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1.
《岩土力学》2017,(5):1365-1372
三维地质模型是地质结构、成分、构造和地质数据在三维可视化空间的有效载体。而基于矢量剪切技术的地质切片,可以直接从三维地质体模型上快速提取纵横交错的虚拟地质剖面,直观地显示地下某一位置的地层结构及地质构造的空间形态。但孤立的地质剖面不能很好地表征地质结构、构造及地质现象的空间连续变化。为此,提出了一种基于实时矢量剪切的三维地质体模型的序贯剖面可视分析方法。运用基于多线程的实时矢量剪切技术,分别完成每个虚拟剖面的地质结构、构造和属性特征的布尔运算,生成具有空间拓扑结构和属性特征的可视化地质切片;依次生成整个地质体模型的多组序贯剖面,最终实现对三维地质模型的结构进行连续、动态显示。通过定制界面进行扫描方向、线程、剖面帧数等参数的控制,具有很好的灵活性、可控性和自动化程度,实现了对三维地质模型的实时、多角度序贯剖面的动态扫描,使得地质空间可视化分析更加直观、高效、灵活。 相似文献
2.
三维地质模型精度评估与误差修正问题已成为制约三维地质模拟技术深入发展应用的瓶颈。在综合国内外研究现状与发展趋势的基础上,提出了三维地质结构模型精度评估、误差检测、动态修正的总体研究框架。在模型精度评估方面,提出分别构建三维地质结构模型精度评估的一般理论模型、面向特定地质体的实际操作模型和地质结构构造不确定性的三维空间分布模型的研究思路,指出应重点研究地质实体自身特性、三维地质建模方法对三维地质结构模型精度的影响,解决由一般地质界面的内插误差和特殊地质体的外推误差引起的精度评估问题。在模型误差修正方面,提出基于建模初始数据的模型误差修正方法和基于建模中间结果的模型误差修正方法,在具体实现时,引入“数据 模型的可视化交互技术”。这些研究成果为建立一套完整的三维地质结构模型精度评估与误差修正的理论体系和方法体系奠定了基础,有助于完善复杂地质条件下三维地质模拟的方法与技术。 相似文献
3.
三维地质模型可以直观的展现地下地质情况,对传统地矿行业的转型升级和城市规划建设都具有重要意义。针对复杂地质条件下三维模型的构建,笔者等提出了一种基于多源数据和地质先验知识约束的三维地质建模方法。以成都市为例,基于MapGIS10.0 软件三维地学建模模块,在DEM数据、数字地质图、综合地质剖面图、钻孔数据、物探解译数据、构造纲要图等多源数据,以及地质体展布形态、产状和厚度变化,断层性质、延伸方向、产状变化、对地质体的错切,褶皱类型、形态特征、两翼产状变化等地质先验知识的共同约束下,开展复杂地质条件下三维地质模型构建研究。笔者等详细介绍了复杂地质体三维建模数据源的准备、建模流程与方法、模型的构建与可靠性分析。认为采用分块建模技术可有效降低复杂地质体三维模型构建的难度,提高建模效率,实现模型的无痕拼接,且易于后期模型的修改完善。本次基于多源数据和地质先验知识约束,采用分块建模技术首次构建了成都市三维地质模型。笔者等通过地质先验知识（地质规律）和静态数据（可视化和抽稀钻孔数据）对模型的可靠性进行了分析,其中抽稀钻孔数据分析采用未参与建模的真实钻孔对三维地质模型中地质体埋深和分层厚度进行误差计算,获得地质体埋深误差均值为33.15 m,分层厚度误差均值21.37 m,认为模型的可靠性较高,可为成都市城市规划和重大工程选址提供重要的基础地质数据支撑。 相似文献
4.
三维地质模型可以直观的展现地下地质情况,对传统地矿行业的转型升级和城市规划建设都具有重要意义。针对复杂地质条件下三维模型的构建,笔者等提出了一种基于多源数据和地质先验知识约束的三维地质建模方法。以成都市为例,基于MapGIS10.0 软件三维地学建模模块,在DEM数据、数字地质图、综合地质剖面图、钻孔数据、物探解译数据、构造纲要图等多源数据,以及地质体展布形态、产状和厚度变化,断层性质、延伸方向、产状变化、对地质体的错切,褶皱类型、形态特征、两翼产状变化等地质先验知识的共同约束下,开展复杂地质条件下三维地质模型构建研究。笔者等详细介绍了复杂地质体三维建模数据源的准备、建模流程与方法、模型的构建与可靠性分析。认为采用分块建模技术可有效降低复杂地质体三维模型构建的难度,提高建模效率,实现模型的无痕拼接,且易于后期模型的修改完善。本次基于多源数据和地质先验知识约束,采用分块建模技术首次构建了成都市三维地质模型。笔者等通过地质先验知识（地质规律）和静态数据（可视化和抽稀钻孔数据）对模型的可靠性进行了分析,其中抽稀钻孔数据分析采用未参与建模的真实钻孔对三维地质模型中地质体埋深和分层厚度进行误差计算,获得地质体埋深误差均值为33.15 m,分层厚度误差均值21.37 m,认为模型的可靠性较高,可为成都市城市规划和重大工程选址提供重要的基础地质数据支撑。 相似文献
5.
现有的三维地质模拟技术没有考虑地质空间几何结构场与属性参数场之间的耦合关系,从而限制了计算机模拟结果的真实性和实用性。工程地质空间多场耦合构模问题已成为制约三维地质模拟技术深入发展应用的瓶颈。在综合国内外研究现状与发展趋势的基础上,提出了工程地质空间多场耦合构模的总体研究框架和基本工作流程,给出了研究过程中所遇到的主要科学问题的解决思路或实现方案,并通过实例说明地质体多场耦合模型在三维地质建模及可视化系统中初步实现后的效果。这些研究成果为建立一套完整的地质体多场耦合构模理论体系和方法体系奠定了基础,有助于推动工程地质数字化建模分析技术的深入应用。 相似文献
6.
随着城市地下空间的开发利用,对三维地质结构的掌握成为科学合理开发利用地下空间的基本前提,三维地质模型的创建也得以迅速发展。三维地质结构模型可以直观展示地层空间分布形态,为地下空间资源的科学规划提供基础数据。本次工作首次完成了北京五环城区(750 km~2)的三维地质结构模型创建。建模工作基于研究区广泛分布的数千工程钻孔,通过筛选、标准化钻孔数据,绘制相应标准化地层剖面(107条),创建了钻孔模型,以及北京五环城区地下50 m以浅三维地质结构模型,并完成精度验证。本次建模过程整理了大量工程钻孔数据,综合考虑了冲洪积扇发育区地层互层、相交、尖灭、透镜体等复杂的地质现象,具有代表性,可为类似地质建模工作提供借鉴。此外,北京城区三维地质结构模型直观展示了研究区浅部的地层分布与地层结构,为后续三维属性模型的创建提供了实体框架,亦为区内地下空间资源地质评价提供了数据支撑。 相似文献
7.
支持结构——属性一体化表达的建模方法是三维建模研究的重点和难点之一。已有三维地质建模技术往往存在结构与属性建模过程的割裂，难以实现对地质结构先验知识与属性分析模拟的融合表达。笔者以西咸新区工程地质建模为例，基于多要素精细化探测成果，建立区域统一的地质构造框架模型；在地质构造约束下，充分考虑地质单元特征，精细剖分建模网格，采用随机模拟算法开展属性建模研究，从而实现地质结构约束下的三维属性模型构建。本方法既保留了构造建模对层面的清晰划分,又可以在地层内部更加合理地展现地质属性的空间分布和变化，能够在工程地质勘察和城市地下空间开发等领域得到应用。 相似文献
8.
基于拉丁方抽样及K-S检验的边坡可靠性分析 总被引：1，自引：0，他引：1
边坡稳定性是受复杂因素影响下的多维非线性问题,大多数边坡工程都存在着不确定性。大量试验和工程实践证明,影响边坡状态的因素中有许多具有显著的随机性,参数具有变异性。从概率的角度出发,结合实际工程,对于原始数据采用K-S检验法进行假设验证,确定参数变量的分布类型,克服了人为假设的误差,并分别采用Latin方抽样(LHS)法和Monte Carlo法对参数进行抽样,得到状态函数值,确定安全系数及可靠指标,对比两种抽样方法,基于LHS法模拟次数要少于Monte Carlo法,而且破坏概率的收敛性也优于Monte Carlo法,明显节省了计算时间 相似文献
9.
煤储层三维地质模型的精确性直接影响到后期煤层气开发方案的部署和煤层气井的产量。本文以山西沁水盆地寿阳ST区块为例,基于地质数据、岩心数据、测井数据和地震数据等资料,提出了井震约束条件下煤储层的三维地质建模方法。通过建立构造模型,采用序贯指示模拟方法模拟煤层在三维空间的分布,建立研究区岩相模型。通过序贯高斯模拟方法模拟煤层含气量、孔隙度、渗透率等参数分布规律,建立反映煤层气特征的精细三维属性模型,预测了相关属性参数的空间分布特征。基于地质模型划分了产能潜力区,结合产能数值模拟技术,进行了煤层气井单井产能预测。本文划分的煤层气产能潜力区与产能预测结果,与目前区块内煤层气开发部署和实际产气情况吻合。 相似文献
10.
探讨了洛塔典型岩溶流域在缺乏钻孔资料的情况下,利用系列地质剖面、地质图、DEM等现有资料建立三维地质模型的建模方法及模型的应用。其中地质剖面数据的获取采用了计算机自动提取地形高程、地层界线、地下河位置等信息制图,精确快速。三维建模过程使用Geo SIS三维地质建模软件平台,以超体元实体模型、断层数学模型、褶皱几何模型等进行建模,模型形象逼真。建好的三维模型可以进行任意方向、角度的切割;进行地下漫游、放大、三维观察地层与断层之间的关系;进行揭层三维显示及单层三维显示; 进行任意形状的开挖显示。从建模的角度考虑,该方法对仅有地形图、水文地质图和极少量钻孔资料的情况下建立三维地质模型,具有普遍推广的意义。 相似文献
11.
Hou Weisheng Cui Chanjie Yang Liang Yang Qiaochu Clarke Keith 《Mathematical Geosciences》2019,51(1):29-51
In each step of geological modeling, errors have an impact on measurements and workflow processes and, so, have consequences that challenge accurate three-dimensional geological modeling. In the context of classical error theory, for now, only spatial positional error is considered, acknowledging that temporal, attribute, and ontological errors—and many others—are part of the complete error budget. Existing methods usually assumed that a single error distribution (Gaussian) exists across all kinds of spatial data. Yet, across, and even within, different kinds of raw data (such as borehole logs, user-defined geological sections, and geological maps), different types of positional error distributions may exist. Most statistical methods make a priori assumptions about error distributions that impact their explanatory power. Consequently, analyzing errors in multi-source and conflated data for geological modeling remains a grand challenge in geological modeling. In this study, a novel approach is presented regarding the analysis of one-dimensional multiple errors in the raw data used for model geological structures. The analysis is based on the relationship between spatial error distributions and different geological attributes. By assuming that the contact points of a geological subsurface are decided by the geological attributes related to both sides of the subsurface, this assumption means that the spatial error of geological contacts can be transferred into specific probabilities of all the related geological attributes at each three-dimensional point, which is termed the “geological attribute probability”. Both a normal distribution and a continuous uniform distribution were transferred into geological attribute probabilities, allowing different kinds of spatial error distributions to be summed directly after the transformation. On cross-points with multiple raw data with errors that follow different kinds of distributions, an entropy-based weight was given to each type of data to calculate the final probabilities. The weighting value at each point in space is decided by the related geological attribute probabilities. In a test application that accounted for the best estimates of geological contacts, the experimental results showed the following: (1) for line segments, the band shape of geological attribute probabilities matched that of existing error models; and (2) the geological attribute probabilities directly show the error distribution and are an effective way of describing multiple error distributions among the input data.
相似文献12.
岩土工程信息化迫切需要加强大数据集成共享和多专业协同合作,BIM技术在工程建设领域的成功经验给我们以启示,可将BIM技术应用于岩土工程信息化建设,但是当前存在的主要问题是地质模型与BIM模型数据标准不统一。为了解决这个问题,提出了地质模型采用BIM数据标准IFC的思路。采用IFC实体扩展及属性集扩展模式,建立了面向三维地质模型的扩展模型IFC-3DGeoMdl。利用已有的IFC对象类型,派生相应的地质物理实体以及地质空间结构实体,给出地质物理实体的空间表达形式;利用IFC中已有的关系类,定义地质物理实体与空间结构实体的关系;进而,基于IFC中的属性表达方式,实现了地质对象的地层信息与物理力学参数等属性的扩展;最后,给出了创建该模型的具体实现过程,并利用实例验证了该模型的实际应用效果。结果表明,采用该模型,可有效实现岩土工程地质模型与BIM结构模型的集成,从而为深化岩土工程的结构设计、施工等提供有效的地质模型信息。 相似文献
13.
成矿过程是一个复杂的物理化学过程,由于地质自身的不确定性、原始数据采集和处理的不当、预测方法中经验参数的不确定性等多重因素的叠加,造成矿产资源定量预测结果中潜在大量不确定性。在科学认识这些不确定性的基础上,如何降低不确定性是预测评价研究的一个重要方向。以地质异常理论和成矿动力学为指导,双向预测评价方法是降低地质异常分析中不确定性的有效途径,该方法具体包括基于矿床成因模型的成矿模拟和基于找矿模型与勘查数据相结合的模型驱动预测。前者作为研究成矿地质演化过程、探讨成矿动力学机制的定量化方法之一,可以直观展示成矿过程内部物理化学变化。作为对致矿地质异常分析的有效手段,通过将成矿过程抽象为不受时空间限制的可迭代计算的偏微分方程组,可实现定量化描述复杂成矿动态过程并预测成矿有利部位。通过挖掘成矿有利信息,分析地质变量并赋值,为预测模型提供大量的定量化预测变量和特征值,是矿产资源定量预测评价的一个最具潜力的发展方向。后者以勘查学为指导的矿化异常分析,从矿致地质异常的角度开展定量预测,减少了单一成矿有利信息的多解性并降低了预测结果的不确定性。该技术手段是依托空间数据库、地质统计学和地理信息系统空间分析技术支撑,以三维地质体模型的建立为基础,以分析成矿规律并建立找矿模型为核心工作内容,以证据权、找矿信息量等数学方法为工具,统计分析研究区内各地质要素单元的分布情况来探讨各地质要素对矿产预测的影响,最终实现基于“立方体预测模型”的定位、定量和定概率的隐伏矿体三维预测目标。以上方法从两种不同的地质角度和定量化理念创新性地实现了双向联合预测评价,两种技术手段的融合作为综合圈定“5P”找矿地段的数学地质方法,其作用和价值是相互补充并有机结合的。通过文中方法介绍和应用实例的研究成果,可以明确该方法确实提高了矿产资源定量预测评价的预测精度,一定程度上降低了预测的不确定性,整体上推动了地球科学研究由定性描述向定量化自然科学的转变。 相似文献
14.
不确定性是指关于空间过程和特征不能被准确确定的过程，它是自然界各种空间现象自身固有的属性，如何在GIS数据库中合理的表示不确定性一直是学术界关注的疸。根据数据性质的不同，GIS中数据不确定性可分为定位不确定性和属性不确定性。由于属性数据有定量和定性之分，故相应的属性不确定性可以有2种表示方法：一种是用点误差分析的方法，另一种则是用离散型的数据误差的方法来进行评价，因此可以用标准差来表示定量数据的不确定性，用概率矢量和概率面来分别表示矢量和栅格数据模型中的定位数据不确定性。以此为基础可以很快地导出基于确定的算术运算和逻辑叠加等空间分析操作后的误差传播关系。 相似文献
15.
Reliable 3D modelling of underground hydrocarbon reservoirs is a challenging task due to the complexity of the underground geological formations and to the availability of different types of data that are typically affected by uncertainties.In the case of geologically complex depositional environments,such as fractured hydrocarbon reservoirs,the uncertainties involved in the modelling process demand accurate analysis and quantification in order to provide a reliable confidence range of volumetric estimations.In the present work,we used a 3D model of a fractured carbonate reservoir and populated it with different lithological and petrophysical properties.The available dataset also included a discrete fracture network(DFN)property that was used to model the fracture distribution.Uncertainties affecting lithological facies,their geometry and absolute positions(related to the fault system),fracture distribution and petrophysical properties were accounted for.We included all different types of uncertainties in an automated approach using tools available in today's modelling software packages and combining all the uncertain input parameters in a series of statistically representative geological realizations.In particular,we defined a specific workflow for the definition of the absolute permeability according to an equivalent,single porosity approach,taking into account the contribution of both the matrix and the fracture system.The results of the analyses were transferred into a 3D numerical fluid-dynamic simulator to evaluate the propagation of the uncertainties associated to the input data down to the final results,and to assess the dynamic response of the reservoir following a selected development plan.The"integrated approach"presented in this paper can be useful for all technicians involved in the construction and validation of 3D numerical models of hydrocarbon-bearing reservoirs and can potentially become part of the educational training for young geo-scientists and engineers,since an integrated and well-constructed workflow is the backbone of any reservoir study. 相似文献
16.
在1:5万平原区填图试点项目中,以生祠堂镇幅浅表地质填图为例,研究了该区浅表三维模型的构建。根据研究区遥感地貌特征,部署了15条北西向地质路线,以Eijkelkamp槽型取样钻为手段,揭露了研究区浅表3~4 m范围内的沉积物特征,建立以DSI为关键技术的三维浅表模型构建的基本流程,将槽型钻岩性描述量化为空间属性点,并建立标准层位,对各层位分别进行属性插值,获取分层沉积物岩性三维模型,选取北西向AA'典型路线三维剖面,研究区域纵向沉积相的变化,以剥去耕植土后的河流相层为例,结合地貌特征,勾绘出本区地表岩性岩相界线。研究成果表明,三维浅表模型对于区域地质调查、地质图、岩性岩相图、全新世第四纪地质填图等均有重要的应用价值,并可应用于浅层地下水防污性能研究、土壤污染等地质环境问题研究。 相似文献
17.
Assessing spatial uncertainty in mapping soil erodibility factor using geostatistical stochastic simulation 总被引：1，自引：0，他引：1
Soil erosion is one of most widespread process of degradation. The erodibility of a soil is a measure of its susceptibility
to erosion and depends on many soil properties. Soil erodibility factor varies greatly over space and is commonly estimated
using the revised universal soil loss equation. Neglecting information about estimation uncertainty may lead to improper decision-making.
One geostatistical approach to spatial analysis is sequential Gaussian simulation, which draws alternative, equally probable,
joint realizations of a regionalised variable. Differences between the realizations provide a measure of spatial uncertainty
and allow us to carry out an error analysis. The objective of this paper was to assess the model output error of soil erodibility
resulting from the uncertainties in the input attributes (texture and organic matter). The study area covers about 30 km2 (Calabria, southern Italy). Topsoil samples were collected at 175 locations within the study area in 2006 and the main chemical
and physical soil properties were determined. As soil textural size fractions are compositional data, the additive-logratio
(alr) transformation was used to remove the non-negativity and constant-sum constraints on compositional variables. A Monte
Carlo analysis was performed, which consisted of drawing a large number (500) of identically distributed input attributes
from the multivariable joint probability distribution function. We incorporated spatial cross-correlation information through
joint sequential Gaussian simulation, because model inputs were spatially correlated. The erodibility model was then estimated
for each set of the 500 joint realisations of the input variables and the ensemble of the model outputs was used to infer
the erodibility probability distribution function. This approach has also allowed for delineating the areas characterised
by greater uncertainty and then to suggest efficient supplementary sampling strategies for further improving the precision
of K value predictions. 相似文献
18.
The majority of geostatistical estimation and simulation algorithms rely on a covariance model as the sole characteristic of the spatial distribution of the attribute under study. The limitation to a single covariance implicitly calls for a multivariate Gaussian model for either the attribute itself or for its normal scores transform. The Gaussian model could be justified on the basis that it is both analytically simple and it is a maximum entropy model, i.e., a model that minimizes unwarranted structural properties. As a consequence, the Gaussian model also maximizes spatial disorder (beyond the imposed covariance) which can cause flow simulation results performed on multiple stochastic images to be very similar; thus, the space of response uncertainty could be too narrow entailing a misleading sense of safety. The ability of the sole covariance to adequately describe spatial distributions for flow studies, and the assumption that maximum spatial disorder amounts to either no additional information or a safe prior hypothesis are questioned. This paper attempts to clarify the link between entropy and spatial disorder and to provide, through a detailed case study, an appreciation for the impact of entropy of prior random function models on the resulting response distributions. 相似文献
19.
The majority of geostatistical estimation and simulation algorithms rely on a covariance model as the sole characteristic of the spatial distribution of the attribute under study. The limitation to a single covariance implicitly calls for a multivariate Gaussian model for either the attribute itself or for its normal scores transform. The Gaussian model could be justified on the basis that it is both analytically simple and it is a maximum entropy model, i.e., a model that minimizes unwarranted structural properties. As a consequence, the Gaussian model also maximizes spatial disorder (beyond the imposed covariance) which can cause flow simulation results performed on multiple stochastic images to be very similar; thus, the space of response uncertainty could be too narrow entailing a misleading sense of safety. The ability of the sole covariance to adequately describe spatial distributions for flow studies, and the assumption that maximum spatial disorder amounts to either no additional information or a safe prior hypothesis are questioned. This paper attempts to clarify the link between entropy and spatial disorder and to provide, through a detailed case study, an appreciation for the impact of entropy of prior random function models on the resulting response distributions. 相似文献