基于华北区域地震活动性分布的地震危险性评价模型

采用了分布式地震活动性模型. 该模型无需潜在震源区划分,同时简化了地震危险性概率分析方法. 根据破坏性地震目录建立了3个地震活动性模型,利用高斯光滑函数获得了华北区域内的a值分布特征,使用3种典型的衰减模型,分别计算了50年内超越概率10%, 5%和2%的地震动峰值加速度分布. 其分析结果显示了峰值加速度分布特征与我国第四代区划图大体一致,特定地震活动区（太原、 石家庄等地区）的峰值加速度略高于第四代区划图的结果,而这种峰值加速度分布特征与该地区较高的地震活动性特征是一致的. 概率危险性曲线结果表明,唐山、太原和北京等地区的潜在地震危险性比华北区域内其它城市高.      

Change of Support for Estimating Local Block Grade Distributions

An important aspect in mineral resource evaluation is the reduction of variance when post-processing the grade distributions defined on the support (volume) of the available data into distributions defined on the support of the proposed selective mining units. Although the volume-variance relationship is well understood for the estimation of global grade distributions, it is still an unsolved issue for local estimation studies based on non-parametric geostatistical methods, such as indicator kriging, for which the support correction is not inherent to the method. To clarify this relationship, the local change of support problem is examined in the scope of two parametric models (multi-Gaussian and discrete Gaussian models). It is shown that the variance reduction factor between point and block-support local distributions depends on the block being considered and is less than the global variance reduction factor. As a consequence, post-processing the local point-support grade distributions on the basis of the latter systematically understates the importance of the change of support at the local scale and makes selective mining appear more economically attractive than it really is. In the light of these results, a methodology is proposed to post-process the local point-support distributions obtained via non-parametric (indicator) methods into block-support distributions. An application to simulated data indicates that this methodology provides an accurate estimation at the block support when dealing with diffusion-type random fields.     

A Combined-Power Model for the Distribution of Axial Force in Shaft Anchor along Its Length

INTRODUCTIONThe anchorage of geomaterial , including shaftanchors and prestressed tendons ,is usually used ingeotechnical engineering. Owing to various advanta-ges ,these two anchorage types are widely used instructures in China ( Cao et al ., 2003 ; Fu et al .,1999 ;Lu et al .,1998 ; Li et al .,1995) . Shaft an-chors can be classifiedinto three kinds by the forceinthe shaft and cement grout :tensile ,press ,and sheartype (Lu et al .,1998) . The tensile type is the mostpopular in China…     

河北大茂山碘化银地面发生器增雪作业影响分析

利用常规气象资料、MICAPS资料和NECP/NCAR再分析资料,结合高斯模拟,分析了2012年11月10日唐县大茂山地基碘化银发生器增雪作业的作业条件。结果发现,此次天气背景为自西南向东北移动的冷涡云系,根据帕斯奎尔(Pasquill)稳定度分类法得出作业时间段大气处于中性层结状态;高斯模式模拟得出,有效的AgI浓度向上扩散范围高达3.0 km;作业点作业时段上空至3.2 km均处于上升气流区,计算出作业点发生器出口温度1.0℃。因冬季人工观测云底高度多为2.5~3.0 km,综合分析认为,该作业点的选址是合适的,此次作业条件较好,可以将催化剂输送到云中,起到催化作用。     

联合多点地质统计学与序贯高斯模拟的随机反演方法

岩相和储层物性参数是油藏表征的重要参数,地震反演是储层表征和油气藏勘探开发的重要手段.随机地震反演通常基于地质统计学理论,能够对不同类型的信息源进行综合,建立具有较高分辨率的储层模型,因而得到广泛关注.其中,概率扰动方法是一种高效的迭代随机反演策略,它能综合考虑多种约束信息,且只需要较少的迭代次数即可获得反演结果.在概率扰动的优化反演策略中,本文有效的联合多点地质统计学与序贯高斯模拟,并结合统计岩石物理理论实现随机反演.首先,通过多点地质统计学随机模拟,获得一系列等可能的岩相模型,扰动更新初始岩相模型后利用相控序贯高斯模拟建立多个储层物性参数模型;然后通过统计岩石物理理论,计算相应的弹性参数;最后,正演得到合成地震记录并与实际地震数据对比,通过概率扰动方法进行迭代,直到获得满足给定误差要求的反演结果.利用多点地质统计学,能够更好地表征储层空间特征.相控序贯高斯模拟的应用,能够有效反映不同岩相中储层物性参数的分布.提出的方法可在较少的迭代次数内同时获得具有较高分辨率的岩相和物性参数反演结果,模型测试和实际数据应用验证了方法的可行性和有效性.     

Crustal laminations in deep seismic profiles in France and neighbouring areas

Summary. Remarkable crustal features appear on the ECORS profiles carried out in northern France and the Bay of Biscay as well as on the SWAT profiles shot in the western Channel and the Celtic Sea. The most striking one is the occurrence of flat laminations in the lower crust. Dipping events and laminations are also present in the upper and lower crust, especially in the SWAT profiles. They can readily be related to tectonic events, Variscan in age, some of them identified in the field. The flat laminations in the lower crust are at first interpreted as resulting from delamination, shearing, magmatism and metamorphism at the crust-mantle transition during the Variscan orogeny. This interpretation raises some difficulty concerning the space and time correlation of the laminations with the Variscan orogeny. They seem to have been emplaced after the Permian-Triassic infilling of the Plymouth Bay basin and before the early Cretaceous opening of the Bay of Biscay. An early to middle Jurassic age is suggested, a period when large cratonic basins were formed without noticeable extension. Heat flow increase and magmatism are proposed as a second hypothesis for the formation of the lower crust laminations. Choosing between orogenic and non-orogenic causes of these laminations will require further deep seismic profiles together with good velocity determination.     

改进泊松算法的图像三维重建点云模型网格化

针对泊松表面重建算法在点云数据的网格化中仍不能有效满足"细节保持与噪声平滑"的平衡问题,该文提出了一种基于高斯滤波的改进泊松算法。通过将高斯滤波引入到点云数据等值面的向量场估计中,一方面实现了对点云拓扑结构的更准确估计以及对点云噪声的有效平滑;另一方面通过调节高斯滤波中的标准差参数,实现了对点云模型网格化的细节保持与噪声平滑的细微控制。以福州大学张孤梅雕像为实验对象,图像三维重建技术获得的点云数据作为数据源,利用改进的泊松算法进行点云网格化。结果表明,改进的泊松算法提高了网格模型的精确性与完整性,且在视觉上更好地逼近真实模型的细节,验证了改进算法的有效性。     

An adaptive unimodal subclass decomposition (AUSD) learning system for land use and land cover classification using high-resolution remote sensing

Land use and land cover classification is an important application of remote-sensing images. The performances of most classification models are largely limited by the incompleteness of the calibration set and the complexity of spectral features. It is difficult for models to realize continuous learning when the study area is transferred or enlarged. This paper proposed an adaptive unimodal subclass decomposition (AUSD) learning system, which comprises two-level iterative learning controls: The inner loop separates each class into several unimodal Gaussian subclasses; the outer loop utilizes transfer learning to extend the model to adapt to supplementary calibration set collected from enlarged study areas. The proposed model can be efficiently adjusted according to the variability of spectral signatures caused by the increasingly high-resolution imagery. The classification result can be obtained using the Gaussian mixture model by Bayesian decision theory. This AUSD learning system was validated using simulated data with the Gaussian distribution and multi-area SPOT-5 high-resolution images with 2.5-m resolution. The experimental results on numerical data demonstrated the ability of continuous learning. The proposed method achieved an overall accuracy of over 90% in all the experiments, validating the effectiveness as well as its superiority over several widely used classification methods.     

Additional Samples: Where They Should Be Located

Information for mine planning requires to be close spaced, if compared to the grid used for exploration and resource assessment. The additional samples collected during quasimining usually are located in the same pattern of the original diamond drillholes net but closer spaced. This procedure is not the best in mathematical sense for selecting a location. The impact of an additional information to reduce the uncertainty about the parameter been modeled is not the same everywhere within the deposit. Some locations are more sensitive in reducing the local and global uncertainty than others. This study introduces a methodology to select additional sample locations based on stochastic simulation. The procedure takes into account data variability and their spatial location. Multiple equally probable models representing a geological attribute are generated via geostatistical simulation. These models share basically the same histogram and the same variogram obtained from the original data set. At each block belonging to the model a value is obtained from the n simulations and their combination allows one to access local variability. Variability is measured using an uncertainty index proposed. This index was used to map zones of high variability. A value extracted from a given simulation is added to the original data set from a zone identified as erratic in the previous maps. The process of adding samples and simulation is repeated and the benefit of the additional sample is evaluated. The benefit in terms of uncertainty reduction is measure locally and globally. The procedure showed to be robust and theoretically sound, mapping zones where the additional information is most beneficial. A case study in a coal mine using coal seam thickness illustrates the method.