技术方法的进步与地球科学的发展

地球科学作为自然科学的一大门类,其发展速度十分惊人。地球科学的迅速发展一方面反映了人类生产的发展对资源和环境方面愈来愈高的要求,一方面得益于科学技术的普遍发展为地球科学研究提供的越来越有利的条件。关于技术方法对地球科学研究的推动作用,人们早有认识,而现在更为深刻。当今对地球科学研究影响最大的关键技术,包括空间技术,深部探测技术,高新分析测试技术和数据综合分析技术,均来源于现代科学技术的最新发展。为了推动地球科学研究,不但要注意引进各种高新技术,还要注意将这些技术与地学研究相结合,发展和创造适合于地学研究的高新技术,并善于综合应用它们,使它们在地学研究中发挥最有效的作用。     

一种面向对象的三维地下空间矢量数据模型

针对地下空间的真三维连续特性以及建模过程的动态交互编辑与分析要求,提出了一种新的三维地下空间矢量数据模型。该模型采用面向对象思想对地下各种空间对象进行抽象描述;利用模型中的线段要素增强几何元素之间拓扑连接关系的维持,为地质体的切割和地下工程体的开挖等分析提供了算法上的便利;引入拓扑面更好地表达了地下空间对象之间的拓扑邻接关系。该模型在三维地下空间数据的存储管理、查询分析以及实时逼真绘制等方面都表现出较好的性能,适用于地下勘探工程的建模与分析。     

环境模拟和GIS集成的初步研究

GIS与环境模拟在技术、研究内容、方法上的进一步集成,具有广泛的应用前景.以开展的流域土壤和水资源研究模型的集成和系统化及其应用项目的实际工作,说明了环境模拟和GIS技术集成的必然性;从GIS技术的发展,环境模拟模型的改进与完善,数据的初始化与管理等方面系统地论述了环境模拟模型和GIS集成的必要性.通过现有集成模式的分析,对二者集成的概念框架以及不同的集成方式进行了概念性的描述,结合研究项目给出了集成示例.     

地下多组分反应溶质运移数值模拟:地质资源和环境研究的新方法

地下多组分反应溶质运移数值模拟(RTM)是解释地球系统中的耦合过程和不同时空尺度对其影响的重要工具。RTM是研究地球科学基础理论、地质资源和环境等复杂地球化学过程的一个新方法,可用于如废物处置安全性评估、地下水污染研究、二氧化碳地质储存、金属矿床的地浸开采等的研究中。笔者首先回顾了反应溶质溶质运移模拟的发展历史,然后总结了反应溶质运移模拟的发展现状,再从耦合过程、空间尺度、裂隙和非均质介质处理角度说明了反应溶质运移模拟所面临的挑战。结合地下水质的演化、生物降解、CO2地质储存等具体实例讨论了反应溶质运移模拟的广泛应用前景,探讨了反应溶质运移模拟的未来发展方向。     

A Fast Approximation for Seismic Inverse Modeling: Adaptive Spatial Resampling

Seismic inverse modeling, which transforms appropriately processed geophysical data into the physical properties of the Earth, is an essential process for reservoir characterization. This paper proposes a work flow based on a Markov chain Monte Carlo method consistent with geology, well-logs, seismic data, and rock-physics information. It uses direct sampling as a multiple-point geostatistical method for generating realizations from the prior distribution, and Metropolis sampling with adaptive spatial resampling to perform an approximate sampling from the posterior distribution, conditioned to the geophysical data. Because it can assess important uncertainties, sampling is a more general approach than just finding the most likely model. However, since rejection sampling requires a large number of evaluations for generating the posterior distribution, it is inefficient and not suitable for reservoir modeling. Metropolis sampling is able to perform an equivalent sampling by forming a Markov chain. The iterative spatial resampling algorithm perturbs realizations of a spatially dependent variable, while preserving its spatial structure by conditioning to subset points. However, in most practical applications, when the subset conditioning points are selected at random, it can get stuck for a very long time in a non-optimal local minimum. In this paper it is demonstrated that adaptive subset sampling improves the efficiency of iterative spatial resampling. Depending on the acceptance/rejection criteria, it is possible to obtain a chain of geostatistical realizations aimed at characterizing the posterior distribution with Metropolis sampling. The validity and applicability of the proposed method are illustrated by results for seismic lithofacies inversion on the Stanford VI synthetic test sets.     

基于LUCC和夜间灯光辐射数据的张掖市甘州区人口空间分布建模

尽管近年来统计数据的生成技术有了很大提高, 但可用的详细人口数据始终难以得到满足.在一些自然-人文要素耦合的建模研究中, 如生态经济集成建模、 环境和健康分析等都需要基于区域尺度的栅格人口分布建模方法.随着GIS和RS技术的发展, 上述建模方法已有较大进步.利用GIS技术, 基于夜间灯光辐射数据和LUCC在象元栅格水平上构建张掖市甘州区人口空间分布. 首先对DMSP夜间灯光辐射数据进行重采样, 通过普通克里金插值获得灯光数据; 然后与LUCC叠加分析, 利用回归分析的方法获取研究区土地利用、 灯光辐射指标和人口统计数据之间的定量关系, 完成空间化.并在乡镇尺度上进行模型检验, 模型总体的调整R²为0.88, 标准误差为400, 为下一步开展时空变化分析提供支持.     

The SISMA prototype system: integrating Geophysical Modeling and Earth Observation for time-dependent seismic hazard assessment

An innovative approach to seismic hazard assessment is illustrated that, based on the available knowledge of the physical properties of the Earth structure and of seismic sources, on geodetic observations, as well as on the geophysical forward modeling, allows for a time-dependent definition of the seismic input. According to the proposed approach, a fully formalized system integrating Earth Observation data and new advanced methods in seismological and geophysical data analysis is currently under development in the framework of the Pilot Project SISMA, funded by the Italian Space Agency. The synergic use of geodetic Earth Observation data (EO) and Geophysical Forward Modeling deformation maps at the national scale complements the space- and time-dependent information provided by real-time monitoring of seismic flow (performed by means of the earthquake prediction algorithms CN and M8S) and permits the identification and routine updating of alerted areas. At the local spatial scale (tens of km) of the seismogenic nodes identified by pattern-recognition analysis, both GNSS (Global Navigation Satellite System) and SAR (Synthetic Aperture Radar) techniques, coupled with expressly developed models for interseismic phase, allow us to retrieve the deformation style and stress evolution within the seismogenic areas. The displacement fields obtained from EO data provide the input for the geophysical modeling, which eventually permits to indicate whether a specific fault is in a “critical state.” The scenarios of expected ground motion (shakemaps) associated with the alerted areas are then defined by means of full waveforms modeling, based on the possibility to compute synthetic seismograms by the modal summation technique (neo-deterministic hazard assessment). In this way, a set of deterministic scenarios of ground motion, which refer to the time interval when a strong event is likely to occur within the alerted area, can be defined both at national and at local scale. The considered integrated approach opens new routes in understanding the dynamics of fault zones as well as in modeling the expected ground motion. The SISMA system, in fact, provides tools for establishing warning criteria based on deterministic and rigorous forward geophysical models and hence allows for a well-controlled real-time prospective testing and validation of the proposed methodology over the Italian territory. The proposed approach complements the traditional probabilistic approach for seismic hazard estimates, since it supplies routinely updated information useful in assigning priorities for timely mitigation actions and hence it is particularly relevant to Civil Defense purposes.     

On the role of Geography in Earth System Science

Geography is fundamentally a non-reductionist and holistic discipline. While we tend to focus on particular areas (Physical, Human, etc.), or we focus on specific successes (Quaternary studies for example) this paper argues that selling Geography though emphasizing these specific areas or strengths misses a major potential contribution our discipline can make. While most sciences have become reductionist over the last two centuries, they have recently discovered that the Earth is a “complex system” with “emergent” properties that cannot be explained through understanding the components parts individually. Many of these sciences are now contributing to a major effort called Earth System Science, an integrative super-discipline that accepts that biophysical sciences and social sciences are equally important in any attempts to understand the state, and future of the Earth System. This paper argues that the development of Earth System Sciences is a risk for Geography since it is, in effect, Geography with few Geographers. While representing a threat, the development of Earth System Science is also an opportunity. I argue that Geography could be a lead discipline among the other biophysical and social sciences that are now building Earth System Science to address key problems within the Earth System. While I am optimistic about the potential of Geography to take this leadership role, I am pessimistic about the likelihood that we will. I provide suggestions on how we might take on the leadership of Earth System Science including individual engagement and a refinement of tertiary training of some Geography students.     

一种基于似三棱柱体元的地质三维建模方法研究

三堆空间建模方法是三堆地劫工程GIS研究的核心问题之一。提出一种基于似三棱柱体元的三堆数据模型，模型包含顶点、线段(棱边、三角形边)、三角形、侧面四边形、三棱柱体元5个基本元素。和点对象、线对象、面对象、体对象、复杂对象、空间对象等6个对象。设计了5个基本元素和3种地质对象的数据结构和它们之间的拓扑关系。以岩体和巷道为例。给出了似三棱柱体建模思路和算法。利用内蒙古某矿区实际钻孔资料和模拟巷道数据对所开发的系统原型进行验证。研究表明。基于似三棱柱体元的数据模型的优势在于可以表示空间对象的表面和内部结构。便于建模和节省存储空间，同时便于不规劓的自然地质体和规则勘探工程建模。     

Fuzzy Modeling for Reserve Estimation Based on Spatial Variability

This article addresses a new reserve estimation method which uses fuzzy modeling algorithms and estimates the reserve parameters based on spatial variability. The proposed fuzzy modeling approach has three stages: (1) Structure identification and preliminary clustering, (2) Variogram analysis, and (3) Clustering based rule system. A new clustering index approach and a new spatial measure function (point semimadogram) are proposed in the paper. The developed methodology uses spatial variability in each step and takes the fuzzy rules from input-output data. The model has been tested using both simulated and real data sets. The performance evaluation indicates that the new methodology can be applied in reserve estimation and similar modeling problems     

A Spatial Correlation-Based Anomaly Detection Method for Subsurface Modeling

Spatial data analytics provides new opportunities for automated detection of anomalous data for data quality control and subsurface segmentation to reduce uncertainty in spatial models. Solely data-driven anomaly detection methods do not fully integrate spatial concepts such as spatial continuity and data sparsity. Also, data-driven anomaly detection methods are challenged in integrating critical geoscience and engineering expertise knowledge. The proposed spatial anomaly detection method is based on the semivariogram spatial continuity model derived from sparsely sampled well data and geological interpretations. The method calculates the lag joint cumulative probability for each matched pair of spatial data, given their lag vector and the semivariogram under the assumption of bivariate Gaussian distribution. For each combination of paired spatial data, the associated head and tail Gaussian standardized values of a pair of spatial data are mapped to the joint probability density function informed from the lag vector and semivariogram. The paired data are classified as anomalous if the associated head and tail Gaussian standardized values fall within a low probability zone. The anomaly decision threshold can be decided based on a loss function quantifying the cost of overestimation or underestimation. The proposed spatial correlation anomaly detection method is able to integrate domain expertise knowledge through trend and correlogram models with sparse spatial data to identify anomalous samples, region, segmentation boundaries, or facies transition zones. This is a useful automation tool for identifying samples in big spatial data on which to focus professional attention.

     

离心模型试验中微型土压力盒土压力测定

土压力作为离心模型试验中重要的测试参数,受土压力盒的性能、离心机数据采集系统稳定性及外部环境等诸多因素的影响,准确地测量土压力较为困难。土压力盒作为土压力测试元件,其性能对土压力测量准确性有直接影响。为获得较为准确的土压力测试数据,结合离心机数据采集系统,选择两种常见的电阻应变式土压力盒。通过标定试验得出两种土压力盒砂标系数均小于出厂标定系数,Ⅰ型偏小64.75%,Ⅱ型偏小18.77%,Ⅱ型土压力盒与出厂数据的重合度比Ⅰ型好;在研究墙高10～30 m类扶壁式挡墙侧向土压力分布的离心模型试验中,与Ⅱ型土压力盒相比,Ⅰ型存在按出厂系数测得数据失真、灵敏度低和稳定性差的缺点。标定试验和离心试验结果表明,接入自行组建的数据采集系统的Ⅱ型土压力盒比接入静态应变数据采集系统的Ⅰ型土压力盒性能更佳。     

A Comparative Study for 3D Surface Modeling of Coal Deposit by Spatial Interpolation Approaches

The planning stages of mining require comprehensive and detailed analyses. The proper determination of the orebody boundary is one of the most important points to provide optimum model structure and projections. The limits can be determined by different methods based on the site geology. Although some three dimensional (3D) models were proposed for providing detailed information concerning a mine deposit, developing a solid model via a 3D approach is novelty. In other words, surface modeling should be performed for creating a solid model and determining limits of the deposit. In this way, sensible generation of the surface model can be achieved. This study investigated the estimation capability of the polynomial approach, which is a novel spatial interpolation method, for modeling a coal deposit surface. The performance of the proposed model was compared with some conventional methods in the literature. The results showed that the polynomial interpolation method is an effective method to employ for surface modeling of a mine deposit.     

A spatial analysis method for geochemical anomaly separation

One purpose of using statistical methods in exploration geochemistry is to assist exploration geologists in separating anomalies from background. This always involves two types of negatively associated errors of misclassification: type I errors occur when samples with background levels are rejected as background; and type II errors occur when samples with anomalous values are accepted as background. A new spatial statistical approach is proposed to minimize errors of total misclassification using a moving average technique with variable window radius. This method has been applied for geochemical anomaly enhancement and recognition as demonstrated by a case study of Au and Au-associated data for 698 stream sediment samples in the Iskut River area, northwestern British Columbia. Similar results were obtained using the fractal concentration-area method on the same data. By employing spatial information in the analysis, the process of selecting anomalies becomes less subjective than in more traditional approaches.     

Investigation of Soil Conditioning Tests with Three-Dimensional Numerical Modeling

Due to the diverse and complex structure of soil and the variety of foam-modifier materials that are used, it is difficult to provide a model to predict the laboratory behavior of modified soils. For example, several studies have shown independently that the amount of the foam-modified soil depends on several factors, such as the internal friction angle and normal stiffness. Of late, modeling by numerical methods has become popular in engineering sciences and the modeling of complex material behavior is possible with the help of numerical methods. In this research, the performance and efficiency of the numerical method in the modeling of laboratory tests such as the slump test and the uniaxial compressive strength test were investigated and it was found that numerical modeling performs very well in predicting the results of these tests for foam-modified sand samples. In order to achieve this goal, the slump test and the uniaxial compressive strength test were performed in the laboratory on several modified sand samples in order to obtain the laboratory results for these samples. Then, numerical simulation of these experiments was carried out using PFC^3D software. The results of numerical modeling were compared with the experimental results, and good agreement was observed. Finally, after calibration of the numerical model using the experimental results, the effect of changes in the internal friction angle and the normal stiffness of the modified sand in the amount of the slump was investigated. According to the results of this sensitivity analysis, it was determined that by increasing both effective parameters the amount of the slump of foam-modified sand decreases and that the parameters are the most important factors in controlling the slump value.     

地球内部物理和演化的几个核心论题：Ⅲ微观地球物理概要

微地球物理是一正处酝酿阶段,以微物理学为基础,以地球内部及地质休和冉石物理特性搂研究对象,以理论、实验、数据和计算机模拟为手段的新兴学科。其研究内容涉及地球内部受多种微物理机制所制约的岩石圈和地幔流变,岩石动力摩擦与地壳脆－塑性转换,地震和断裂力学问题,流体－岩石相互作用,声发射／微震活动与声波／超声波理论和地质应用等。结合其动力学和相互耦合关系,是微地球物理学的一个重要研究方向。其应用结果将导致环境地球物理和环境地球化学并行发展。关于地球内部的认识存在相当的不确定性,有些问题如板块和地幔涌运动,以致微破裂和断层滑移运动等都可能涉及随机和无序理论的应用。微观与宏观方法的结合,并使两者相一致,是最终解决问题的必要途径和工作目标。     

成矿环境空间结构的模糊建模

为了提高矿产预测的精度和可靠性, 必须分析和利用与矿床有关的空间结构信息.提出了一种用模糊集建立成矿环境空间结构模型的方法.成矿环境空间结构是地质变量在矿床周围的分布, 可用变量与空间点之间的模糊关系来描述.同一地区的同类矿床, 其空间结构具有一定相似性, 通过这种相似性的极大化可对结构模型进行优化.优化的结构模型是一种包含了方向和距离关系的特殊的空间关联规则集, 也是模糊推理矿产预测的推理规则库.通过模糊推理进行结构相似性的比较, 可对任意点上的找矿有利性进行预测.以云南东川地区铜矿预测的实例说明了该方法具有良好的应用效果.      

地球系统科学研究与网络技术

地球系统科学研究是项十分复杂的系统工程，它涉及到地质学，地理学，海洋学，土壤学，大气科学，生命科学，化学，物理学以及信息科学和社会学等多门学科，网络的迅速发展给地球系统科学研究提供了机遇，作者在文中分析了当今网络的先进技术与地球系统科学研究的关系，提出了网络将对其研究产生深远的影响。     

Tertiary education requirements in the geosciences for the minerals industry and in the environmental field to meet the demands of the 21st century in South Africa

South and southern Africa are currently facing a major skills shortage in the applied earth sciences, particularly in the minerals industry and in the environmental field. This paper offers outlines of course curricula, developed in South Africa, which are designed to meet these needs.It is argued that insufficient time is devoted to applied geology in degree courses in South Africa and that appropriate specialisations should be introduced into the third and fourth years of Earth Science degrees. More detailed specialisation should be offered at master's level. Examples of such courses currently run in South Africa are cited.The important contribution of the earth sciences to contemporary environmental issues is stressed and the need for environmental geologists emphasised. It is argued that the huge amount of information essential to environmental geology requires postgraduate level teaching of this subject. An example of such a master's level course is taken from a course planned at the University of the Witwatersrand.Courses similar to those being developed in southern Africa need to be developed in other African regions.     

Non-parametric machine learning methods for interpolation of spatially varying non-stationary and non-Gaussian geotechnical properties

Spatial interpolation has been frequently encountered in earth sciences and engineering.A reasonable appraisal of subsurface heterogeneity plays a significant role in planning,risk assessment and decision making for geotechnical practice.Geostatistics is commonly used to interpolate spatially varying properties at un-sampled locations from scatter measurements.However,successful application of classic geostatistical models requires prior characterization of spatial auto-correlation structures,which poses a great challenge for unexperienced engineers,particularly when only limited measurements are available.Data-driven machine learning methods,such as radial basis function network(RBFN),require minimal human intervention and provide effective alternatives for spatial interpolation of non-stationary and non-Gaussian data,particularly when measurements are sparse.Conventional RBFN,however,is direction independent(i.e.isotropic)and cannot quantify prediction uncertainty in spatial interpolation.In this study,an ensemble RBFN method is proposed that not only allows geotechnical anisotropy to be properly incorporated,but also quantifies uncertainty in spatial interpolation.The proposed method is illustrated using numerical examples of cone penetration test(CPT)data,which involve interpolation of a 2D CPT cross-section from limited continuous 1D CPT soundings in the vertical direction.In addition,a comparative study is performed to benchmark the proposed ensemble RBFN with two other non-parametric data-driven approaches,namely,Multiple Point Statistics(MPS)and Bayesian Compressive Sensing(BCS).The results reveal that the proposed ensemble RBFN provides a better estimation of spatial patterns and associated prediction uncertainty at un-sampled locations when a reasonable amount of data is available as input.Moreover,the prediction accuracy of all the three methods improves as the number of measurements increases,and vice versa.It is also found that BCS prediction is less sensitive to the number of measurement data and outperforms RBFN and MPS when only limited point observations are available.