Comparison of Two Methods Used to Model Shape Parameters of Pareto Distributions

Two methods are compared for estimating the shape parameters of Pareto field-size (or pool-size) distributions for petroleum resource assessment. Both methods assume mature exploration in which most of the larger fields have been discovered. Both methods use the sizes of larger discovered fields to estimate the numbers and sizes of smaller fields: (1) the tail-truncated method uses a plot of field size versus size rank, and (2) the log–geometric method uses data binned in field-size classes and the ratios of adjacent bin counts. Simulation experiments were conducted using discovered oil and gas pool-size distributions from four petroleum systems in Alberta, Canada and using Pareto distributions generated by Monte Carlo simulation. The estimates of the shape parameters of the Pareto distributions, calculated by both the tail-truncated and log–geometric methods, generally stabilize where discovered pool numbers are greater than 100. However, with fewer than 100 discoveries, these estimates can vary greatly with each new discovery. The estimated shape parameters of the tail-truncated method are more stable and larger than those of the log–geometric method where the number of discovered pools is more than 100. Both methods, however, tend to underestimate the shape parameter. Monte Carlo simulation was also used to create sequences of discovered pool sizes by sampling from a Pareto distribution with a discovery process model using a defined exploration efficiency (in order to show how biased the sampling was in favor of larger fields being discovered first). A higher (more biased) exploration efficiency gives better estimates of the Pareto shape parameters.     

海相低勘探程度地区油气资源评价:以柴达木盆地德令哈坳陷石炭系为例

海相低勘探程度地区油气资源评价的难点是资料少、地质认识程度低、主要参数获取难度大,影响评价结果可信性.以柴达木盆地德令哈坳陷石炭系为例,系统评价德令哈坳陷石炭系生储盖条件,油气资源评价选用盆地模拟法与类比法相结合方法,关键参数的确定采用了地球物理、地球化学与石油地质学等多种方法,利用油气运移聚集模拟和不同运聚单元资源量...     

Undiscovered Petroleum Accumulation Mapping Using Model-Based Stochastic Simulation

Stochastic simulation has been proven to be a useful tool for revealing uncertainties in petroleum exploration and exploitation. The application to petroleum resource assessment would result in predicted potential accumulations with geographic locations, a desirable feature for improving both resource management and exploration efficiency. The associated uncertainties with the prediction provide information useful for exploration risk analysis. This attempt has been encumbered by two typical technical difficulties: biased observation data and lack of information with respect to the undiscovered accumulation locations. In this paper we propose a model-based simulation approach, in which models are used to perform unbiased parameter estimation from biased data and to facilitate the location of undiscovered petroleum accumulations based on reasoning of available geological and geophysical observations. The Fourier transform algorithm is chosen for the simulation because the spatial correlation and location-specific features can be studied separately from different data sources and integrated in the simulation in a frequency domain. The proposed approach is illustrated by an example from the Rainbow petroleum play in the West Canadian Sedimentary Basin. In the application example, a pre-1994 exploration history data set was used as input, and the predictions are then checked against the locations of post-1993 exploratory drilling results. The comparison of the predictions from the proposed approach and the traditional conditional simulation shows that the model-based approach captures the essentials of geological controls on the spatial distribution of petroleum accumulation, thus improving the projections of undiscovered petroleum accumulations.     

Prediction of volumes and risk in hydrocarbon exploration: a quantification of geology

 The prediction of the hydrocarbon potential of a specific trap or of a number of specific traps (venture), referred to herein as prospect appraisal, concerns a probabilistic exercise based on the quantification of geology in terms of structural closure, reservoir quality, hydrocarbon charge, and the retention potential of the seal. Its objectives include: (a) prediction of the hydrocarbon volumes that could be present in the trap from an analysis of its geologic attributes; (b) the amount of uncertainty introduced in the volumetric prediction by the uncertainties in the subsurface geology; (c) the risk that one or more of the essential attributes of the prospect are underdeveloped and recoverable reserves are absent. The uncertainty of the geologic input requires a probabilistic approach, for which the Monte Carlo procedure is well suited. Prospect appraisal forms the basis for decision-making in oil exploration and development and, therefore, should be reliable, consistent, and auditable. This requires the use of a consistent methodology, the development of reliable models to quantify the geologic processes involved, and the collection of comprehensive and relational databases for the many geologic variables. As a result of data availability, uncertainty and risk tend to increase strongly from mature, producing basins to areas of frontier exploration. This may complicate management of exploration portfolios. Received: 1 July 1996/Accepted: 25 November 1996     

Sensitivity and uncertainty analyses for performance assessment modeling

Sensitivity and uncertainty analyses methods for computer models are being applied in performance assessment modeling in the geologic high-level radioactive-waste repository program. The models used in performance assessment tend to be complex physical/chemical models with large numbers of input variables. There are two basic approaches to sensitivity and uncertainty analyses: deterministic and statistical. The deterministic approach to sensitivity analysis involves numerical calculation or employs the adjoint form of a partial differential equation to compute partial derivatives; the uncertainty analysis is based on Taylor series expansions of the input variables propagated through the model to compute means and variances of the output variable. The statistical approach to sensitivity analysis involves a response surface approximation to the model with the sensitivity coefficients calculated from the response surface parameters; the uncertainty analysis is based on simulation. The methods each have strengths and weaknesses.     

人力资源管理中存在的问题与对策

当前我国企事业单位的人力资源管理,在开发形式、考评标准、选用制度等方面存在着不科学、不规范等问题。通过分析人力资源管理中的各种弊端及症结,提出其相应的对策,即在人力资源开发上实行购买培训,接受社会评估;在人员考评上建立定性考评与定量考评、贡献考评与能力考评相结合的考评体系;在人员选用上建立科学、民主、公开、透明的新机制。     

Some Suggested Future Directions ofQuantitative Resource Assessments

Like most journeys, success depends critically on wherewe are going to be in the end. Thus, if we are to have someideas about future directions of quantitative assessments ofmineral resources, we need some basic understanding of whatthe assessments will be used for. What will be expected ofquantitative resource assessments in the future? It would behelpful to identify who will use these future assessments, howthe assessments will be used, and what are acceptable forms ofproducts. The purpose o…     

安徽省两淮地区煤炭资源地质条件分区、分等初步研究

地质变化程度及其所涉及的相关地质条件分类问题是影响勘查工程布置的主要因素。借鉴原国家煤炭部技术咨询委员会1992年所作的《矿井综合评价及分类》所建立的评价指标体系和层次分析评价办法,对两淮地区煤炭资源地质条件进行定性与定量相结合的分区、分等综合评价。首先以两淮地区现有的地质报告成果为依据,以矿区为基本评价单元,选择构造复杂程度和煤层稳定类型作为评价参数,将煤层赋存深度和水文地质条件作为修正参数,应用层次分析法建立起相应的评价指标体系,确定各层次权重系数及相关因素的隶属度,以此建立地质条件分等与煤层连续性、煤层连续性与构造复杂程度及煤层稳定程度之间的对应关系,并确定地质条件分等定量划分标准,在此基础上对两淮地区煤炭资源地质条件作出分区、分等综合评价：淮北煤田的宿县、临涣矿区和淮南煤田的潘谢、淮南定远矿区为地质条件Ⅱ～Ⅲ等区;淮北煤田的濉萧、涡阳矿区和淮南煤田新集矿区为地质条件Ⅳ等区。     

发现过程模型法对大港陆地探区油气资源的评价

对现有油气资源基本评价方法的原理、优缺点、适应性做了分析总结，重点剖析了在油藏总体分布服从帕莱托分布基础上建立起来的发现过程模型法．同时根据已建立的油气藏总体预测模型，对符合发现过程模型的大港陆地古近系成藏体系进行了油气资源评价。     

Computer Modeling and Simulation of Geofluids： A General Review and Sample Description

Thermodynamic properties of fluids are essential for the understanding of the geochemical behavior of various processes,The paper introduces the most updated computer modeling and simulation methods in the study of thermodynamics of geofluids,inclduing semiempirical models(such as equation of state)and molecular dynamics and Monte Carlo simulation.A well-established semi-empirical model can interpolate and extrapolate experimental data and yield much physicochemical information.Computer modeling may produce“experimental data“ yield much physicochemical information.Computer modeling may produce“experimental data“even under experimentally difficult conditions.They provide important methods for the study of geological fluid systems on the quantitative basis.     

三种水文模型不确定性分析方法比较

模型不确定性研究是水文科学的重要课题。以尼泊尔Bagmati流域为案例,采用了马尔科夫链蒙托卡罗(Markov Chain Monte Carlo)、蒙托卡罗(Monte Carlo)和拉丁超立方体(Latin Hypercube)等三种方法,分析了水箱模型输出成果的不确定性,并将三种方法所获得参数不确定性进行了比较。另外,运用Meta-Gaussian模型计算了总体不确定性,在基于所采用的似然函数基础上,对由参数导致模型输出的不确定性和模型输出的总体不确定性进行了比较。结果显示,模型的不确定性比参数不确定性更为重要,同时也表明,尽管蒙托卡罗和拉丁超立方体两种模拟方法产生几乎相同的结果,但两者都与马尔科夫链蒙托卡罗方法有很大的不同。     

Stochastic analysis of unsaturated seepage through randomly heterogeneous earth embankments

Spatial variability of material properties is inherent in both natural soil deposits and earth structures, yet it is often ignored during geotechnical design. With the objective of developing novel methods for assessing the effects of soil variability on groundwater flow, this study presents a stochastic finite element model of seepage through a flood defense embankment with randomly heterogeneous material properties. Stochastic modeling is undertaken by means of a Monte Carlo simulation which involves a large number of finite element analyses, each with randomly varied porosity at element level, which leads to a corresponding random variation of both permeability and water retention properties across the embankment domain. This provides a statistical distribution of responses, such as total flow rate and time to reach steady state, instead of a single deterministic result as in conventional studies of seepage through unsaturated heterogeneous soils. As the degree of heterogeneity increases, water tends to flow along the most permeable paths inside the soil mass, resulting in an irregular shape of the predicted wetting fronts and pore pressure contours. The mean and standard deviation of the computed quantities strongly depend on the statistics of the input porosity field. Simulations are also conducted to compare the statistical variation of flow rate with and without dependency of the water retention curve on porosity. With recent growth in computer speed, stochastic finite element models based on the Monte Carlo approach can become a powerful design tool, especially if a quantitative assessment of geotechnical risks is required. Copyright © 2011 John Wiley & Sons, Ltd.     

资源定量评价发展方向展望

未来的资源定量评价希望能够评估未发现矿产资源的量、价值并对其进行定位预测, 以能够表达矿产资源的经济潜力和不确定性.近年来金属价格的长期下跌提出了对更大型的矿床的需求.敏感度分析表明了减少评价中不确定性和风险的最有效途径是降低有关吨位估计因素的不确定性.到目前为止, 在评价中所有可能造成误差的因素中, 那些与吨位估计误差有关的因素是最重要的.鉴于吨位模型的绝对重要地位以及矿床模型是吨位最有效的预测手段, 正确地选择矿床模型是控制误差最重要的途径.地表大部分地区被大面积裸露的岩石和沉积物所覆盖.由于很多出露地表的矿床已经被发现, 人们开始把注意力转向盖层下面岩石可能显露的矿化信息上.这些区域的资源评价必需依靠对其周边地区的外推、地下覆盖岩石新的地质填图或者通过在其他成功勘探区获得的经验进行类推.盖层对评价的不确定性以及评价的方法与程序都具有深远的影响, 因为地下地质现象的不可见性和地球物理方法所获得的是一种被削弱了的信息.许多早期的评价方法都是基于从那些出露地表的矿床中总结出的地球化学和地球物理变量之间的关系而进行的, 而现在我们同样需要研究基于地下隐伏矿床的勘探经验.矿床模型在资源定量评价中的重要地位基于以下两个原因: (1) 大多数矿床类型具有明显不同的品位和吨位分布; (2) 不同的矿床类型出现在不同的地质背景中, 而这种背景可从地质图中进行区分.在综合利用地质、矿产、地球物理和地球化学等地学信息进行资源评价及矿床勘探中, 矿床模型起着至关重要的作用.品位和吨位模型以及定量描述、经济和矿床密度模型的发展将有利于减少这些新的评价的不确定性.      

Research on the loss of group residential buildings under fierce winds

The prediction and assessment of the loss of group residential buildings under fierce winds are not only an important but also a very basic work. Many rural buildings, especially situated in southeastern of China, have suffered great damage and losses during such wind events in past 10 years. One new methodology is proposed in this study in order to estimate and evaluate the loss reasonably based on group building types and distribution, wind intensities and directions. This methodology comprehensively considers the mechanisms of interaction between the roof tiles, roof panels, doors and windows, which are more likely damaged seriously during fierce winds, the physical properties of those components, the wind pressure coefficients on the surface of group buildings in different wind directions, etc. Then Monte Carlo simulation is used to estimate the damage of group residential buildings under simulated fluctuating winds with different speeds and measured typhoon records. The simulation results indicate that our proposed quantified assessment method can be utilized for official, developers, architects, designers and homeowners to estimate and mitigate the losses that might be experienced during wind-related disasters either pre- or post-construction.     

Probabilistic stability assessment of slopes using high dimensional model representation

This paper presents a new computational tool for probabilistic stability assessment of earth slopes/embankments. The method involves high dimensional model representation (HDMR) that facilitates lower dimensional approximation of the original limit state, response surface generation of HDMR component functions, and Monte Carlo simulation. HDMR is a general set of quantitative model assessment and analysis tools for capturing the high-dimensional relationships between sets of input and output model variables. It is a very efficient formulation of the system response, if higher-order variable correlations are weak, allowing the physical model to be captured by the first few lower-order terms. Once the approximate form of the original limit state is defined, the failure probability can be obtained by statistical simulation. Results of four numerical examples indicate that the proposed method provides accurate and computationally efficient estimates of the failure probability of earth slopes/embankments.     

三维城市地质信息平台

三维城市地质信息平台综合利用GIS、数字地质、现代数据库、计算机网络等技术,对研究范围的基础地质、水文地质、工程地质、环境地质、地面沉降、地球物理、地球化学、遥感、灾害地质等多专业的地质信息和成果进行集成和综合,实现对地质信息管理、更新维护、检索查询、分析评价、三维地质模拟和成果显示,在此基础上对城市地表与地下空间结构组织与空间资源、地质灾害、地下水资源与地质环境保护、地面沉降监测与防治、城市规划与建设、土地质量与后备资源等进行分析评价和预测模拟。     

与找矿信息量法结合的含矿网格单元蒙特卡洛矿产资源潜力评价方法的原理及应用

文章介绍了以含矿网格单元为统计单位、并与找矿信息量法结合的蒙特卡洛矿产资源潜力评价方法的原理和工作步骤,以及用该法进行丹池锡多金属成矿带锡矿矿产资源潜力评价工作案例,表明该法可以把评价工作区的矿产空间分布信息、成矿模式和找矿模型、成矿-找矿空间信息引入蒙特卡洛方法中,无需人类专家估计矿床个数,减少了工作步骤,提高了工作效率和自动化程度,减少了因人为主观性而造成的评价误差。     

塔里木叠合盆地待发现可采油气资源初步预测及评价

油气资源评价单元的划分是盆地油气资源定量评价的核心,而盆地的含油气系统又为限定评价单元之基础。以复合油气系统原理和方法为指导,油气源对比判识为手段,以寻找各供烃中心和油气藏之间成因关系为目的,重新划分了塔里木盆地4个复合油气系统和5个评价单元。在详尽分析评价单元油气勘探历史和发现历史基础上,结合已发现或落实的圈闭数量和规模,利用第七逼近法和蒙特卡罗法,对塔里木盆地已知油气系统中评价单元进行了油气资源与油气田规模、数量的定量预测评价。研究表明,塔里木盆地待发现石油可采资源量11.43×108t,预测油田数量94个,86%集中在台盆区下古生界海相评价单元;预测待发现天然气可采资源量21000×108m3,气田数量104个,58%集中在库车前陆评价单元。塔里木盆地有近91%的石油、84%的天然气资源等待发现,是我国陆上资源发现程度较低的盆地,也是我国未来油气储量增长最重要的盆地。     

成藏体系中油气田母体的分布形式

预测一个地区油气田的规模分布和数量,为经济分析和勘探决策提供定量依据,是油气资源评价中必不可少的一个部分。目前对成藏体系中油气田规模分布形式存在不同的看法,建立一个可信的母体分布模型是预测油气田规模分布的基础。为研究成藏体系油气田母体的规模的分布形式,本文收集了世界范围内近六十个成藏体系和含油气盆地已发现油气田规模分布的资料,以此分析油气田母体的分布类型。     

Safety assessment of infrastructures using a new Bayesian Monte Carlo method

A recently developed Bayesian Monte Carlo (BMC) method and its application to safety assessment of structures are described in this paper. We use a one-dimensional BMC method that was proposed in 2009 by Rajabalinejad in order to develop a weighted logical dependence between successive Monte Carlo simulations. Our main objective in this research is to show that the extended BMC can dramatically improve simulation efficiency by using prior information from modelling and outcomes of preceding simulations. We provide theory and numerical algorithms for an extended BMC method for multi-dimensional problems, integrate it with a probabilistic finite element model and apply these coupled models to assessment of reliability of a flood defence for the 17th Street Flood Wall system in New Orleans. This is the first successful demonstration of the BMC method to a complex system. We provide a comparison of the numerical efficiency for the BMC, Monte Carlo (MC) and Dynamic Bounds methods that are used in reliability assessment of complex infrastructures.