基于改进的接收点插值算法的频率域海洋可控源电磁法2.5维正演

在海洋可控源电磁法勘探中,接收站常置于海底.在进行海洋电磁场模拟时,由于海水和海底介质存在显著电性差异,这给海底接收点处场值的求取带来困难.本文提出一种新的接收点插值算法,该算法考虑到海底电场法向分量不连续性问题,用法向电流分量进行插值以准确求取海底任意接收点处电磁场值.本文利用交错网格有限差分法实现了二维介质中频率域海洋可控源法（CSEM）正演.对构造走向做傅里叶变换,将三维电磁模拟问题转换为波数域2.5维问题,即三维场源激励下针对二维地电模型的电磁模拟问题.使用交错网格有限差分法,基于一次场/二次场分离方法导出波数域二次电场离散形式,并进一步求得波数域电磁场.采用本文提出的改进的插值算法可求得海底任意接收点处波数域电磁场,采用傅里叶逆变换对波数域电磁场进行积分可得到接收点处空间域电磁场.模型算例表明,与常规的线性插值和严格插值算法相比,本文提出的改进的插值算法具有更高的精度.

     

一种边缘保持的地震数据插值方法

在地震数据处理中,地震数据插值方法常常用来解决地震数据空间采样率低和不规则的问题.本文提出了一种基于边缘保持滤波器的地震数据插值方法.在该方法中,对于一个1D信号,逐点滑动一个处理窗口,将信号分成多个信号片段.对于某一个待恢复的缺失采样点,存在多个包含(或邻近)该采样点的信号片段可以用来估计它.采用多项式来拟合这些信号片段,并选择拟合误差最小的信号片段估计此缺失采样点,达到边缘保持的目的.对于2D地震信号,先沿不同方向扫描抽取1D信号,然后采用上述1D边缘保持插值算法分别进行处理,得到沿不同方向的插值结果.对于任一待插值采样点,选取对应拟合误差最小的方向的插值结果作为最后输出的2D数据的插值结果.理论模型和实际资料的处理结果表明,所提方法具有保边缘、抗假频及能够进行不规则数据重建等特点,既能有效的实现不规则地震数据的重建,又能很好的保持原有数据的边缘特征.     

基于CUDA技术的矿产储量计算

插值计算是矿产储量计算中的重要环节,但由于计算量大,经常需要在插值密度和计算时间之间进行权衡。本项研究通过最新的CUDA技术,将插值运算转换到显卡上进行并行化计算,极大地提高了计算速度。以紫金山铜矿数据为研究对象,进行了方法技术的实验,与基于CPU的计算相比,基于GPU下CUDA的计算速度提高了67倍。     

基于偏微分方程的定向插值在偏移成像中的应用

对于射线类偏移成像来说,求解射线追踪系统中所涉及的属性值不在网格节点上的插值计算问题是一个非常重要的环节,它影响到求解走时、路径和振幅信息的计算效率和精度,进而影响到整个偏移成像的质量和效率.本研究根据速度模型的空间梯度特点,考虑被插值点处速度的梯度在横向和纵向的分布特征,构建基于速度梯度空间变化的偏微分方程算法,将近几年发展起来的基于偏微分方程的定向插值算法引入到射线类偏移成像当中,实现射线追踪当中涉及的属性值不在网格节点上的插值计算.由于偏微分方程法本身固有的特性(局部特征不变性、解的唯一性和线性叠加性),因此,该算法可以实现不破坏原始速度模型空间梯度结构的非网格节点属性的插值计算.通过在常用的速度模型上的插值计算对比、不同速度模型上射线路径对比分析以及复杂介质模型上最后的偏移成像结果分析可以得出,应用基于速度梯度构建的偏微分方程插值算法在进行插值计算的过程当中可以实现不破坏原始速度模型空间速度梯度结构的属性计算,同时应用该算法可以最终提高射线类偏移成像的质量.

     

基于频率-结构双重加权阈值的地震数据插值

地震数据的插值是地震数据处理的关键环节,插值效果的优劣关系到后续反演、去噪、反褶积、偏移等工作的进行.基于稀疏反演的常规频率-波数（FK）域插值方法往往使用广义阈值,而由于缺失地震数据仅沿波数方向呈稀疏态,在沿频率方向呈类子波频谱形态分布的非稀疏态,直接应用基于Lp范数的广义阈值会难以补全缺失数据的高低频信息,不利于后续依赖低频信息的反演及依赖高频的高分辨率处理工作的开展;基于该问题,本文设计沿频率方向类子波频谱形态变化的频率加权阈值,同时考虑完整地震数据在波数域的聚集分布,引入沿波数方向的结构加权阈值,提出基于频率-结构的双重加权阈值,在补全缺失地震道的同时,保证其高低频信息的有效恢复.模型和实际数据表明,相比于广义阈值,基于频率-结构的双重加权阈值可以减少插值误差,最大限度保证缺失地震道位置插值结果高低频信息的完整性.

     

http://www.sciencedirect.com/science/article/pii/S1674987111001411

正Three-dimensional geological modeling(3DGM) assists geologists to quantitatively study in three-dimensional(3D) space structures that define temporal and spatial relationships between geological objects.The 3D property model can also be used to infer or deduce causes of geological objects.3DGM technology provides technical support for extraction of diverse geoscience information,3D modeling,and quantitative calculation of mineral resources.Based on metallogenic concepts and an ore deposit model, 3DGM technology is applied to analyze geological characteristics of the Tongshan Cu deposit in order to define a metallogenic model and develop a virtual borehole technology;a BP neural network and a 3D interpolation technique were combined to integrate multiple geoscience information in a 3D environment. The results indicate:(1) on basis of the concept of magmatic-hydrothermal Cu polymetallic mineralization and a porphyry Cu deposit model,a spatial relational database of multiple geoscience information for mineralization in the study area(geology,geophysics,geochemistry,borehole,and cross-section data) was established,and 3D metallogenic geological objects including mineralization stratum,granodiorite, alteration rock,and magnetic anomaly were constructed;(2) on basis of the 3D ore deposit model,23,800 effective surveys from 94 boreholes and 21 sections were applied to establish 3D orebody models with a kriging interpolation method;(3) combined 23,800 surveys involving 21 sections,using VC++ and OpenGL platform,virtual borehole and virtual section with BP network,and an improved inverse distance interpolation(IDW) method were used to predict and delineate mineralization potential targets (Cu-grade of cell not less than 0.1%);(4) comparison of 3D ore bodies,metallogenic geological objects of mineralization,and potential targets of mineralization models in the study area,delineated the 3D spatial and temporal relationship and causal processes among the ore bodies,alteration rock,metallogenic stratum,intrusive rock,and the Tongshan Fault.This study provides important technical support and a scientific basis for assessment of the Tongshan Cu deposit and surrounding exploration and mineral resources.     

用于强震记录仿真地动位移的高精度累积数值积分方法研究

针对传统梯形积分方法的低精度缺陷,提出了一套高精度累积数值积分方法.首先对被积数据进行分段三次Hermite插值,之后采用积分区间四等分的Newton-Cotes积分公式进行积分.误差分析表明,本方法精度远高于梯形积分方法精度.在对构建信号进行方法验证的前提下,采用2013年4月20日雅安芦山地震和2008年5月12日汶川地震的真实强震动加速度记录对本方法进行测试,测试结果表明,本方法适用于将强震动加速度记录积分为位移记录.     

An evaluation of void‐filling interpolation methods for SRTM data

The Digital Elevation Model that has been derived from the February 2000 Shuttle Radar Topography Mission (SRTM) has been one of the most important publicly available new spatial data sets in recent years. However, the ‘finished’ grade version of the data (also referred to as Version 2) still contains data voids (some 836,000 km²)—and other anomalies—that prevent immediate use in many applications. These voids can be filled using a range of interpolation algorithms in conjunction with other sources of elevation data, but there is little guidance on the most appropriate void‐filling method. This paper describes: (i) a method to fill voids using a variety of interpolators, (ii) a method to determine the most appropriate void‐filling algorithms using a classification of the voids based on their size and a typology of their surrounding terrain; and (iii) the classification of the most appropriate algorithm for each of the 3,339,913 voids in the SRTM data. Based on a sample of 1304 artificial but realistic voids across six terrain types and eight void size classes, we found that the choice of void‐filling algorithm is dependent on both the size and terrain type of the void. Contrary to some previous findings, the best methods can be generalised as: kriging or inverse distance weighting interpolation for small and medium size voids in relatively flat low‐lying areas; spline interpolation for small and medium‐sized voids in high‐altitude and dissected terrain; triangular irregular network or inverse distance weighting interpolation for large voids in very flat areas, and an advanced spline method (ANUDEM) for large voids in other terrains.     

Assessing housing growth when census boundaries change

The US Census provides the primary source of spatially explicit social data, but changing block boundaries complicate analyses of housing growth over time. We compared procedures for reconciling housing density data between 1990 and 2000 census block boundaries in order to assess the sensitivity of analytical methods to estimates of housing growth in Oregon. Estimates of housing growth varied substantially and were sensitive to the method of interpolation. With no processing and areal‐weighted interpolation, more than 35% of the landscape changed; 75–80% of this change was due to decline in housing density. This decline was implausible, however, because housing structures generally persist over time. Based on aggregated boundaries, 11% of the landscape changed, but only 4% experienced a decline in housing density. Nevertheless, the housing density change map was almost twice as coarse spatially as the 2000 housing density data. We also applied a dasymetric approach to redistribute 1990 housing data into 2000 census boundaries under the assumption that the distribution of housing in 2000 reflected the same distribution as in 1990. The dasymetric approach resulted in conservative change estimates at a fine resolution. All methods involved some type of trade‐off (e.g. analytical difficulty, data resolution, magnitude or bias in direction of change). However, our dasymetric procedure is a novel approach for assessing housing growth over changing census boundaries that may be particularly useful because it accounts for the uniquely persistent nature of housing over time.     

Comparative analysis of different techniques for spatial interpolation of rainfall data to create a serially complete monthly time series of precipitation for Sicily,Italy

The availability of good and reliable rainfall data is fundamental for most hydrological analyses and for the design and management of water resources systems. However, in practice, precipitation records often suffer from missing data values mainly due to malfunctioning of raingauge for specific time periods. This is an important issue in practical hydrology because it affects the continuity of rainfall data and ultimately influences the results of hydrologic studies which use rainfall as input. Many methods to estimate missing rainfall data have been proposed in literature and, among these, most are based on spatial interpolation algorithms.