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1.
Singer Donald A U. S. Geological Survey Middlefield Road Menlo Park California USA 《中国地质大学学报(英文版)》2001,12(1)
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… 相似文献
2.
资源定量评价发展方向展望 总被引：8，自引：0，他引：8
DonaldA.Singer 《地球科学》2001,26(2):152-156
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. 相似文献
3.
3D geological models are created to integrate a set of input measurements into a single geological model. There are many problems with this approach, as there is uncertainty in all stages of the modelling process, from initial data collection to the approach used in the modelling scheme itself to calculate the geological model. This study looks at the uncertainty inherent in geological models due to data density and introduces a novel method to upscale geological data that optimises the information in the initial dataset. This method also provides the ability for the dominant trend of a geological dataset to be determined at different scales. By using self-organizing maps (SOM's) to examine the different metrics used to quantify a geological model, we allow for a larger range of metrics to be used compared to traditional statistical methods, due to the SOM's ability to deal with incomplete datasets. The classification of the models into clusters based on the geological metrics using k-means clustering provides a useful insight into the models that are most similar and models that are statistical outliers. Our approach is guided and can be calculated on any input dataset of this type to determine the effect that data density will have on a resultant model. These models are all statistical derivations that represent simplifications and different scales of the initial dataset and can be used to interrogate the scale of observations. 相似文献
4.
River flow is a complex dynamic system of hydraulic and sediment transport. Bed load transport have a dynamic nature in gravel bed rivers and because of the complexity of the phenomenon include uncertainties in predictions. In the present paper, two methods based on the Artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are developed by using 360 data points. Totally, 21 different combination of input parameters are used for predicting bed load transport in gravel bed rivers. In order to acquire reliable data subsets of training and testing, subset selection of maximum dissimilarity (SSMD) method, rather than classical trial and error method, is used in finding randomly manipulation of these subsets. Furthermore, uncertainty analysis of ANN and ANFIS models are determined using Monte Carlo simulation. Two uncertainty indices of d factor and 95% prediction uncertainty and uncertainty bounds in comparison with observed values show that these models have relatively large uncertainties in bed load predictions and using of them in practical problems requires considerable effort on training and developing processes. Results indicated that ANFIS and ANN are suitable models for predicting bed load transport; but there are many uncertainties in determination of bed load transport by ANFIS and ANN, especially for high sediment loads. Based on the predictions and confidence intervals, the superiority of ANFIS to those of ANN is proved. 相似文献
5.
The presence of geological units with different grade characteristics mostly leads to problems during the grade modeling process. In special cases, if the area under study has units with small thickness and low grade with respect to the dominant unit of the area, it is difficult to reproduce different grade contents in these units in the simulated grade models because of the low thickness and lack of data in these units. In this study, the local moment constraints method, based on the definition of soft conditioning data reflecting geological knowledge, is investigated for improving simulated grade models under the mentioned conditions. This method is applied for grade simulation at the 1,750 m level of Sungun porphyry copper mine. The studied area is divided into two rock type domains: Sungun porphyry and Dyke. The Sungun porphyry unit is the dominant rock type in the considered area and has, on average, a higher copper grade, while dykes discontinue Sungun porphyry rock units sporadically and most of them are barren of mineralization. It is demonstrated that the use of soft conditioning data makes the simulated grade model closer to reality and improves the reproduction of grade contents considering the rock type units in the area. In the next step, the results obtained from conditional simulation are used for mineral resources classification. To this end, the conditional coefficient of variation is chosen as a criterion for measuring uncertainty and for defining the resources classes. Then, it is shown that uncertainty can be considerably reduced in the prepared models if soft data are considered; as a result, an increase in measured resource classification is observed. 相似文献
6.
A recently developed Bayesian interpolation method (BI) and its application to safety assessment of a flood defense structure
are described in this paper. We use a one-dimensional Bayesian Monte Carlo method (BMC) that has been proposed in (Rajabalinejad
2009) to develop a weighted logical dependence between neighboring points. The concept of global uncertainty is adequately explained
and different uncertainty association models (UAMs) are presented for linking the local and global uncertainty. Based on the
global uncertainty, a simplified approach is introduced. By applying the global uncertainty, we apply the Guassian error estimation
to general models and the Generalized Beta (GB) distribution to monotonic models. Our main objective in this research is to
simplify the newly developed BMC method and demonstrate that it can dramatically improve the simulation efficiency by using
prior information from outcomes of the preceding simulations. We provide theory and numerical algorithms for the BI method
geared to multi-dimensional problems, integrate it with a probabilistic finite element model, and apply the coupled models
to the reliability assessment of a flood defense for the 17th Street Flood Wall system in New Orleans. 相似文献
7.
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. 相似文献
8.
地下水库库容不确定性分析 总被引：3，自引：0，他引：3
文章利用蒙特卡罗方法分析了济宁市潜水含水层给水度空间分布的随机性对地下水库库容计算值的影响，讨论了当给水度均值与方差发生变化时，库容均值和方差的变化特征，为地下水库合理规划建设和地下水人工回灌的实施提供了依据。 相似文献
9.
WolfgangKinzelbach PeterBauer TobiasSiegfried PhilipBrunner 《《幕》》2003,26(4):279-284
Groundwater is a strategic resource due to its usually high quality and perennial availability. However, groundwater management all over the world often lacks sustainability as evidenced by falling water tables, drying wetlands, increasing sea-water intrusion and general deterioration of water quality. As groundwater cannot be renewed artificially on a large scale, sustainable management of this resource is vital. A number of scientific tools are available to assist in his task. Three items are discussed here. They include methods for the determination of groundwater recharge, groundwater modeling including the estimation of its uncertainty, and thenterfacing to the socio-economic field. Generally the quality of water management work can be largely enhanced with new tools available, including remote sensing, digital terrain models, differential GPS, environmental tracers, automatic data collection, modeling and the coupling of models from different disciplines 相似文献
10.
Some studies suggest that creep parameters should be determined using a greater quantity of creep test data to provide more reliable prediction regarding the deformation of soft soils. This study aims to investigate the effect of loading duration on model updating. One‐dimensional consolidation data of intact Vanttila clay under different loading durations collected from the literature is used for demonstration. The Bayesian probabilistic method is used to identify all unknown parameters based on the consolidation data during the entire consolidation process, and their uncertainty can be quantified through the obtained posterior probability density functions. Additionally, the optimal models are also determined from among 9 model candidates. The analyses indicate that the optimal models can describe the creep behavior of intact soft soils under different loading durations, and the adopted method can evaluate the effect of loading duration on uncertainty in the creep analysis. The uncertainty of a specific model and its model parameters decreases as more creep data are involved in the updating process, and the updated models that use more creep data can better capture the deformation behavior of an intact sample. The proposed method can provide quantified uncertainty in the process of model updating and assist engineers to decide whether the creep test data are sufficient for the creep analysis. 相似文献
11.
12.
Prior Ángel Tolosana-Delgado Raimon van den Boogaart K. Gerald Benndorf Jörg 《Mathematical Geosciences》2021,53(5):945-968
In the field of mineral resources extraction, one main challenge is to meet production targets in terms of geometallurgical properties. These properties influence the processing of the ore and are often represented in resource modeling by coregionalized variables with a complex relationship between them. Valuable data are available about geometalurgical properties and their interaction with the beneficiation process given sensor technologies during production monitoring. The aim of this research is to update resource models as new observations become available. A popular method for updating is the ensemble Kalman filter. This method relies on Gaussian assumptions and uses a set of realizations of the simulated models to derive sample covariances that can propagate the uncertainty between real observations and simulated ones. Hence, the relationship among variables has a compositional nature, such that updating these models while keeping the compositional constraints is a practical requirement in order to improve the accuracy of the updated models. This paper presents an updating framework for compositional data based on ensemble Kalman filter which allows us to work with compositions that are transformed into a multivariate Gaussian space by log-ratio transformation and flow anamorphosis. This flow anamorphosis, transforms the distribution of the variables to joint normality while reasonably keeping the dependencies between components. Furthermore, the positiveness of those variables, after updating the simulated models, is satisfied. The method is implemented in a bauxite deposit, demonstrating the performance of the proposed approach.
相似文献13.
Geologic uncertainty in a regulatory environment: An example from the potential Yucca Mountain nuclear waste repository site 总被引：1，自引：0，他引：1
Regulatory geologists are concerned with predicting the performance of sites proposed for waste disposal or for remediation of existing pollution problems. Geologic modeling of these sites requires large-scale expansion of knowledge obtained from very limited sampling. This expansion induces considerable uncertainty into the geologic models of rock properties that are required for modeling the predicted performance of the site.One method for assessing this uncertainty is through nonparametric geostatistical simulation. Simulation can produce a series of equiprobable models of a rock property of interest. Each model honors measured values at sampled locations, and each can be constructed to emulate both the univariate histogram and the spatial covariance structure of the measured data. Computing a performance model for a number of geologic simulations allows evaluation of the effects of geologic uncertainty. A site may be judged acceptable if the number of failures to meet a particular performance criterion produced by these computations is sufficiently low. A site that produces too many failures may be either unacceptable or simply inadequately described.The simulation approach to addressing geologic uncertainty is being applied to the potential high-level nuclear waste repository site at Yucca Mountain, Nevada, U.S.A. Preliminary geologic models of unsaturated permeability have been created that reproduce observed statistical properties reasonably well. A spread of unsaturated groundwater travel times has been computed that reflects the variability of those geologic models. Regions within the simulated models exhibiting the greatest variability among multiple runs are candidates for obtaining the greatest reduction in uncertainty through additional site characterization. 相似文献
14.
Nan Li Leon Bagas Mark Lindsay Daniel Wedge Lin Bai Xianglong Song 《Earth Science Informatics》2017,10(2):149-167
Three-dimensional (3D) buffer analysis is a basic function of spatial analysis used widely in 3D Geographic Information Systems (3DGIS). Current buffer analysis methods for spatial points and curves generally function well. One exception is buffer zone of surface. Previous researchers in this field have used voxel models to overcome this limitation; however, defects with voxel model buffer analysis include redundancies, approximations, and poor visualization characteristics. In this contribution, a surface buffer analysis method is presented for the boundary representation of geological objects. Exact geometric representation is achieved via the construction of irregular triangle meshes in 3D. The results can be used for 3D structural modeling and then form the basis for spatial analysis or model-based quantitative assessment in mineral potential mapping and resource evaluation. Three comparisons between existing voxel methods and our new method, evaluating visualization, precision and redundancy, are conducted. The comparisons show that our proposed method is robust and provides a higher quality output than voxel modeling. Finally, uncertainty analysis of buffer distance in different geological objects was discussed. 相似文献
15.
水资源资产价格模糊数学综合评价指标体系构建——以黑河中游张掖市为例 总被引：5，自引：4，他引：1
针对水资源本身的模糊性和不确定性,基于模糊数学综合评价模型,从水量、水质、人口、社会经济和生态环境5个方面选取18个评价指标,结合AHP法与熵权法确定指标权重,对张掖市2010-2014年的水资源价格进行动态评价,水价计算模糊数学模型由水资源价值评价和水资源价格计算两部分组成.结果表明：采用水资源价值模糊综合指数对水资源价值进行测算,5 a间张掖市水资源模糊综合指数介于水资源价值指数的“中等”与“偏低”之间,说明张掖市水资源价值属于中等偏低;在2010-2014年5 a间水资源价格呈明显上升趋势,核算期初的2010年为2.12元·m-3,证实了张掖市目前水资源价格偏低,水资源资产价格存在较大的上升空间,而核算期末的2014年最高达4.96元·m-3.基于熵权与AHP相结合确定权重的水资源价格模糊数学综合评价模型,评价结果更客观合理,为下一步水资产负债表编制中水资产与负债价值核算提供数据支持. 相似文献
16.
Robert A. Crovelli 《Mathematical Geology》1988,20(8):955-972
The geologic appraisal model that is selected for a petroleum resource assessment depends upon purpose of the assessment, basic geologic assumptions of the area, type of available data, time available before deadlines, available human and financial resources, available computer facilities, and, most importantly, the available quantitative methodology with corresponding computer software and any new quantitative methodology that would have to be developed. Therefore, different resource assessment projects usually require different geologic models. Also, more than one geologic model might be needed in a single project for assessing different regions of the study or for cross-checking resource estimates of the area. Some geologic analyses used in the past for petroleum resource appraisal involved play analysis. The corresponding quantitative methodologies of these analyses usually consisted of Monte Carlo simulation techniques. A probabilistic system of petroleum resource appraisal for play analysis has been designed to meet the following requirements: (1) includes a variety of geologic models, (2) uses an analytic methodology instead of Monte Carlo simulation, (3) possesses the capacity to aggregate estimates from many areas that have been assessed by different geologic models, and (4) runs quickly on a microcomputer. Geologic models consist of four basic types: reservoir engineering, volumetric yield, field size, and direct assessment. Several case histories and present studies by the U.S. Geological Survey are discussed.This paper was presented at Emerging Concepts. MGLIS-87, Redwood City, California, 13–15 April 1987. 相似文献
17.
Guillaume Larocque Pierre Dutilleul Bernard Pelletier James W. Fyles 《Mathematical Geology》2007,39(3):263-288
Coregionalization analysis has been presented as a method of multi-scale analysis for multivariate spatial data. Despite an
increasing use of this method in environmental and earth sciences, the uncertainty associated with the estimation of parameters
in coregionalization analysis (e.g., sills and functions of sills) is potentially high and has not yet been characterized.
This article aims to discuss the theory underlying coregionalization analysis and assess the robustness and limits of the
method. A theoretical framework is developed to calculate the ergodic and fluctuation variance-covariance matrices of least-squares
estimators of sills in the linear model of coregionalization. To adjust for the positive semidefiniteness constraint on estimated
coregionalization matrices, a confidence interval estimation procedure for sills and functions of sills is presented. Thereafter,
the relative importance of uncertainty measures (bias and variance) for sills and structural coefficients of correlation and
determination is assessed under different scenarios to identify factors controlling their uncertainty. Our results show that
the sampling grid density, the choice of the least-squares estimator of sills, the positive semidefiniteness constraint, the
presence of scale dependence in the correlations, and the number and range of variogram models, all affect the level of uncertainty,
sometimes through multiple interactions. The asymptotic properties of variogram model parameter estimators in a bounded sampling
domain impose a theoretical limit to their accuracy and precision. Because of this limit, the uncertainty was found to be
high for several scenarios, especially with three variogram models, and was often more dependent on the ratio of variogram
range to domain extent than on the sampling grid density. In practice, in the coregionalization analysis of a real dataset,
the circular requirement for sill estimates in the calculation of uncertainty measures makes the quantification of uncertainty
very problematic, if not impossible. The use of coregionalization analysis must be made with due knowledge of the uncertainty
levels and limits of the method. 相似文献
18.
基于暴雨管理模型(SWMM),构建了澳门半岛雅廉访实验小区降雨径流模拟系统,采用generalized likelihood uncertainty estimation(GLUE)方法对复杂降雨径流模型参数的不确定性进行了分析,采用均匀分布为参数的先验分布(prior distribution),选取拉丁超立方法作为采样方法,Nash-Sutcliffe效率系数作为似然评判准则。结果表明该方法可以有效的分析降雨径流模型参数的不确定性,对降雨径流模型参数识别提供了深入分析与理解模型系统的有效途径。 相似文献
19.
《地学前缘(英文版)》2022,13(6):101435
The past two decades have seen a rapid adoption of artificial intelligence methods applied to mineral exploration. More recently, the easier acquisition of some types of data has inspired a broad literature that has examined many machine learning and modelling techniques that combine exploration criteria, or ‘features’, to generate predictions for mineral prospectivity. Central to the design of prospectivity models is a ‘mineral system’, a conceptual model describing the key geological elements that control the timing and location of economic mineralisation. The mineral systems model defines what constitutes a training set, which features represent geological evidence of mineralisation, how features are engineered and what modelling methods are used. Mineral systems are knowledge-driven conceptual models, thus all parameter choices are subject to human biases and opinion so alternative models are possible. However, the effect of alternative mineral systems models on prospectivity is rarely compared despite the potential to heavily influence final predictions. In this study, we focus on the effect of conceptual uncertainty on Fe ore prospectivity models in the Hamersley region, Western Australia. Four important considerations are tested. (1) Five different supergene and hypogene conceptual mineral systems models guide the inputs for five forest-based classification prospectivity models model. (2) To represent conceptual uncertainty, the predictions are then combined for prospectivity model comparison. (3) Representation of three-dimensional objects as two-dimensional features are tested to address commonly ignored thickness of geological units. (4) The training dataset is composed of known economic mineralisation sites (deposits) as ‘positive’ examples, and exploration drilling data providing ‘negative’ sampling locations. Each of the spatial predictions are assessed using independent performance metrics common to AI-based classification methods and subjected to geological plausibility testing. We find that different conceptual mineral systems produce significantly different spatial predictions, thus conceptual uncertainty must be recognised. A benefit to recognising and modelling different conceptual models is that robust and geologically plausible predictions can be made that may guide mineral discovery. 相似文献
20.
岩土体当中存在大量的不确定因素,给边坡的稳定性分析判断带来了困难。在分析了计算参数的不确定性是影响分析可靠性的主要原因的基础上,运用模糊集理论考虑计算参数的不确定性,提出了模糊参数的具体构造方法和边坡稳定的不确定性分析思路。该方法可以根据不同隶属度下的参数截集区间,计算出相应隶属度下的安全系数区间,并可由此得到边坡的可靠性指标和安全系数建议值。通过不同算例研究表明,使用此方法能充分考虑计算参数的不确定性,得到的安全系数更加科学可靠。 相似文献