全极化探地雷达正演模拟

全极化探地雷达不但能获取当前探地雷达使用的共极化信息,而且能使用交叉极化信息,进而更好地分析目标属性.本文在时域有限差分法的基础上,构建了全极化探地雷达的正演模拟方法,通过水平正交双方向同时接收获取全极化信息.标准目标体金属板和角反射器的正演模拟与实验室物理模型测试一致的共极化和交叉极化响应信息,证实了该正演模拟方法的...     

基于改进声波方程和MCPML边界的频率域高精度正演模拟

数值频散和边界反射是频率域模拟时需要解决的两个重要问题.然而,受计算效率和分解阻抗矩阵时的内存占用量的制约,提高有限差分算子长度或增加有限差分网格数目均不是提高频率域模拟精度的最优解决方案.本文首先分析了数值频散产生的理论机制,在此基础上,推导了一种"波数补偿"的声波方程表达式来压制数值频散,并给出其物理意义,有效地改...     

A traveling epidemic model of space–time disease spread

This work presents a random field model of disease attribute (incidence, mortality etc.) that transfers the study of the attribute distribution from the original spatiotemporal domain onto a lower-dimensionality traveling domain that moves along the direction of disease velocity. The partial differential equations connecting the disease attribute covariances in the original and the traveling domain are derived with coefficients that are functions of the disease velocity. These equations offer epidemiologic insight concerning the strength of the space–time dependence between the disease attribute values in the two domains. The traveling disease model has certain theoretical and computational advantages in the study and prediction of space–time disease attribute distributions in conditions of uncertainty. Estimates of the disease attribute are derived in the traveling domain and then used to generate maps of space–time disease attribute distribution in the original domain. The theoretical model is illustrated and additional insight is gained by means of a numerical mortality simulation study, which shows that the proposed model is at least as accurate but computationally more efficient than mainstream mapping techniques of higher dimensionality. These findings concerning the very good predictability of the proposed model also strongly support its adequacy to represent the space–time mortality distribution.     

HYDRO_GEN: A spatially distributed random field generator for correlated properties

This paper describes a new method for generating spatially-correlated random fields. Such fields are often encountered in hydrology and hydrogeology and in the earth sciences. The method is based on two observations: (i) spatially distributed attributes usually display a stationary correlation structure, and (ii) the screening effect of measurements leads to the sufficiency of a small search neighborhood when it comes to projecting measurements and data in space. The algorithm which was developed based on these principles is called HYDRO_GEN, and its features and properties are discussed in depth. HYDRO_GEN is found to be accurate and extremely fast. It is also versatile: it can simulate fields of different nature, starting from weakly stationary fields with a prescribed covariance and ending with fractal fields. The simulated fields can display statistical isotropy or anisotropy.     

基于频率域峰值属性的河道砂体定量预测及应用(英文)

河道砂体是陆相含油气盆地最重要的储集类型之一,其边界识别和厚度定量预测是储层预测的热点难题。本文在总结现有方法技术的基础上,提出一种利用频率域峰值属性进行河道砂体边界识别和厚度定量预测的新方法。对典型河道薄砂体地震反射进行了正演模拟,构造了一种新的地震属性——峰值频率-振幅比,研究表明:峰值频率属性对地层厚度变化敏感,振幅属性对地层岩性变化敏感,两者比值突出河道砂体的边界,同时,借助峰值频率与薄层厚度间存在的定量关系进行薄砂体厚度计算。实际数据应用表明,地震峰值频率属性可以较好的刻画河道的平面展布特征;峰值频率-振幅比属性可以提高对河道砂体边界的识别能力;利用频率域地震属性进行砂体边界识别及厚度定量预测是可行的。     

基于地震属性约简的深度学习储层物性参数预测:以莺歌海盆地乐东区为例

储层物性参数作为描述储层特性、储层建模和流体模式的重要指标,其准确估算可以为储层预测提供有力参考依据,但传统储层物性参数反演方法无法兼顾反演精度及空间连续性。针对上述问题,本文引入地震属性作为深度学习算法输入,针对地震属性之间存在的信息冗余特征,利用随机森林-递归消除法对地震属性进行约简预处理,最终建立一种基于地震属性约简的储层物性参数预测方法。实际数据测试结果表明,地震属性约简的深度学习储层物性参数预测结果具有良好的精度及横向分辨率,证实本文方法的有效性。     

Response of a non-linear system with restoring forces governed by fractional derivatives—Time domain simulation and statistical linearization solution

In this paper, the random response of a non-linear system comprising frequency dependent restoring force terms is examined. These terms are accurately modeled in seismic isolation and in many other applications using fractional derivatives. In this context, an efficient numerical approach for determining the time domain response of the system to an arbitrary excitation is first proposed. This approach is based on the Grunwald–Letnikov representation of a fractional derivative and on the well-known Newmark numerical integration scheme for structural dynamic problems. Next, it is shown that for the case of a stochastic excitation, in addition to the time domain solutions, a frequency domain solution can be readily determined by the method of statistical linearization. The reliability of this solution is established in a Monte Carlo simulation context using the herein adopted time domain solution scheme. Furthermore, several related parameter studies are reported.     

Random partitioning and adaptive filters for multiple-point stochastic simulation

Multiple-point geostatistical simulation is used to simulate the spatial structures of geological phenomena. In contrast to conventional two-point variogram based geostatistical methods, the multiple-point approach is capable of simulating complex spatial patterns, shapes, and structures normally observed in geological media. A commonly used pattern based multiple-point geostatistical simulation algorithms is called FILTERSIM. In the conventional FILTERSIM algorithm, the patterns identified in training images are transformed into filter score space using fixed filters that are neither dependent on the training images nor on the characteristics of the patterns extracted from them. In this paper, we introduce two new methods, one for geostatistical simulation and another for conditioning the results. At first, new filters are designed using principal component analysis in such a way to include most structural information specific to the governing training images resulting in the selection of closer patterns in the filter score space. We then propose to combine adaptive filters with an overlap strategy along a raster path and an efficient conditioning method to develop an algorithm for reservoir simulation with high accuracy and continuity. We also combine image quilting with this algorithm to improve connectivity a lot. The proposed method, which we call random partitioning with adaptive filters simulation method, can be used both for continuous and discrete variables. The results of the proposed method show a significant improvement in recovering the expected shapes and structural continuity in the final simulated realizations as compared to those of conventional FILTERSIM algorithm and the algorithm is more than ten times faster than FILTERSIM because of using raster path and using small overlap specially when we use image quilting.     

计算层状介质中电磁场的层矩阵法

现有人工源频率域电磁法的研究大多仅针对某种具体的方法,而较少将问题综合起来分析.本文综合多种方法的共同点提出了层矩阵法,它采取了源置于层间的模型进行公式的推导,理论上可以计算任意层状介质中任意位置的任意场源在空间中任意位置产生的场强,可适用于多种电磁法的正演模拟计算.层矩阵法的核心是对空间域的变量x, y, z中的x和y变量进行傅氏变换后转换到波数域k_x和k_y中,在波数域利用边界条件,用层矩阵建立起各层的关系后计算得到各层的波数域电磁场值,然后经过二维反傅氏变换最终得到空间域中任意位置的场值.因为文中定义的层矩阵是建立层关系的关键,所以称此方法为层矩阵法.本文以水平电偶源为例独立推导了层状介质中人工源频率域电磁场解的理论公式.为了验证方法的正确性,文中建立了多种模型,利用自行编排的程序将层矩阵法与现有文献的各种解析公式的解进行了对比,结果表明本文提出的层矩阵法是灵活的、可靠的.     

金属矿山地地区地震勘探随机噪声的波动方程模拟

消减随机噪声是目前陆地地震勘探数据处理的关键问题之一,分析随机噪声的产生机制及特征是对其进行有效压制的先决条件.本文针对中国南方山地金属矿区的勘探环境,根据随机噪声中包含的自然噪声和人文噪声的发声机理分别确定其噪声源函数,以波动方程作为噪声传播模型对山地地区随机噪声进行建模,将随机噪声作为一个综合波场,并且与实际噪声记录进行比较.随机噪声记录作为时空域的二维随机过程,分别对模拟噪声和实际噪声记录的时间域波形(振动图)特征包括频谱、功率谱密度,相空间轨迹图,统计量特征(能量分布,累积分布,均值,方差,峰度,偏度),和空间域波形(波剖面)特征包括波数谱和统计量特征进行比较,对比结果显示在时空域模拟噪声和实际噪声都有基本相同的性质,证明了本文对随机噪声模拟方法的可行性,为进一步研究随机噪声时空域传播特性以及噪声消除奠定理论基础.     

Modelling of magnetic data for scaling geology

Interpretation of magnetic data can be carried out either in the space or frequency domain. The interpretation in the frequency domain is computationally convenient because convolution becomes multiplication. The frequency domain approach assumes that the magnetic sources distribution has a random and uncorrelated distribution. This approach is modified to include random and fractal distribution of sources on the basis of borehole data. The physical properties of the rocks exhibit scaling behaviour which can be defined as P(k) = Ak^?β, where P(k) is the power spectrum as a function of wave number (k), and A and β are the constant and scaling exponent, respectively. A white noise distribution corresponds to β = 0. The high resolution methods of power spectral estimation e.g. maximum entropy method and multi‐taper method produce smooth spectra. Therefore, estimation of scaling exponents is more reliable. The values of β are found to be related to the lithology and heterogeneities in the crust. The modelling of magnetic data for scaling distribution of sources leads to an improved method of interpreting the magnetic data known as the scaling spectral method. The method has found applicability in estimating the basement depth, Curie depth and filtering of magnetic data.     

Plurigaussian modeling of geological domains based on the truncation of non-stationary Gaussian random fields

The plurigaussian model is used in mining engineering, oil reservoir characterization, hydrology and environmental sciences to simulate the layout of geological domains in the subsurface, while reproducing their spatial continuity and dependence relationships. However, this model is well-established only in the stationary case, when the spatial distribution of the domains is homogeneous in space, and suffers from theoretical and practical impediments in the non-stationary case. To overcome these limitations, this paper proposes extending the model to the truncation of intrinsic random fields of order k with Gaussian generalized increments, which allows reproducing spatial trends in the distribution of the geological domains. Methodological tools and algorithms are presented to infer the model parameters and to construct realizations of the geological domains conditioned to existing data. The proposal is illustrated with the simulation of rock type domains in an ore deposit in order to demonstrate its applicability. Despite the limited number of conditioning data, the results show a remarkable agreement between the simulated domains and the lithological model interpreted by geologists, while the conventional stationary plurigaussian model turns out to be unsuccessful.     

深海热液硫化物矿体3D瞬变电磁正演

深海热液硫化物矿体瞬变电磁的正演是考虑深海环境的全空间条件下三维体的涡流电磁响应.采用全空间矢量有限元法模拟计算深海热液硫化物矿的三维瞬变电磁响应,对硫化物矿体采用矩形单元模型剖分,应用Galerkin法推导有限元方程,先计算频率域响应,再通过Fourier反变换将其转换至时间域,得出深海热液硫化物矿矿体的瞬变电磁响应.并用双半空间模型的解析解检验了全空间矢量有限元法模拟计算算法和程序的正确性,最后按照等比例缩小电磁物理实验原则,比对数值计算和物理实验结果论证了全空间3D模型数值的正确性.结果表明:对于海水、矿体以及围岩复杂电磁边界,应用全空间矢量有限元法模拟计算深海热液硫化物矿瞬变电磁响应异常与物理模拟结果一致,而且计算方法简单精确,异常幅值明显,边界清晰.     

Multiscale flow and transport model in three-dimensional fractal porous media

This paper proposes a multiscale flow and transport model which can be used in three-dimensional fractal random fields. The fractal random field effectively describes a field with a high degree of variability to satisfy the one-point statistics of Levy-stable distribution and the two-point statistics of fractional Levy motion (fLm). To overcome the difficulty of using infinite variance of Levy-stable distribution and to provide the physical meaning of a finite domain in real space, truncated power variograms are utilized for the fLm fields. The fLm model is general in the sense that both stationary and commonly used fractional Brownian motion (fBm) models are its special cases. When the upper cutoff of the truncated power variogram is close to the lower cutoff, the stationary model is well approximated. The commonly used fBm model is recovered when the Levy index of fLm is 2. Flow and solute transport were analyzed using the first-order perturbation method. Mean velocity, velocity covariance, and effective hydraulic conductivity in a three-dimensional fractal random field were derived. Analytical results for particle displacement covariance and macrodispersion coefficients are also presented. The results show that the plume in an fLm field moves slower at early time and has more significant long-tailing behavior at late time than in fBm or stationary exponential fields. The proposed fractal transport model has broader applications than those of stationary and fBm models. Flow and solute transport can be simulated for various scenarios by adjusting the Levy index and cutoffs of fLm to yield more accurate modeling results.     

Geostatistical simulation of random fields with bivariate isofactorial distributions by adding mosaic models

This work deals with the geostatistical simulation of a family of stationary random field models with bivariate isofactorial distributions. Such models are defined as the sum of independent random fields with mosaic-type bivariate distributions and infinitely divisible univariate distributions. For practical applications, dead leaf tessellations are used since they provide a wide range of models and allow conditioning the realizations to a set of data via an iterative procedure (simulated annealing). The model parameters can be determined by comparing the data variogram and madogram, and enable to control the spatial connectivity of the extreme values in the realizations. An illustration to a forest dataset is presented, for which a negative binomial model is used to characterize the distribution of coniferous trees over a wooded area.     

Corrective pattern-matching simulation with controlled local-mean histogram

This paper presents a new stochastic simulation method that improves on our unilateral patchwork simulation method (Faucher et al., Stoch Environ Res Risk Assess, 27:253–273, 2012) by eliminating anisotropy biases. As in our unilateral method, images are built by assembling patterns together while controlling the local-mean histogram. The patterns, which are square image-pieces, are picked in a reference image. The reference image is used as a data bank holding the statistical informations about the random field to simulate. In contrast with the unilateral method, the path followed by our new simulation is random and guided by local errors. The new method, called corrective pattern-matching simulation, proceeds iteratively by making local corrections to the simulated image. For several types of images, it is shown that our simulations respect conditioning data and reproduce faithfully the reference image visual appearance. It is shown that the control of the local-mean histogram allows to control one-point statistics and multi-point statistics.     

快速精确的二维频率空间域弹性波数值模拟

二维频率空间域的数值模拟方法具有以下的优势:多炮模拟时,计算成本比时间域方法低;无累计误差;在地震反演中处理多震源模拟时,只需要有限的几个频率就可以得到好的反演结果.差分离散化形成的稀疏系数矩阵,需要求解一个巨大规模的线性方程组,最大瓶颈是需要海量的计算机内存,导致计算量庞大.本文在前人研究的基础上,采用嵌套剖分网格排序法,极大限度减少对计算机内存的需求,从而减少了计算量.针对弹性波数值模拟的特征,提出二维频率空间域弹性波多炮模拟的快速计算流程.数值模拟试验证明使用嵌套剖分排序法的弹性波多炮数值模拟比压缩存储法具有节省存储量、计算效率高等优势,为后续的二维频率空间域弹性波全波形反演奠定了很好的基础.     

台站地震资料的时频域自适应极化分析和滤波

提出一种自适应协方差的时频域极化滤波方法。该方法在广义S变换时频方法的基础上,构造时频域自适应协方差矩阵,通过特征分析计算时频域瞬时极化参数,设计极化滤波器,实现多分量地震极化分析和滤波。其优势在于协方差矩阵的分析时窗的长度由多分量地震数据的瞬时频率确定,可以自适应于有效信号的周期,在每个时频点计算极化参数不需要进行插值处理;结合时间频率信息,解决在时间域或频率域波形或频率重叠的信号具有明显的直观性。模型数据及实际三分量台站地震数据处理结果表明,该极化滤波方法在台站地震资料分析和处理方面具有很好的直观性和较高的分辨率。     

A six-step practical approach to semivariogram modeling

Geostatistical prediction and simulation are being increasingly used in the earth sciences and engineering to address the imperfect knowledge of attributes that fluctuate over large areas or volumes—pollutant concentration, electromagnetic fields, porosity, thickness of a geological formation. Central to the application of such techniques is the need to know the spatial continuity, knowledge that is commonly condensed in the form of covariance or semivariogram models. Their preparation is subdivided here into the following steps: (1) Data editing, (2) Exploratory data analysis, (3) Semivariogram estimation, (4) Directional investigation, (5) Simple modeling, (6) Nested modeling. I illustrate these stages practically with a real data set from a geophysical survey from Elk County, Kansas, USA. The applicability of the approach is not limited by the physical nature of the attribute of interest.     

Detecting and quantifying sources of non-stationarity via experimental semivariogram modeling

Conventional geostatistics often relies on the assumption of second order stationarity of the random function (RF). Generally, local means and local variances of the random variables (RVs) are assumed to be constant throughout the domain. Large scale differences in the local means and local variances of the RVs are referred to as trends. Two problems of building geostatistical models in presence of mean trends are: (1) inflation of the conditional variances and (2) the spatial continuity is exaggerated. Variance trends on the other hand cause conditional variances to be over-estimated in certain regions of the domain and under-estimated in other areas. In both cases the uncertainty characterized by the geostatistical model is improperly assessed. This paper proposes a new approach to identify the presence and contribution of mean and variance trends in the domain via calculation of the experimental semivariogram. The traditional experimental semivariogram expression is decomposed into three components: (1) the mean trend, (2) the variance trend and (3) the stationary component. Under stationary conditions, both the mean and the variance trend components should be close to zero. This proposed approach is intended to be used in the early stages of data analysis when domains are being defined or to verify the impact of detrending techniques in the conditioning dataset for validating domains. This approach determines the source of a trend, thereby facilitating the choice of a suitable detrending method for effective resource modeling.