分类(PPC)模型与实数编码遗传算法(RCGA)相结合的计算方法,分析了运用RCGA-PPC模型进行化探异常识别与提取的关键技术问题,并在MATLAB环境下开发了该方法的软件应用模块。以云南个旧地区水系沉积物地球化学数据为例,选取区域内Sn、Cu、Pb、Zn、As、Cd等主要成矿元素及与成矿关系密切的9种元素作为计算变量,利用RCGA-PPC模型对其进行处理和异常识别。研究表明:RCGAPPC模型中最佳投影值较高的地区与该区域实际矿床(点)吻合情况较好。该模型对化探异常的识别能力较强,是一种有效的化探多元素综合异常识别与提取方法。     

基于统计识别模型的遥感蚀变信息提取

遥感数据具有离散性、有限性及非线性关系的数学特征.在专题纹理信息提取分析基础上,以异常区灰度值和矿区控矿构造信息为特征值,利用统计学原理,建立统计识别模型.利用统计识别模型对未知区的特征向量进行识别分类,并应用于吉林东部小西南岔多元成矿靶区预测及矿区附近找矿评价工作中,把提取的蚀变信息与矿山工程地质知识相结合,经野外实地检查与部分探矿工程验证,结果与实际相吻合,获得较好的铜、金矿化显示.     

基于归一化特征值的重磁数据边界识别方法及其在西藏古堆地热勘探中的应用

基于重磁数据的地质体边界识别是地球物理数据解释的重要内容。随着重磁梯度张量测量技术的不断发展,基于梯度张量数据圈定地质体构造边界位置的方法也在不断发展。本文定义一种基于梯度张量特征值的归一化边界识别滤波器,可同时进行不同深度目标体的边界位置圈定。为验证本文方法的有效性,将建立方法应用于合成的重磁数据中,相比于传统边界识别滤波器,本文滤波器具有更高的水平分辨率和精度,并且在正负叠加异常的试验中,可有效地避免虚假边界的产生。最后,将归一化特征值边界识别滤波器应用于西藏古堆地热田的地质构造解释,结果表明,基于特征值的边界圈定方法能够更准确地显示地质构造的边界位置,发现更多地质体构造细节特征。     

滑坡前兆突变异常识别方法

将滑坡位移观测值时间序列视为非平稳随机过程, 采用建立系统的同态模型的方法提取短期异常 , 并给出了异常识别准则、有序度计算公式; 用一阶差分进行高通滤波的方法提取临滑异常并进行预测; 根据异常时刻组成的灾变日期集用灰色灾变模型进行预测。     

化探异常定量评价及重点异常区验证——以山西省阳高县孙仁堡探区为例

通过对研究区地球化学特征参数、地球化学异常特征值和综合地球化学异常指标的计算,得出了4个地球化学参数及2个地球化学指标:剔除比率、变异系数、浓集比率、矿化系数、单元素地球化学异常指标及综合地球化学异常指标,用于定量评价化探异常,确定主要成矿元素,圈定异常区,并对主要异常区进行了有效识别,进一步缩小了有利勘探靶区。     

地球化学异常识别的两种机器学习算法之比较

在Sklearn的Python语言代码基础上,开发了基于孤独森林和一类支持向量机的多元地球化学异常识别方法程序。选择吉林省和龙地区为实验区,从1∶5万水系沉积物资料中提取地球化学异常。把实验区已知矿点的空间分布位置作为"地真"数据,绘制两种机器学习算法的ROC曲线并计算AUC值,用来对比两种方法的多元地球化学异常识别效果。研究结果表明:两种机器学习算法都能够有效识别多元地球化学异常,所提取的多元地球化学异常与已知矿点具有显著的空间关联性;孤独森林算法在数据处理耗时和多元地球化学异常识别效果方面略优于一类支持向量机。     

勘查地球化学数据挖掘与弱异常识别

我国积累的大量高质量、多元素、多尺度的地球化学数据,为矿产勘查与环境评价提供了有效的数据支撑。如何对这些数据进行二次开发和再利用,提取有价值的地球化学异常信息并带动找矿突破,是缓解当前矿产资源短缺的重要途径之一。在覆盖区和深部的找矿实践中,由于矿体埋深和覆盖层的影响,往往在表生介质中形成弱小的地球化学异常,识别和评价弱小地球化学异常是当前勘查地球化学数据处理的重要方向之一。本文围绕地球化学异常信息的提取和评价,主要从以下几个方面讨论了相关的国内外研究进展和发展趋势:勘查地球化学数据处理与异常识别方法和模型,勘查地球化学数据闭合效应的影响及其解决方案,基于大数据和机器学习的勘查地球化学数据处理以及弱小地球化学异常的识别和评价。研究发现,在地质环境的约束下,基于大数据思维和机器学习相结合的方法,注重地球化学空间分布模式与已发现矿床的相关关系,同时使用所有地球化学变量能有效刻画具有非线性特征的地球化学空间分布模式,可识别出传统方法无法识别的异常,为开展地球化学空间模式识别与异常提取提供了新的途径。     

用ASTER数据进行不同类型矿床蚀变异常提取研究

文章在利用多光谱ASTER数据进行不同矿床蚀变异常提取的地质和波谱前提的基础上，对东天山斑岩型Cu矿床、镁铁质岩型Cu-Ni矿床和矽卡岩型Pb-Zn矿床的羟基ASTER蚀变异常提取方法进行了研究；对于铁染异常，利用ASTER数据可提取的只有黄钾铁矾异常。对黄山东Cu-Ni矿及沙泉子Pb-Zn矿的蚀变分带现象进行了初步研究，其结果有助于区分矿床类型。此外还利用多光谱ASTER数据研究了识别某些矿物的可能性。     

基于反双曲正切的位场边界识别技术

通过分析倾斜角概念,提出利用反双曲正切函数特性对归一化的垂向导数进行变换处理,来识别重磁异常中地质体边界和提取地质体分布、断裂构造平面展布特征等信息。理论模型和实际资料对比分析表明,利用该方法识别重磁异常边界具有较好的效果和较高的分辨能力,能够获取丰富的地质信息,对识别地质体边界、划分大地构造单元、确定断裂带和地质构造走向等具有一定的意义。     

Application of singularity mapping technique to identify local anomalies using stream sediment geochemical data,a case study from Gangdese,Tibet, western China

Identifying geochemical anomalies from background is a fundamental task in exploration geochemistry. The Gangdese mineral district in western China has complex geochemical surface expression due to complex geological background and was chosen as a study area for recognition of the spatial distribution of geochemical elements and separating anomalies from background using stream sediment geochemical data. The results illustrate that weak anomalies are hidden within the strong variance of background and are not well identified by means of inverse distance weighted; neither are they clearly identified by the C–A method if this method is applied to the whole study area. On the other hand, singularity values provide new information that complements use of original concentration values and can quantify the properties of enrichment and depletion caused by mineralization. In general, producing maps of singularities can help to identify relatively weak metal concentration anomalies in complex geological regions. Application of singularity mapping technique in Gangdese district shows local anomalies of Cu are not only directly associated with known deposits in the central part of the study area, but also with E–W and N–E oriented faults in the north of the study area. Both types of anomalies should be further investigated for undiscovered Cu mineral deposits.     

砂岩型铀矿氡及其子体测量异常特征

氡及其子体测量用于寻找砂岩型铀矿床上能够形成清晰的异常,但氡及其子体测量方法较多且各具有不同的特点。总结几种常用的氡及其子体测量方法在砂岩型铀矿上的异常特征,并进行比较分析,结果表明铀矿体所在部位大都具有明显的负异常特征,而矿体的头、尾部多呈正异常,其中累积测量比瞬时测量的异常特征更加明显,对应钻孔的位置更好。     

A spatial analysis method for geochemical anomaly separation

One purpose of using statistical methods in exploration geochemistry is to assist exploration geologists in separating anomalies from background. This always involves two types of negatively associated errors of misclassification: type I errors occur when samples with background levels are rejected as background; and type II errors occur when samples with anomalous values are accepted as background. A new spatial statistical approach is proposed to minimize errors of total misclassification using a moving average technique with variable window radius. This method has been applied for geochemical anomaly enhancement and recognition as demonstrated by a case study of Au and Au-associated data for 698 stream sediment samples in the Iskut River area, northwestern British Columbia. Similar results were obtained using the fractal concentration-area method on the same data. By employing spatial information in the analysis, the process of selecting anomalies becomes less subjective than in more traditional approaches.     

Lithospheric magnetic anomalies in the territory of Siberia (from measurements by the CHAMP satellite)

The position of lithospheric magnetic anomalies, detected in total magnetic intensity and the vertical component of the magnetic field, has been determined for Siberia using data from the CHAMP satellite. The paper describes the technique for the satellite data processing and the ways of recognition of regional lithospheric magnetic anomalies from satellite-measured values of the total geomagnetic field, which are obtained from several sources (external and internal with respect to the Earth’s surface). Maps of magnetic-field anomalies of different scales have been constructed for several regions of Siberia depending on the method of areal averaging. The possible geologic and physical nature of the magnetic anomalies and their relationship with deep-seated crustal structures are considered. Preliminary interpretation of the magnetic-field maps shows that the anomalies are connected with the present-day large geologic and geophysical elements of the basement. The features of the lithospheric magnetic field, as a parameter reflecting the present position of tectonic structures and their physical properties, can be used for their contouring in combination with other geological and geophysical methods.     

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.      

放射性方法在DZ地区探测天然气藏有效性的研究

本文介绍了ＤＺ地区应用氡管法、α径迹法、地面γ能谱法及水中铀含量测量等放射性方法探测天然气藏的依据和效果。根据放射性测量资料，圈出了ＤＺ地区油气放射性异常（带）。对比结果表明：这些异常分布在地震勘探圈定出的ＤＺ鼻状隆起上，后者被钻探结果证实为含天然气的构造，有力地说明放射性方法探测天然气藏的有效性。最后，根据放射性异常分布特征和地质资料，总结出断鼻天然气藏的放射性异常模式。     

地磁异常数据处理技术在低纬度地区的应用研究——以柬埔寨王国Mesam金矿为例北大核心CSCD

柬埔寨王国位于低纬度地区,地质勘查程度较低,地面高精度磁测技术能够快速获取磁异常信息,进行找矿评价。在低纬度地区磁化方向主要以水平磁化为主,磁性体产生的磁异常以负磁异常为主。本文通过对柬埔寨王国Mesam金矿磁测数据进行倒相180°、化赤和低纬度化极处理对比,认为三种处理方法得到的结果都能够完整地反映磁场分布特点,在不能忽略剩磁影响的低纬度地区对实测数据进行低纬度化极后再进行解释更加贴近真实且细节更加丰富。通过对低纬度化极后的磁异常进行水平总梯度模和小波多尺度分解计算等位场异常处理,认为磁异常水平总梯度模计算能够较好地反映深部地质体的边界范围,小波多尺度分解计算能够提取特定深度地质体的空间信息,在该区选取的磁异常处理技术是有效的,为进一步扩大该金矿区远景储量提供了新的思路。     

Separation of a geochemical anomaly from background by fractal and U-statistic methods,a case study: Khooni district,Central Iran

Separation of geochemical anomalies from background are one of the important steps in mineral exploration. The Khooni mineral district (Central Iran) has complex geochemical surface expression due to a complex geological background. This region was chosen as a study area for recognition of the spatial distribution of geochemical elements and separating anomalies from background using stream sediment geochemical data. In the past decades, geochemical anomalies have been identified by means of various methods. Some of these separation methods include: statistical analysis methods, spatial statistical methods and fractal and multi-fractal methods. In this article, two efficient methods, i.e. U-statistics and the fractal concentration-area for separation and detection of anomalous areas of the background were used. The U spatial statistic method is a weighted mean, which considers sampling point positions and their spatial relation in the estimation of anomaly location. Also, fractal and multi-fractal models have also been applied to separate anomalies from background values. In this paper, the concentration–area model (C–A) was suggested to separate the anomaly of background. For this purpose, about 256 stream sediment samples were collected and analyzed. Then anomaly maps of elements were generated based on U spatial statistics and the C-A fractal methods for Au, As and Sb elements. According to obtained results, the U-statistics method performed better than C-A method. Because the comparisons of the known deposits and occurrences against the anomalous area created using thresholds from U-statistics and C-A method show that the spatial U-statistics method hits all of 3 known deposits and occurrences, the C-A fractal method hits 1 and fails 2. In addition, the results showed that these methods with regard to spatial distribution and variability within neighboring samples, in addition to concentration value frequency distributions and correlation coefficients, have more accurate results than the traditional approaches.     

A Study of the Method for the Recognition of Anomalies in Geochemical Hydrocarbon Exploration

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Regional anomalies of hydrocarbon fluid saturation as a new source of data on promising oil and gas deposits in the Caspian shelf

This paper analyzes the ratio of local and regional anomalies of fluid saturation identified in the southern margins of the Eastern European Platform by remote fluid indexation. A characteristic feature of this area is the very low background values in the initial field, i.e., local anomalies reflecting the deposits. Regional anomalies are mainly related to oil and gas accumulation zones. In the Middle Caspian areas studied, the regional field of the fluid saturation index is the background for local anomalies. We made an attempt to justify the hydrocarbon migration and generation zones as anomaly-forming zones of the regional anomalies. The correlation of oil and gas accumulation zones with the regional field anomalies was noted.