Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.     

华南（东）变质基底特征、古构造型式及铀、金矿化远景

华南（东）变质基底由杨子及华夏两块不同特征的地质体组成，中元古代之后，该地区分别经过了碰撞对接、拉开、再拼贴的演化过程。碰撞对接带和在古裂谷系基础上成型的陆内推覆及平移、剪切型拼贴带构成了本区基底构造主要型式。铀及金矿远景与基底特征关系密切，铀矿主要产于基底裂隆带部位，金则主要产于裂凹（裂陷）带部位。古基底构造交叉部位是中新生代构造活动活跃部位，受其控制的早期横向火山裂谷盆地，在晚期拉张条件下形成的岩浆杂岩带是铀、金、多金属成矿最佳远景区。     

桃山、诸广复式岩体花岗岩类岩石铀、钍地球化学特征

通过对桃山、诸广复式岩体的深入研究,得出铀、钍元素在本地区花岗岩中具有以下地球化学特征及地球化学行为:1.岩体的铀、钍丰度与岩体外接触带的变质岩铀,钍丰度具同步增长特点;2.铀与硅、钾、钠关系密切,并有随钾增长,及随铀增长二种趋势,而钍则与TiO_2、FeO、MnO关系密切;3.钍在花岗岩中分布型式为正态分布,变异系数较铀小,而铀在花岗岩中分布型式为正态分布及对数正态分布,变异系数略高,显示了铀有某种富集可能;4.铀在花岗岩中地球化学行为,表现有二个富集高峰,既有在结晶早期富集在各类副矿物中的早富集特征,也有随花岗岩形成和演化富集在晚期的晚富集特征。二个富集途径,即随Si、K增高和随Si、Na增高途径。     

Multi-scale aquifer characterization and groundwater flow model parameterization using direct push technologies

Direct push (DP) technologies are typically used for cost-effective geotechnical characterization of unconsolidated soils and sediments. In more recent developments, DP technologies have been used for efficient hydraulic conductivity (K) characterization along vertical profiles with sampling resolutions of up to a few centimetres. Until date, however, only a limited number of studies document high-resolution in situ DP data for three-dimensional conceptual hydrogeological model development and groundwater flow model parameterization. This study demonstrates how DP technologies improve building of a conceptual hydrogeological model. We further evaluate the degree to which the DP-derived hydrogeological parameter K, measured across different spatial scales, improves performance of a regional groundwater flow model. The study area covers an area of ~60 km² with two overlying, mainly unconsolidated sand aquifers separated by a 5–7 m thick highly heterogeneous clay layer (in north-eastern Belgium). The hydrostratigraphy was obtained from an analysis of cored boreholes and about 265 cone penetration tests (CPTs). The hydrogeological parameter K was derived from a combined analysis of core and CPT data and also from hydraulic direct push tests. A total of 50 three-dimensional realizations of K were generated using a non-stationary multivariate geostatistical approach. To preserve the measured K values in the stochastic realizations, the groundwater model K realizations were conditioned on the borehole and direct push data. Optimization was performed to select the best performing model parameterization out of the 50 realizations. This model outperformed a previously developed reference model with homogeneous K fields for all hydrogeological layers. Comparison of particle tracking simulations, based either on the optimal heterogeneous or reference homogeneous groundwater model flow fields, demonstrate the impact DP-derived subsurface heterogeneity in K can have on groundwater flow and solute transport. We demonstrated that DP technologies, especially when calibrated with site-specific data, provide high-resolution 3D subsurface data for building more reliable conceptual models and increasing groundwater flow model performance.     

Optimum aim point biasing in case of a planetary quarantine constraint

Because of the tremendous importance attached to the conclusive demonstration of the presence or absence of extraterrestrial life in the solar system, many scientists have expressed concern that unsterile spacecraft contaminate other planets with terrestrial organisms. In response to this concern, NASA has initiated a planetary quarantine program, allowing a certain probability of impact for each mission.This paper will discuss how planetary quarantine affects midcourse guidance. In the first part the concept of a quarantine contour will be introduced, in the second part it will be shown how to find the optimum biased aim points on this contour in order to minimize midcourse requirements.     

Identification of heterogeneous aquifer transmissivity using an AE-based method

Determination of hydraulic head, H, as a function of spatial coordinates and time, in ground water flow is the basis for aquifer management and for prediction of contaminant transport. Several computer codes are available for this purpose. Spatial distribution of the transmissivity, T(x,y), is a required input to these codes. In most aquifers, T varies in an erratic manner, and it can be characterized statistically in terms of a few moments: the expected value, the variance, and the variogram. Knowledge of these moments, combined with a few measurements, permits one to estimate T at any point using geostatistical methods. In a review of transmissivity data from 19 unconsolidated aquifers, Hoeksema and Kitanidis (1985) identified two types of the logtransmissivity Y= ln(T) variations: correlated variations with variance sigma2Yc and correlation scale, I(Y), on the order of kilometers, and uncorrelated variations with variance sigma2Yn. Direct identification of the logtransmissivity variogram, Gamma(Y), from measurements is difficult because T data are generally scarce. However, many head measurements are commonly available. The aim of the paper is to introduce a methodology to identify the transmissivity variogram parameters (sigma2Yc, I(Y), and sigma2Yn) using head data in formations characterized by large logtransmissivity variance. The identification methodology uses a combination of precise numerical simulations (carried out using analytic element method) and a theoretical model. The main objective is to demonstrate the application of the methodology to a regional ground water flow in Eagle Valley basin in west-central Nevada for which abundant transmissivity and head measurements are available.     

再论华南（东）晋宁－加里东海盆地形成、演化及封闭

华南（东）晋宁－加里东海盆地形成于青白口纪，经历了晋宁期，加里东早期及加里东晚期３个演化阶段。海盆地基底为陆壳，形成于拉伸的裂谷环境，海盆地的封闭以陆内俯冲及拼贴为主，具多阶段性。海盆地基底，特别是华夏地块基底高热值属性导致了加里东海盆地有湘桂海盆地和赣闽粤海盆地２种类型，后者位于华夏基底之上，活动性明显，形成数条陆内动力热流变质带。     

An exact solution of solute transport by one-dimensional random velocity fields

The problem of one-dimensional transport of passive solute by a random steady velocity field is investigated. This problem is representative of solute movement in porous media, for example, in vertical flow through a horizontally stratified formation of variable porosity with a constant flux at the soil surface. Relating moments of particle travel time and displacement, exact expressions for the advection and dispersion coefficients in the Focker-Planck equation are compared with the perturbation results for large distances. The first- and second-order approximations for the dispersion coefficient are robust for a lognormal velocity field. The mean Lagrangian velocity is the harmonic mean of the Eulerian velocity for large distances. This is an artifact of one-dimensional flow where the continuity equation provides for a divergence free fluid flux, rather than a divergence free fluid velocity.