On three-dimensional geological modeling and visualization

3D geological modeling and visualization are the key technique issues to implement the plan of 揇igital Earth? At present, the major difficulties in 3D geo-logical modeling are as follows[1—5]: (1) 3D spatial data are difficult to acquire. What 3D geological modeling of complex objects and visu-alization depend on is the original data. However, it is very difficult to establish 3D complex geological models when the sampled data are sparse and insuffi-cient, the seismic profile data are lack…     

An integrated model to simulate sown area changes for major crops at a global scale

Dynamics of land use systems have attracted much attention from scientists around the world due to their ecological and socio-economic implications. An integrated model to dynamically simulate future changes in sown areas of four major crops (rice, maize, wheat and soybean) on a global scale is pre- sented. To do so, a crop choice model was developed on the basis of Multinomial Logit (Logit) model to model land users' decisions on crop choices among a set of available alternatives with using a crop utility function. A GIS-based Environmental Policy Integrated Climate (EPIC) model was adopted to simulate the crop yields under a given geophysical environment and farming management conditions, while the International Food Policy and Agricultural Simulation (IFPSIM) model was utilized to estimate crop price in the international market. The crop choice model was linked with the GIS-based EPIC model and the IFPSIM model through data exchange. This integrated model was then validated against the FAO statistical data in 2001-2003 and the Moderate Resolution Imaging Spectroradiometer (MODIS) global land cover product in 2001. Both validation approaches indicated reliability of the model for ad- dressing the dynamics in agricultural land use and its capability for long-term scenario analysis. Finally, the model application was designed to run over a time period of 30 a, taking the year 2000 as baseline. The model outcomes can help understand and explain the causes, locations and consequences of land use changes, and provide support for land use planning and policy making.     

An explicit four-dimensional variational data assimilation method based on the proper orthogonal decomposition: Theoretics and evaluation

The proper orthogonal decomposition (POD) method is used to construct a set of basis functions for spanning the ensemble of data in a certain least squares optimal sense. Compared with the singular value decomposition (SVD), the POD basis functions can capture more energy in the forecast ensemble space and can represent its spatial structure and temporal evolution more effectively. After the analysis variables are expressed by a truncated expansion of the POD basis vectors in the ensemble space, the control variables appear explicitly in the cost function, so that the adjoint model, which is used to derive the gradient of the cost function with respect to the control variables, is no longer needed. The application of this new technique significantly simplifies the data assimilation process. Several assimilation experiments show that this POD-based explicit four-dimensional variational data assimilation method performs much better than the usual ensemble Kalman filter method on both enhancing the assimilation precision and reducing the computation cost. It is also better than the SVD-based explicit four-dimensional assimilation method, especially when the forecast model is not perfect and the forecast error comes from both the noise of the initial filed and the uncertainty of the forecast model. Supported by the National Natural Science Foundation of China (Grant No. 40705035), National High Technology Research and Development Program of China (Grant No. 2007AA12Z144), Knowledge Innovation Project of Chinese Academy of Sciences (Grant Nos. KZCX2-YW-217 and KZCX2-YW-126-2), and National Basic Research Program of China (Grant No. 2005CB321704)     

基于先验信息约束的重磁三维交互反演建模技术——以铜陵矿集区为例

三维地质建模是实现深部矿产勘查突破的重要途径,其通过控矿地质体的三维建模,直观刻画控矿要素之间的空间、成因和演化关系,帮助理解成矿系统,开展深部找矿预测.当前三维建模主要采用地质资料构建,在缺少钻孔等已知资料的情况下,难于构建出可靠的三维地质模型.为了克服常规三维地质建模方法可信度低、精度差的缺点,本文将重磁交互反演技术引入到三维地质建模中,提出了基于先验信息约束,通过二度半剖面交互反演、三维物性反演联合修正的三维地质模型方法.采用该方法建立了铜陵矿集区的三维地质模型,并开展了深部找矿预测,取得以下主要认识:1)基于先验信息约束的重磁交互反演建模技术能大幅提高三维地质模型的可信度,是实现地下地质体"透明化"的重要途径;2)铜陵地区重要控矿地层(C-P-T2)主要分布于向斜区和火山岩覆盖区,深部岩浆岩条件优越,深部找矿工作应从传统的背斜隆起区转向向斜区和火山岩覆盖区以及部分凹陷区,这将极大拓展铜陵地区找矿空间;3)铜陵地区传统的五大矿田的侵入岩均具有复合岩体特征,特别是与辉石闪长岩共生的矿产以铁铜矿为主,而与金矿密切相关的侵入岩则多为中酸性岩体,这一推断如果成立,将对铜陵地区找矿突破产生重大影响;4)铜陵地区的推覆构造十分发育,木镇凹陷区的早古生代基底和南陵盆地北西缘的戴公山背斜就是一套区域性推覆构造的产物,三维地质模型还揭示铜陵地区侵入岩具有深、中、浅三重结构,这为铜陵隆起的推覆成因提供了证据,也指示了在铜陵之外再寻找类似铜陵矿集区的良好前景.     

Three-dimensional geological modeling and its application in Digital Mine

The 3D geological modeling is the prerequisite and core foundation for Digital Mine. Although this new technology brings new opportunities and motivation for the mineral exploration industry, it still has many difficulties to be solved in this area. Based on the characteristics of mine data and the aim of Digital Mine construction, this paper introduces a theory including multi-source data coupling, multi-modeling methods integration, multi-resolution visualization and detection, and multidimensional data analysis and application. By analyzing problems such as the uncertainty in each step of the modeling process, we designed a novel modeling method that can be applied to the complex geological body modeling, mineral resource/reserve estimation, and the mining exploration engineering. Along with the process of mine exploration, development, and reclamation, 3D modeling undergoes the process of “construction-simulation-revision” during which the 3D model is able to be dynamically updated and gradually improved. Based on the result of practical utilization, it is proven that the methodology introduced by this paper can be used to build an effective 3D model by fully using the mining data under the control of spatial information quality evaluation. Our experiments show that such a 3D model can be used to evaluate the mine resource and provide the scientific evidence to improve mining efficiency during the various stages of evolvement process in mine.     

The Handling of Hazard Data on a National Scale: A Case Study from the British Geological Survey

This paper reviews how hazard data and geological map data have been combined by the British Geological Survey (BGS) to produce a set of GIS-based national-scale hazard susceptibility maps for the UK. This work has been carried out over the last 9 years and as such reflects the combined outputs of a large number of researchers at BGS. The paper details the inception of these datasets from the development of the seamless digital geological map in 2001 through to the deterministic 2D hazard models produced today. These datasets currently include landslides, shrink-swell, soluble rocks, compressible and collapsible deposits, groundwater flooding, geological indicators of flooding, radon potential and potentially harmful elements in soil. These models have been created using a combination of expert knowledge (from both within BGS and from outside bodies such as the Health Protection Agency), national databases (which contain data collected over the past 175 years), multi-criteria analysis within geographical information systems and a flexible rule-based approach for each individual geohazard. By using GIS in this way, it has been possible to model the distribution and degree of geohazards across the whole of Britain.     

Fhe application of electromagnetic-induction on the measurement of sea ice thickness in the Antarctic

As an important component of the cryosphere, sea ice is very sensitive to climate change. The study of sea ice physics needs accurate sea ice thickness. This paper presents an electromagnetic induction （EM） technique which can be used to measure the sea ice thickness distribution efficiently and its successful application in the Antarctic Neila Fjord. Based on the electrical properties of sea ice and seawater and the application of electromagnetic field theory, this technique can accurately detect the distance between the EM instrument and the ice/water interface to measure the sea ice thickness. Analyzing the apparent conductivity data obtained by the electromagnetic induction technique and drill-hole measurements at same location allows the construction of a transform equation for the apparent conductivity and sea ice thickness. The verification of the calculated sea ice thickness using this equation indicates that the electromagnetic induction technique is able to determine reliable sea ice thickness with an average relative error of only 5.5%. The ice thickness profiles show the sea ice distribution in Neila Fjord is basically level with a thickness of 0.8 - 1.4 m.     

Assessing hydrological model predictive uncertainty using stochastically generated geological models

In distributed and coupled surface water–groundwater modelling, the uncertainty from the geological structure is unaccounted for if only one deterministic geological model is used. In the present study, the geological structural uncertainty is represented by multiple, stochastically generated geological models, which are used to develop hydrological model ensembles for the Norsminde catchment in Denmark. The geological models have been constructed using two types of field data, airborne geophysical data and borehole well log data. The use of airborne geophysical data in constructing stochastic geological models and followed by the application of such models to assess hydrological simulation uncertainty for both surface water and groundwater have not been previously studied. The results show that the hydrological ensemble based on geophysical data has a lower level of simulation uncertainty, but the ensemble based on borehole data is able to encapsulate more observation points for stream discharge simulation. The groundwater simulations are in general more sensitive to the changes in the geological structure than the stream discharge simulations, and in the deeper groundwater layers, there are larger variations between simulations within an ensemble than in the upper layers. The relationship between hydrological prediction uncertainties measured as the spread within the hydrological ensembles and the spatial aggregation scale of simulation results has been analysed using a representative elementary scale concept. The results show a clear increase of prediction uncertainty as the spatial scale decreases. Copyright © 2015 John Wiley & Sons, Ltd.     

Characteristics of shallow gas hydrate in Okhotsk Sea

Multidisciplinary field investigations were carried out in Okhotsk Sea by R/V Akademik M.A. Lavrentyev (LV) of the Russian Academy of Sciences (RAS) in May 2006, supported by funding agencies from Ko- rea, Russia, Japan and China. Geophysical data including echo-sounder, bottom profile, side-scan- sonar, and gravity core sample were obtained aimed to understand the characteristics and formation mechanism of shallow gas hydrates. Based on the geophysical data, we found that the methane flare detected by echo-sounder was the evidence of free gas in the sediment, while the dome structure de- tected by side-scan sonar and bottom profile was the root of gas venting. Gas hydrate retrieved from core on top of the dome structure which was interbedded as thin lamination or lenses with thickness varying from a few millimeters to 3 cm. Gas hydrate content in hydrate-bearing intervals visually amounted to 5%―30% of the sediment volume. This paper argued that gases in the sediment core were not all from gas hydrate decomposition during the gravity core lifting process, free gases must existed in the gas hydrate stability zone, and tectonic structure like dome structure in this paper was free gas central, gas hydrate formed only when gases over-saturated in this gas central, away from these struc- tures, gas hydrate could not form due to low gas concentration.     

Hydrological modelling using proxies for gauged precipitation and temperature

Precipitation and temperature time series suffer from many problems, such as short time, inadequate spatial coverage, missing data, and biases from various causes, which are particularly critical in remote areas such as Northern Canada. The development of alternative datasets for using as proxies for inadequate/missing weather data represents a key research area. In this paper, the performance of 6 alternative datasets is evaluated for hydrological modelling over 12 watersheds located across Canada and the contiguous United States. The datasets can be classified into 3 distinct categories: (a) interpolated gridded data, (b) reanalysis data, and (c) climate model outputs. Hydrological simulations were carried out using a lumped conceptual hydrological model calibrated using standard weather data and compared against results using a calibration specific to each alternative dataset. Prior to the hydrological simulations, the alternative datasets were all evaluated with respect to their ability to reproduce gridded daily precipitation and temperature characteristics over North America. The results show that both the reanalysis data and climate model data adequately represent the spatial pattern of daily precipitation and temperature over North America. The North American Regional Reanalysis (NARR) dataset consistently shows the best performance. With respect to hydrological modelling, the observed discharges are accurately represented by both the gridded and NARR datasets, and more so for the NARR data. The National Centers for Environmental Prediction dataset consistently performs worst as it is unable to even capture the seasonal pattern of observed streamflow for 3 out of the 12 watersheds. These results indicate that the NARR dataset could be used as a proxy for gauged precipitation and temperature for hydrological modelling over watersheds where observational datasets are deficient. The results also illustrate the ability of climate model data to be used for performing hydrological modelling when driven by reanalysis data at their boundaries, and especially so for high‐resolution models.     

Imaging a 3D geological structure from HEM, airborne magnetic and ground ERT data in Kalat-e-Reshm area, Iran

A set of geophysical data collected in an area in Iran are analyzed to check the validity of a geological map that was prepared in connection to a mineral prospecting project and also to image the spatial electrical resistivity distribution. The data set includes helicopter electromagnetic (HEM), airborne magnetic and ground electrical resistivity measurement. Occam approach was used to invert the HEM data to model the resistivity using a layered earth model with fixed thicknesses. The algorithm is based on a nonlinear inverse problem in a least-squares sense.The algorithm was tested on a part of an HEM dataset acquired with a DIGHEM helicopter EM system at Kalat-e-Reshm, Semnan in Iran. The area contains a resistive porphyry andesite that is covered by Eocene sedimentary units. The results are shown as resistivity sections and maps confirming the existence of an arc like resistive structure in the survey area. The resistive andesite seems to be thicker than it is indicated in the geological maps. The results are compared with the reduced to the pole (RTP) airborne magnetic anomaly field data as well as with two ground resistivity profiles. We found reasonable correlations between the HEM 1D resistivity models and 2D models from electrical resistivity tomography (ERT) inversions. A 3D visualization of the 1D models along all flight lines provided a useful tool for the study of spatial variations of the resistivity structure in the investigation area.     

Directional hydrostratigraphic units simulation using MCP algorithm

Understanding the geological uncertainty of hydrostratigraphic models is important for risk assessment in hydrogeology. An important feature of sedimentary deposits is the directional ordering of hydrostratigraphic units (HSU). Geostatistical simulation methods propose efficient algorithm for assessing HSU uncertainty. Among different geostatistical methods to simulate categorical data, Bayesian maximum entropy method (BME) and its simplified version Markov-type categorical prediction (MCP) present interesting features. In particular, the zero-forcing property of BME and MCP can provide a valuable constrain on directional properties. We illustrate the ability of MCP to simulate vertically ordered units. A regional hydrostratigraphic system with 11 HSU and different abundances is used. The transitional deterministic model of this system presents lateral variations and vertical ordering. The set of 66 (11 × 12/2) bivariate probability functions is directly calculated on the deterministic model with fast Fourier transform. Despite the trends present in the deterministic model, MCP is unbiased for the HSU proportions in the non-conditional case. In the conditional cases, MCP proved robust to datasets over-representing some HSU. The inter-realizations variability is shown to closely follow the amount and quality of data provided. Our results with different conditioning datasets show that MCP replicates adequately the directional units arrangement. Thus, MCP appears to be a practical method for generating stochastic models in a 3D hydrostratigraphic context.     

3D modeling of geological anomalies based on segmentation of multiattribute fusion

3D modeling of geological bodies based on 3D seismic data is used to define the shape and volume of the bodies, which then can be directly applied to reservoir prediction, reserve estimation, and exploration. However, multiattributes are not effectively used in 3D modeling. To solve this problem, we propose a novel method for building of 3D model of geological anomalies based on the segmentation of multiattribute fusion. First, we divide the seismic attributes into edge- and region-based seismic attributes. Then, the segmentation model incorporating the edge- and region-based models is constructed within the levelset-based framework. Finally, the marching cubes algorithm is adopted to extract the zero level set based on the segmentation results and build the 3D model of the geological anomaly. Combining the edge-and region-based attributes to build the segmentation model, we satisfy the independence requirement and avoid the problem of insufficient data of single seismic attribute in capturing the boundaries of geological anomalies. We apply the proposed method to seismic data from the Sichuan Basin in southwestern China and obtain 3D models of caves and channels. Compared with 3D models obtained based on single seismic attributes, the results are better agreement with reality.     

A geographic data model for representing ground water systems

The Arc Hydro ground water data model is a geographic data model for representing spatial and temporal ground water information within a geographic information system (GIS). The data model is a standardized representation of ground water systems within a spatial database that provides a public domain template for GIS users to store, document, and analyze commonly used spatial and temporal ground water data sets. This paper describes the data model framework, a simplified version of the complete ground water data model that includes two-dimensional and three-dimensional (3D) object classes for representing aquifers, wells, and borehole data, and the 3D geospatial context in which these data exist. The framework data model also includes tabular objects for representing temporal information such as water levels and water quality samples that are related with spatial features.     

Fast and dynamic generation of linear octrees for geological bodies under hardware acceleration

In the application of 3D Geoscience Modeling,we often need to generate the volumetric representations of geological bodies from their surface representations.Linear octree,as an efficient and easily operated volumetric model,is widely used in 3D Geoscience Modeling.This paper proposes an algorithm for fast and dynamic generation of linear octrees of geological bodies from their surface models under hardware acceleration.The Z-buffers are used to determine the attributes of octants and voxels in a fast way,a...     

基于局部一维模型与走时标定的区域 三维速度模型构建技术研究

构建区域介质三维速度模型并以之获得准确的区域震相走时, 是提高区域地震定位精度的重要手段之一. 为充分利用已有的一维模型、 GT事件、 地质资料等实现三维模型构建, 尝试基于目标区域内已有的部分局部一维模型, 通过克里金空间插值建立初始三维模型, 然后利用GT事件走时数据并参考其它地震地质资料对其不断进行修正, 使得其走时偏差图与GT事件走时偏差图一致, 进而获得能够提高区域地震定位精度的三维模型. 使用不同模型进行的地震定位实验表明, 以此方法建立的三维模型的定位偏差较初始模型减少约20%, 较好地起到了减小区域震相走时残差, 提高区域地震定位精度的作用.      

Distributed modeling of monthly air temperatures over the rugged terrain of the Yellow River Basin

Our analyses of the monthly mean air temperature of meteorological stations show that altitude, global solar radiation and surface effective radiation have a significant impact on air temperature. We set up a physically-based empirical model for monthly air temperature simulation. Combined the proposed model with the distributed modeling results of global solar radiation and routine meteorological observation data, we also developed a method for the distributed simulation of monthly air temperatures over rugged terrain. Spatial distribution maps are generated at a resolution of 1 km×1 km for the monthly mean, the monthly mean maximum and the monthly mean minimum air temperatures for the Yellow River Basin. Analysis shows that the simulation results reflect to a considerable extent the macro and local distribution characteristics of air temperature. Cross-validation shows that the proposed model displays good stability with mean absolute bias errors of 0.19°C–0.35°C. Tests carried out on local meteorological station data and case year data show that the model has good spatial and temporal simulation capacity. The proposed model solely uses routine meteorological data and can be applied easily to other regions. Supported by China Meteorological Administration key Project on New Technique Diffusion (Grant No. CMATG2006Z10) and Jiangsu Key Laboratory of Meteorological Disasters (Grant No. KLME050102)     

A ubiquitous knowledgeable data representation model (UKRM) for three-dimensional geographic information systems (3D GIS)

In the face of complicated, diversified three-dimensional world, the existing 3D GIS data models suffer from certain issues such as data incompatibility, insufficiency in data representation and representation types, among others. It is often hard to meet the requirements of multiple application purposes (users) related to GIS spatial data management and data query and analysis, especially in the case of massive spatial objects. In this study, according to the habits of human thinking and recognition, discrete expressions (such as discrete curved surface (DCS), and discrete body (DB)) were integrated and two novel representation types (including function structure and mapping structure) were put forward. A flexible and extensible ubiquitous knowledgeable data representation model (UKRM) was then constructed, in which structurally heterogeneous multiple expressions (including boundary representation (B-rep), constructive solid geometry (CSG), functional/parameter representation, etc.) were normalized. GIS’s ability in representing the massive, complicated and diversified 3D world was thus greatly enhanced. In addition, data reuse was realized, and the bridge linking static GIS to dynamic GIS was built up. Primary experimental results illustrated that UKRM was overwhelmingly superior to the current data models (e.g. IFC, CityGML) in describing both regular and irregular spatial objects.     

Stochastic earthquake source model for ground motion simulation

In the analysis and design of important structures with relatively long life spans, there is a need to generate strong motion data for possible large events. The source of an earthquake is characterized by the spatial distribution of slip on the fault plane. For future events, this is unknown. In this paper, a stochastic earthquake source model is developed to address this issue. Here, 1D and 2D stochastic models for slip distribution developed by Lavallée et al.(2006) are used. The random field associated with the slip distribution is heavy-tailed stable distribution which can be used for large events. Using 236 past rupture models, the spectral scaling parameter and the four stable or Levy's parameters against empirical relationship for known quantities like magnitude or fault length are developed. The model is validated with data from 411 stations of 1999 Chi-Chi earthquake. The simulated response spectrum showed good agreement to actual data. Further the proposed model is used to generate ground motion for the 1993 Killari Earthquake where strong motion data is not available. The simulated mean peak ground velocity was in turn related to the intensity(MSK) and compared against values in the literature.     

Effects of fault geometry and slip style on near-fault static displacements caused by the 1999 Chi-Chi,Taiwan earthquake

We investigated the fault geometry effects and the corresponding coseismic slip distribution using various proposed earthquake fault models for the Chi-Chi earthquake of 21 September 1999. The types of fault geometries are threefold: a simple planar fault plane, a two segmented planar fault plane and a three dimensional (3D) curved fault surface rupture propagation model. We derived the estimated spatial slip distribution from an inversion analysis of GPS coseismic displacement data and show that the 3D fault model is the preferred solution. The simple and segmented fault models lead to significant artificial slip distributions associated with the pre-defined fault geometry and the spatial distribution of GPS stations. The spatial distribution of coseismic slip deduced from the 3D fault model has three observable features: (1) the overall slip is concentrated at depth of less than 12 km, which may well correspond to a shallow-dipping detachment; (2) the maximum slip of about 10 m is located 45 km to the north of the epicenter; and (3) the slip vector is dominated by the dip-slip component. In addition, the results from the inversion of GPS data are consistent with those from the inversion analysis of teleseismic broadband data. A resolution analysis, further, demonstrates that the results are highly correlated with field GPS data studies when we used synthetic test data. The inversion of spatially distributed GPS data is highly sensitive to fault geometry. We conclude that the use of the 3D fault model is not only necessary but also certainly competent enough to well explain the inferred slip style and the observed static coseismic displacements.