Appraisal of fracture sampling methods and a new workflow to characterise heterogeneous fracture networks at outcrop

Characterising fractures at outcrop for use as analogues to fractured reservoirs can use several methods. Four important fracture data collection methods are linear scanline sampling, areal sampling, window sampling and circular scanline sampling. In regions of homogeneous fracture networks these methods are adequate to characterise fracture patterns for use as outcrop analogues, however where fractures are heterogeneous, it is more difficult to characterise fracture networks and a different approach is needed.We develop a workflow for fracture data collection in a region of heterogeneous fractures in a fold and thrust belt, which we believe has applicability to a wide variety of fracture networks in different tectonic settings. We use an augmented circular scanline method, along with areal sampling to collect a range of fracture attribute data, including orientation, length, aperture, spatial distribution and intensity. This augmented circular scanline method more than halves the time taken for data collection, provides accurate, unbiased data that is representative of local fracture network attributes and involves data collection of a wider range of fracture attributes than other sampling techniques alone.     

地震多参数神经网络储层油气预测中的参数优化

在利用多参数进行储层油气预测时,并不是使用的特征越多越好,最佳特征的维数取决于实际问题的预测效果。这里运用聚类分析法优选地震特征参数,将距离较远或相似系数低的特征参数聚为一类,用来对未知样本进行地震储层预测。利用优选后的参数进行神经网络储层油气预测,在实际应用时取得了较好的效果。     

地震多属性聚类分析煤层中岩浆侵入影响范围

在淮北杨柳矿区,层状或脉状侵入的岩浆岩导致主采煤层呈现较人范嘲的吞蚀、烧变、焦化、变溥现象,Ⅲ常规地震时间剖面及顺层层拉平切片上难于确定其分布范同。为了精细确定主采煤层巾岩浆侵入的影响范田．基于煤层反射波振幅、波形、能量的同一性及差异性特征,利用优化后的地震多属性尤监督神经网络聚类分析技术对其进行分析。解释结果表明,3煤层未受到岩浆侵入,而10煤层岩浆侵入比较明显,其在成果图上呈现出犬范围的黄色团块状及脉状特征。与实际钻孔揭露资料对比,利用地震多属性聚类分析技术圈定的岩浆岩分布范嗣符合率达78％,具有较高准确度。     

密井网区井震结合进行沉积微相研究及储层预测方法探讨——以大庆杏树岗油田杏56区为例

随着中国油气田开发程度的逐步加深,有效预测井间砂体的分布已成为高效开采与提高采收率的核心问题。文中以大庆杏树岗油田杏56区块为例,尝试利用井、震有机结合的方法进行精细沉积微相展布的研究,对进入特高含水阶段的油田进行井间砂体的预测。在密测网地震层位追踪的前提下提取多种地震属性,以反距离加权平均法提取井点属性,并采用聚类方法对提取的井点地震属性和井点储层参数进行多元统计相关性分析,以确定聚类分析中使用的地震信息,进而建立多元一次方程,描述敏感地震信息与储层参数的桥梁,以便用井、震信息综合预测井间储层参数的变化,由此编制出目的层段的沉积微相平面展布图,并结合生产动态资料进行验证。其成果在实际生产中得到较好的验证。     

Space-time seismicity and earthquake swarms: Certain observations along the slow-spreading mid-Indian Ocean ridges

The slow spreading mid-Indian Ocean ridge system containing the Carlsberg, Central and Southwest Indian ridges is seismically very active. In the present study, a detailed analysis has been carried out of the data of earthquake sources along different ridge segments in order to investigate the spatial and temporal clustering patterns and to evaluate crustal processes related to the swarm occurrences along these ridges. The spatial and temporal clustering pattern of the recent earthquakes (1980–1990) pertaining to nine major spreading segments and eight fracture zones suggests that the events cluster in greater proportion along the spreading segments than along the fracture zones. We performed a systematic search of earthquake catalogue during the period 1964–1990 by examining the spatio-temporal hypocentral clusters in order to identify the swarm occurrences along these ridges. The search included eighteen prominent sequences, of which, thirteen were earthquake swarms. Except two, all other swarms were found to be occurring mainly on the spreading segments. The maximum magnitude observed in these swarms is m_b = 5.4 and have many events predominantly showing normal faulting mechanisms. The spatial disposition and temporal activity of the events in swarms is much similar to the foreshock-mainshock-aftershock sequences observed along the spreading rift valley zones. These characteristics help us to support that swarms along the slow spreading mid-Indian Ocean ridges are the result of extensional tectonic activity, leading to the development of the median valley topography, a mechanism similar to that proposed by Bergman and Solomon (1990) for the Mid-Atlantic Ridge.     

Influence of structural position on fracture networks in the Torridon Group,Achnashellach fold and thrust belt,NW Scotland

In fold-and-thrust belts rocks undergo deformation as fold geometries evolve. Deformation may be accommodated by brittle fracturing, which can vary depending on structural position. We use 2D forward modelling and 3D restorations to determine strain distributions throughout folds of the Achnashellach Culmination, Moine Thrust Belt, NW Scotland. Fracture data is taken from the Torridon Group; a thick, coarse grained fluviatile sandstone deposited during the Proterozoic. Modelling infers a correlation between strain and simple curvature; we use simple curvature to infer how structural position and strain control fracture attribute variations in a fold and thrust belt.In high curvature regions, such as forelimbs, fracture intensities are high and fractures are short and oriented parallel to fold hinges. In low curvature regions fractures have variable intensities and are longer. Fracture orientations in these regions are scattered and vary over short distances. These variations do not relate to strain; data suggests lithology may influence fracturing. The strain history of fold structures also influences fracturing; structures with longer deformation histories exhibit consistent fracture attributes due to moderate-high strain during folding, despite present day low curvature. This is in contrast to younger folds with similar curvatures but shorter deformation histories. We suggest in high strain regions fracturing is influenced by structural controls, whereas in low strain regions lithology becomes more important in influencing fracturing.     

上海市地震滑坡的预测研究

本文选用八个工程地质类比因素,根据灰色聚类分析与模糊聚类分析预测了上海地区的地震滑坡,并用毕肖甫条分法与有限单元法对不稳定地区作了重点验证。     

An enhanced stochastic optimization in fracture network modelling conditional on seismic events

This paper presents an approach to modelling fracture networks in hot dry rock geothermal reservoirs. A detailed understanding of the fracture network within a geothermal reservoir is critically important for assessments of reservoir potential and optimal production design. One important step in fracture network modelling is to estimate the fracture density and the fracture geometries, particularly the size and orientation of fractures. As fracture networks in these reservoirs can never be directly observed there is significant uncertainty about their true nature and the only feasible approach to modelling is a stochastic one. We propose a global optimization approach using simulated annealing which is an extension of our previous work. The fracture model consists of a number of individual fractures represented by ellipses passing through the micro-seismic points detected during the fracture stimulation process, i.e. the fracture model is conditioned on the seismic points. The distances of the seismic points from fitted fracture planes (ellipses) are, therefore, important in assessing the goodness-of-fit of the model. Our aims in the proposed approach are to formulate an appropriate objective function for the optimal fitting of a set of fracture planes to the micro-seismic data and to derive an efficient modification scheme to update the model parameters. The proposed objective function consists of three components: orthogonal projection distances of the seismic points from the nearest fitted fractures, the amount of fracturing (fitted fracture areas) and the volumes of the convex hull of the associated points of fitted fractures. The functions used in the model update scheme allow the model to achieve an acceptable fit to the points and to converge to acceptable fitted fracture sizes. These functions include two groups of proposals: one for updating fracture parameters and the other for determining the size of the fracture network. To increase the efficiency of the optimization, a spatial clustering approach, the Distance-Directional Transform, was developed to generate parameters for newly proposed fractures. A simulated dataset was used as an example to evaluate our approach and we compared the results to those derived using our previously published algorithm on a real dataset from the Habanero geothermal field in the Cooper Basin, South Australia. In a real application, such as the Habanero dataset, it is difficult to determine definitively which algorithm performs better due to the many uncertainties but the number of association points, the number of final fractures and the error are three important factors that quantify the effectiveness of our algorithm.     

基于蚁群聚类算法的岩石边坡稳定性分析

由于岩石边坡影响因素众多且关系复杂,不能用简单的方法进行分析和判断。在工程类比的基础上,一般采用聚类的方法。但由于边坡工程问题环境的复杂性,岩石边坡稳定分析的聚类问题是一个复杂的模糊、随机优化问题,采用传统方法难免带来很多局限性。为了更好地解决这类问题,首次把蚁群聚类算法这种新近提出的仿生聚类算法引入岩石边坡工程领域,以解决其稳定分析问题,提出一种分析岩石边坡稳定问题的新方法。该方法在分析岩石边坡工程实例资料的基础上,采用蚁群聚类算法,以工程类比的思想判断岩石边坡的稳定状态。工程应用证明,该算法可以自动把岩石边坡分成几种类似的状态,判断准确率较高、计算速度较快,是一种比较实用的岩石边坡稳定分析方法,值得在岩石边坡分析领域推广应用。     

High-Frequency Sequence Stratigraphy Using Syntactic Methods and Clustering Applied to the Upper Limestone Coal Group (Pendleian, E1) of the Kincardine Basin, United Kingdom

We define a distance between sedimentary successions to compare their dissimilarity formally. Distance definition is based on attributed syntactic representation. One-dimensional successions can be represented by a string of lithofacies symbols sequentially or vertically. Each symbol can also have a vector of attributes that can provide other information on lithofacies such as thickness. The distance of any two successions is then defined consisting of its syntactic and attribute subdistances. Syntactic distance measures difference of vertical lithofacies change between two successions and attribute distance measures difference of thickness of corresponding lithofacies. Clustering is used to test validity of distance definition and its potential application to analysis of cycle-dominated sedimentary successions. Example is from the Namurian-A succession in Kincardine basin, central Scotland. There are 56 cycles in intervals of about 300 m each in two boreholes. Recognition of intermediate cycles depends on correctly determining of types of these short cycles and their vertical stacking pattern. Intermediate cycles have better potential in high-resolution stratal correlation regionally. Syntactic clustering results show that 56 short cycles can be classified into four groups with distinctive geological interpretation, which further helps reveal hierarchical cyclic architecture of the whole succession.     

http://www.sciencedirect.com/science/article/pii/S1674987111001277

A numerical model is developed for investigating the evolution of fracture permeability in a coupled fracture-matrix system in the presence of fracture-skin with simultaneous colloidal and bacterial tr...     

聚类方法在电气石颜色成因研究中的应用

天然电气石颜色多种多样,颜色成因非常复杂。为了更好了解它的颜色成因,采用统计学中的聚类方法对其颜色成因进行了分类。该分类方法以Matlab软件为工作平台,从测试数据(电子探针分析结果)中选出对电气石颜色形成起重要作用的氧化物,如TiO2,FeO,Fe2O3,MnO作为聚类分析的特征变量。以这些变量作为距离聚类分析的基础,对所研究各种颜色的电气石进行聚类。通过聚类分析研究,把电气石颜色成因的结果与其它测试方法的结果进行对比,证实本聚类方法真实可靠。     

核概率距离聚类方法及应用

研究聚类分析新方法一直是统计学和机器学习研究领域普遍关注的课题。针对概率距离聚类算法不能解决非线性可分聚类问题的缺欠,笔者应用核函数理论将该模型拓展成为一种能够解决非线性可分聚类问题的统计模型,称为核概率距离聚类分析模型。研制出一种应用新模型进行遥感图像非监督分类研究的实施策略和可行算法;在GDAL遥感图像数据输入输出函数库基础上,用VC++语言开发了遥感图像核概率距离聚类分析算法程序;用ERDAS软件提供的一幅7波段491像素×440像素大小的TM图像进行新方法分类应用实验研究。对比了新模型和其原版本的TM遥感图像非监督分类效果,结果表明新模型的非监督分类效果优于原有的分类模型。     

利用地震P波确定煤层瓦斯富集带的分布

查明煤层瓦斯富集区域,对可能的瓦斯突出点进行预报,是当前煤矿生产中亟待解决的重要课题。利用地震P波对裂缝性地层所表现出的方位各向异性特征,根据地震属性随方位角变化可以预测裂隙发育方向和密度的基本原理,应用多种地震P波方位属性预测裂隙发育带。通过对淮南张集煤矿西三采区三维地震P波资料的处理,获得6个方位地震数据体,从中提取多种与煤层和围岩裂隙相关的地震属性,并计算出裂隙的发育方向和密度,为确定瓦斯富集带的分布提供了一种新的途径。      

Fuzzy Clustering with Spatial Correction and Its Application to Geometallurgical Domaining

This paper describes a proposed method for clustering attributes on the basis of their spatial variability and the uncertainty of cluster membership. The method is applied to geometallurgical domaining in mining applications. The main objective of geometallurgical clustering is to ensure consistent feed to a processing plant by minimising transitions between different types of feed coming from different domains (clusters). For this purpose, clusters should contain not only similar geometallurgical characteristics but also be located in as few contiguous and compact spatial locations as possible so as to maximise the homogeneity of ore delivered to the plant. Most existing clustering methods applied to geometallurgy have two problems. Firstly, they are unable to differentiate subsets of attributes at the cluster level and therefore cluster membership can only be assigned on the basis of exactly identical attributes, which may not be the case in practice. Secondly, as they do not take account of the spatial relationships they can produce clusters which may be spatially dispersed and/or overlapped. In the work described in this paper a new clustering method is introduced that integrates three distinct steps to ensure quality clustering. In the first step, fuzzy membership information is used to minimise compactness and maximise separation. In the second step, the best subsets of attributes are defined and applied for domaining purposes. These two steps are iterated to convergence. In the final step a graph-based labelling method, which takes spatial constraints into account, is used to produce the final clusters. Three examples are presented to illustrate the application of the proposed method. These examples demonstrate that the proposed method can reveal useful relationships among geometallurgical attributes within a clear and compact spatial structure. The resulting clusters can be used directly in mine planning to optimise the ore feed to be delivered to the processing plant.     

探讨基于CitusDB的地质资料集群和大数据架构

地质资料是地质工作形成的重要成果资料,具有可被重复开发利用、能够长期提供服务的功能。然而,因地质资料的分散式管理,使得地质资料信息存储分散,“孤岛”式服务的现象普遍存在,缺乏资料信息共享、综合利用的机制和手段,制约着地质资料信息潜在价值的有效发挥。地质资料信息服务集群化旨在通过信息领域前沿技术,对地质资料进行集成集群和深度开发,将分散、孤立的地质资料进行分布式汇集,全方位多角度解读、展现、挖掘地质资料信息,充分发挥地质资料服务于经济社会发展的作用。长期的地质调查工作,已经形成了多专业、数据格式多样的海量地质资料,信息服务的集群化必将面临地质大数据相关的技术问题。介绍了地质资料信息服务集群化模式,分析了CitusDB软件的分布式大数据运行机理,探讨了基于CitusDB软件的地质资料集群和大数据服务架构,可为地质大数据与信息服务提供一定的参考。     

模糊聚类分析在地下工程地质环境质量评价中的应用

城市工程地质环境质量评价方法主要有积分值法、指数模型法、敏感因子模型法、基于层次分析法的模糊综合评价法、和灰色聚类评价法。鉴于各评价因素数值空间分布的不连贯性和地质环境特性的不确定性,本文讨论模糊聚类分析法在于地下空间开发有关的地质环境质量评价中的应用。     

基于K均值动态聚类分析的地球物理测井岩性分类方法

在地球物理测井数据处理与解释中,岩性识别是地层评价、油藏描述等方面的一项重要内容.利用计算机自动进行岩性识别已成为测井解释发展的重要方向、人们研究和关注的内容.聚类分析是数据挖掘中的一个重要研究领域,是一种数据划分或分组处理的重要手段和方法.K均值算法是聚类算法中主要算法之一,它是一种基于划分的聚类算法.依据不同岩性在常规测井资料中的不同响应,根据K均值动态聚类方法的原理,结合其它资料,对井中的岩性进行分类,从而达到了区分和识别钻孔不同岩性的目的.     

Two-dimensional geostatistical modeling and prediction of the fracture system in the Albala Granitic Pluton, SW Iberian Massif, Spain

We use a fracture index distribution method of geostatistical modelling and prediction to characterize quantitatively the fracture system in two-dimensions (2D) in the Mina Ratones area, located in the Albalá Granitic Pluton (SW Iberian Massif). The fracture index (FI) is a quantitative estimate of the fracture density in discrete domains. To validate the results of geostatistical modeling a detailed structural map of the area was also made on a scale of 1:1000. The resulting grids, expressed as pixel-maps, describe the continuous value of the FI in 2D for the whole Mina Ratones area. Based on the modelled distribution of the FI and their correlation with mapped faults, we distinguish two structural domains in the studied area: elongated bands of fracture zones with high FI values and romboidal blocks located between them with low FI values. The separation between both domains is gradual. Though a threshold value of the FI that separate both structural domains is not clearly defined, the fracture zones generally present FI>1 and the individualized blocks FI<0.50. As a consequence, the obtained grid of the FI permits the quantitative structural classification of the granitic massif in 2D and understanding fault zone architecture in the Mina Ratones area.