Stochastic Distance Based Geological Boundary Modeling with Curvilinear Features

Obtaining accurate geological boundaries and assessing the uncertainty in these limits are critical for effective ore resource and reserve estimation. The uncertainty in the extent of an ore body can be the largest source of uncertainty in ore resource estimation when drilling is sparse. These limits are traditionally interpreted deterministically and it can be difficult to quantify uncertainty in the boundary and its impact on ore tonnage. The proposed methodology is to consider stochastic modeling of the ore boundary with a distance function recoding of the available data. This technique is modified to incorporate non-stationarities in the form of a locally varying anisotropy field used in kriging and sequential Gaussian simulation. Implementing locally varying anisotropy kriging retains the geologically realistic features of a deterministic model while allowing for a stochastic assessment of uncertainty. A case study of a gold deposit in Northern Canada is used to demonstrate the methodology. The proposed technique generates realistic, curvilinear geological boundary models and allows for an assessment of the uncertainty in the model.     

Stochastic Structural Modeling

A consistent stochastic model for faults and horizons is described. The faults are represented as a parametric invertible deformation operator. The faults may truncate each other. The horizons are modeled as correlated Gaussian fields and are represented in a grid. Petrophysical variables may be modeled in a reservoir before faulting in order to describe the juxtaposition effect of the faulting. It is possible to condition the realization on petrophysics, horizons, and fault plane observations in wells in addition to seismic data. The transmissibility in the fault plane may also be included in the model. Four different methods to integrate the fault and horizon models in a common model is described. The method is illustrated on an example from a real petroleum field with 18 interpreted faults that are handled stochastically.     

Stochastic Simulation of Patterns Using Distance-Based Pattern Modeling

The advent of multiple-point geostatistics (MPS) gave rise to the integration of complex subsurface geological structures and features into the model by the concept of training images. Initial algorithms generate geologically realistic realizations by using these training images to obtain conditional probabilities needed in a stochastic simulation framework. More recent pattern-based geostatistical algorithms attempt to improve the accuracy of the training image pattern reproduction. In these approaches, the training image is used to construct a pattern database. Consequently, sequential simulation will be carried out by selecting a pattern from the database and pasting it onto the simulation grid. One of the shortcomings of the present algorithms is the lack of a unifying framework for classifying and modeling the patterns from the training image. In this paper, an entirely different approach will be taken toward geostatistical modeling. A novel, principled and unified technique for pattern analysis and generation that ensures computational efficiency and enables a straightforward incorporation of domain knowledge will be presented.     

Surface-Based 3D Modeling of Geological Structures

Building a 3D geological model from field and subsurface data is a typical task in geological studies involving natural resource evaluation and hazard assessment. However, there is quite often a gap between research papers presenting case studies or specific innovations in 3D modeling and the objectives of a typical class in 3D structural modeling, as more and more is implemented at universities. In this paper, we present general procedures and guidelines to effectively build a structural model made of faults and horizons from typical sparse data. Then we describe a typical 3D structural modeling workflow based on triangulated surfaces. Our goal is not to replace software user guides, but to provide key concepts, principles, and procedures to be applied during geomodeling tasks, with a specific focus on quality control.     

Stochastic Modeling of Progressive Failure in Heterogeneous Soil Slope

Accurate and efficient simulation of the slope stability, certainly gives the reliable approach for the hazard preparedness. However, inherent difficulties associated with the slope failure make the situation very difficult. First, the computation of fracture path based on the strict mathematical formalism is cumbersome especially for the progressive failure phenomenon. Second, due to the lack of reliable knowledge on material properties, stochastic simulation is necessary. Stochastic modeling together with the progressive failure phenomenon is apparently difficult task. In this paper, heterogeneous slope is simulated considering the progressive failure phenomenon using the modified finite element method introducing the fracture along the edge of the meshes thus incorporating the time evolution of the fracture surface. This is achieved by restructuring the tessellation in every fracture stage. Unlike remeshing this technique only increases the number of total nodes while number of meshes remaining same, which is simple and natural. Further, in this research, effect of uncertainty in the material properties upon the uncertainty in the response of soil slope has been evaluated, hence giving the reliable probabilistic estimation of the factor of safety, failure surface and deformation of the slope. Thus the simulation based on the more reliable understanding of the material properties and the efficient numerical procedure for the progressive failure phenomenon can give the reliable result of the simulation for the heterogeneous soil slope thus enabling the more accurate way for hazard preparedness.     

多点地质统计学在河流相储层建模中的应用

多点地质统计学综合了基于象元方法以及基于目标方法两者的优点,对于河流相等具有复杂地质形态的储层精确建模具有较强的优势.在对传统建模方法综合分析的基础上,介绍了多点地质统计学的基本理论及SNESIM算法,并应用该技术对大牛地气田某开发井区的辫状分流河道相进行了实际建模.研究结果表明,在河流相储层建模中,该方法比传统的建模方法更具优越性.最后,进一步综合讨论了多点地质统计学目前面临的主要问题(包括训练图像、目标体连续性、数据样板选择、综合地震信息等方面)的改进方法.     

地质流体状态方程

几乎所有的地球化学过程都有地质流体参加, 定量地了解地质流体的物理化学性质是定量研究地球化学过程的基础.100多年以来, 广大化学和实验地球化学工作者做了大量的实验测定工作, 可是所有这些工作之和, 仅仅覆盖地球范围内一个不大的温压空间, 远远不能满足地球化学研究的需要.近年来, 我们试图通过分子水平上的研究, 结合热力学和统计力学方面的知识, 在重现前人实验结果的基础上, 研究实验工作者没有或不能研究的温压和成分空间, 得到了一系列能够精确预测地质流体在广阔的温压范围内的物理化学性质的状态方程.这些状态方程不仅能够重现实验数据, 而且具有良好的外延能力, 可以应用于地球化学领域诸多方面的研究.重点讨论了几个状态方程(包括纯流体状态方程含水溶液状态方程和含盐-水-气的状态方程) 在预测流体的溶解度、相平衡、化学位和PVT性质方面的应用.简要介绍了近年来笔者应用分子动力学和蒙特卡罗模拟在地质流体研究方面所取得的成果      

油藏地质建模及实时跟踪研究

为了提高采收率,降低开发风险,以滩海地区某油田为研究对象,结合地质、测井、地震等资料,对该油藏进行实时跟踪地质特征综合研究。应用地质建模、随钻测井、地质导向等技术,建立了精细的三维地质导向模型,并根据随钻测井数据和综合地质信息,实时验证构造和储集层信息,对导向模型不断校正,使模型与实钻结果一致,还以该模型为基础,优化水平井钻井的前进轨迹。结果表明,此种方法的应用降低了海上油田开发风险,能取得良好的开发效果。     

Fine Geological Modeling of the Tight Oil Reservoir

<正>1 Introduction The study area of Northern Honggang is located in the Daan-Honggang terrace in the central depression of the southern Songliao basin,covering an area of 110km2.The oil field is categorized as an ultra-low permeability reservoir and the target horizon is the Fuyu oil layer.The reservoir is characterized as poor physical property,strong     

地质空间认知与多维动态建模结构研究

地质空间建模本质上是通过有限的地质空间数据,重构地质空间对象和格局,以恢复或模拟特定地质空间相关特征供人感知的过程和工具。从空间认识的角度分析讨论了地质空间的本质特征,提出了三维地质建模的5个技术层次结构、对应的模型层次划分和三维地质建模生命周期。实际应用表明,该体系结构能够有效支持地上地下一体化三维地质建模。这将有助于多维地质空间建模理论体系的建立与完善。     

Stochastic Seismic Waveform Inversion Using Generative Adversarial Networks as a Geological Prior

Mathematical Geosciences - We present an application of deep generative models in the context of partial differential equation constrained inverse problems. We combine a generative adversarial...     

Stochastic Modeling of Variably Saturated Transient Flow in Fractal Porous Media

This work presents the application of a Monte Carlo simulation method to perform an statistical analysis of transient variably saturated flow in an hypothetical random porous media. For each realization of the stochastic soil parameters entering as coefficients in Richards' flow equation, the pressure head and the flow field are computed using a mixed finite element procedure for the spatial discretization combined with a backward Euler and a modified Picard iteration in time. The hybridization of the mixed method provides a novel way for evaluating hydraulic conductivity on interelement boundaries. The proposed methodology can handle both large variability and fractal structure in the hydraulic parameters. The saturated conductivity K _s and the shape parameter _vg in the van Genuchten model are treated as stochastic fractal functions known as fractional Brownian motion (fBm) or fractional Gaussian noise (fGn). The statistical moments of the pressure head, water content, and flow components are obtained by averaging realizations of the fractal parameters in Monte Carlo fashion. A numerical example showing the application of the proposed methodology to characterize groundwater flow in highly heterogeneous soils is presented.     

Stochastic Modeling of Subseismic Faults Conditioned on Displacement and Orientation Maps

Mathematical Geosciences - Subseismic faults are small faults or fractures that may be difficult to determine but can have large consequences for fluid flow and pressure communication in the...     

Application of Bayesian Generative Adversarial Networks to Geological Facies Modeling

Mathematical Geosciences - Geological facies modeling is a key component in exploration and characterization of subsurface reservoirs. While traditional geostatistical approaches are still commonly...     

Surpac软件在三维地质建模中的应用

当今矿业领域开始不断向着数字化、可视化的方向发展,数字矿山已成为矿山采矿行业未来发展的主要趋势。该文在基于某地区金矿的勘查数据,介绍了Surpac三维数学建模软件的主要功能,模块和在地学领域中的应用,并综合论证该软件未来的发展优势和前景。     

基于线框单元体的三维闭合地质块体构建方法

为能充分利用空间数据模型中的拓扑关系来实现三维闭合块体的构建,引入了表示简单块体轮廓的线框单元体概念来组织三维模型间各要素之间的拓扑关系;并以此为基础给出了以方向边和方向三角形作为基本识别单元进行三维简单形体的自动识别方法。应用实例表明：利用该方法不仅可以准确构建复杂地质块体,还可以准确描述块体内各要素的拓扑关系,再现局部特殊地质现象,如小断层（悬面）等。为三维地质模型在地震正演模拟、射线追踪等分析应用方面提供了基础。     

基于钻孔数据的滑坡三维地质建模研究

对现有建模方法进行分析,结合千将坪滑坡地质特点,首先进行钻孔数据处理,然后提出引入虚拟钻孔,再利用GOCAD软件提供的Kriging插值技术建立滑坡界面和实体模型.该方法不但为滑坡三维地质建模提供了参考,也为区域性、地质状况复杂、钻孔资料欠缺地区的三维地质建模提供了借鉴.     

一种基于物性数据的深部三维地质建模方法

地质采样信息不足是制约深部三维地质建模的重要因素, 深部物性探测数据由于其易于获取而能够有效形成可视化模型.结合这一特点, 在地质调查项目工作中探索出了一种基于物性探测数据的三维地质建模方法.它首先利用岩石样品物性测量实验数据提取出物性参数及其对应地质属性的映射关系, 然后将不同地球物理方法所获取到的物性数据进行综合建模并解释, 最后将解释后的可视化模型转换为地质三维模型.实践证明, 该方法能够针对性地解决项目中的一些深部地质三维建模问题.      

Spatial Modeling Techniques for Characterizing Geomaterials:Deterministic vs.Stochastic Modeling for Single-Variable and Multivariate Analyses

Sample data in the Earth and environmental sciences are limited in quantity and sampling location and therefore, sophisticated spatial modeling techniques are indispensable for accurate imaging of complicated structures and properties of geomaterials. This paper presents several effective methods that are grouped into two categories depending on the nature of regionalized data used. Type I data originate from plural populations and type II data satisfy the prerequisite of stationarity and have distinct spatial correlations. For the type I data, three methods are shown to be effective and demonstrated to produce plausible results: (1) a spline-based method, (2) a combination of a spline-based method with a stochastic simulation, and (3) a neural network method. Geostatistics proves to be a powerful tool for type II data. Three new approaches of geostatistics are presented with case studies: an application to directional data such as fracture, multi-scale modeling that incorporates a scaling law, and space-time joint analysis for multivariate data. Methods for improving the contribution of such spatial modeling to Earth and environmental sciences are also discussed and future important problems to be solved are summarized.      

Geological Modeling on the Reservoir of Oil Sand in Estuary

<正>1 Introduction Athabasca oil sands are large deposits of heavy crude oil,located in northeastern Alberta Basin,Canada.Those oil sands,hosted primarily in upper and middle of McM urray Formation,is in 18m in thickness and 160m-180m in buried depth.The average liquid saturation is