自适应滤波器

自适应滤波器是一个空间域的数字滤波器。它对不应作滤波处理的点不作滤波,使滤波过程对区域成分的畸变降到最小。它采用一元三点内插法作插值,使滤波公司简单,计算速度快而又能保证精度。判别局部成分的标志及滤波计算都只用局部成分前二个点及后三个点,因而边缘损失小。     

Sage自适应滤波在航空重力数据处理的应用

航空重力测量数据存在大量的干扰噪声,卡尔曼滤波是消除干扰、获得高精度重力异常的一种滤波方法。针对标准卡尔曼滤波精度依赖于先验量测噪声统计信息的问题,以Sage-Husa自适应卡尔曼滤波算法为基础,结合固定区间平滑,设计了量测噪声自适应的卡尔曼平滑滤波器,利用卡尔曼滤波及自适应卡尔曼平滑滤波对模型数据进行了滤波试验。试验结果说明,固定区间平滑的应用可以消除因滤波器未收敛造成的滤波误差,当量测噪声信息不明时,量测噪声自适应卡尔曼滤波器能够获得准确的滤波结果,其滤波精度高于标准卡尔曼滤波器。     

自适应加权改进窗口中值滤波

针对传统的多级二维中值滤波窗口函数及窗口大小对地震数据噪声处理存在影响,提出了一种自适应加权改进窗口多级二维中值滤波器。对传统的多级二维中值滤波窗口函数进行改进,使其具有保护线性和细节特征。在改进窗口函数的基础上,提出了自适应加权函数,加权函数的自适应性对噪声衰减和有效信号的保真奠定了基础,自适应加权改进窗口中值滤波器去除噪声明显。通过理论模型和实际数据处理的对比,表明本方法去除噪声和保护有效信号能力优于传统的二维多级中值滤波器。     

复杂地震波场的自适应流预测插值方法

地震数据本质上是非平稳的,如何解决复杂非平稳地震波场的数据缺失问题是地震勘探数据处理的重要环节之一。预测滤波器在地震数据处理和分析中具有重要的作用,该技术可以有效地解决地震数据缺失问题,但传统的平稳预测滤波方法无法很好地适应地震数据的非平稳特征;因此,开发高效的复杂地震波场自适应预测插值方法具有重要的工业价值。本文将预测滤波器加入"流处理"的概念,滤波器系数随着地震数据的变化同时更新,此计算过程仅需矢量点积运算,能够提高计算效率并降低内存空间;并以此为基础开发基于流预测滤波的地震数据插值方法。利用多次波的动力学信息,通过互相关技术构建虚拟一次波,有效地解决了缺失数据位置滤波系数估计不准的问题,为插值过程提供了更为合理的滤波器估计,更好地解决了非平稳地震数据的重建问题。对Sigsbee 2B模型和实际数据的测试结果表明,该方法可以合理地针对复杂地震信息完成缺失数据的重建。     

基于 ＣＥＥＭＤ和自适应中值滤波的大地电磁数据去噪研究

为提高大地电磁数据的信噪比,笔者提出基于互补总体经验模式分解 （ＣＥＥＭＤ） 和自适应中值滤波的去噪方法,利用 ＣＥＥＭＤ将大地电磁时间序列数据分解成多个固有模态函数 （ＩＭＦ）及趋势项,依据噪声的高低频特征有选择地利用自适应中值滤波对固有模态函数 （ＩＭＦ）进行去噪,再进行数据重构。对实测数据进行处理,该方法能较好地抑制大地电磁数据中、低频部分的噪声干扰,抑制突变点,提高数据的信噪比。     

一种快速有效的地震道空间内插方法

地震道空间内插所面临的主要问题是空间假频。为此,Ｓｐｉｔｚ（１９９１年）提出了一种ｔ－ｘ域道内插方法可以很有效地克服空间假频,其数学基础是单位步长预测滤波技术。最近,在Ｓｐｉｔｚ工作的基础上,Ｐｏｒｓａｎｉ（１９９９年）提出了一种半步长预测滤波技术,它可以将原来用于求解预测滤波器系数的两组复杂的复线性系统方程简化为一组更为简单的复线性系统方法,从而大大降低了运算工作量。合成数据及实际地震记录的试处     

青海油砂山油田第68层分流河道砂体解剖学

青海油砂山剖面第６８层三角洲分流河道砂体内部可识别出来Ｇｐｒ、Ｇｌｔ、Ｇｅ、Ｓｌｔ、Ｓｍｔ、Ｓｐｒ、Ｓｌａ、Ｓｂｍ、ＳＩｃｒ、ＳＩｈ和Ｍｒｉ等１２种岩石相，它们构成了６种岩石相组合，即:Ｇｅ－Ｇｐｒ－Ｇｌｔ组合，Ｇｌｔ－Ｓｌｔ组合，Ｓｌｔ－Ｓｍｔ组合，Ｇｌｔ－Ｓｂｍ组合，Ｓｓｔ－Ｍｒｌ组合，Ｇｐｒ（Ｓｐｒ）－Ｍｒｌ－Ｓｓｔ－Ｍｒｌ－ＳＩｃｒ－Ｍｒｌ组合。按照沉积界面之间的切割关系，建立一个包括７级界面的界面层次，第一级为砂体的上下边界，第七级为纹层边界，沉积界面将砂体分隔为三个沉积幕，它们由六个沉积亚幕组成。砂体建筑结构要素包括侧积体（ＬＡ），纵向砂坝（ＬＢ），横向砂坝（ＴＢ），简单砾质充填（ＧＦ），简单砂质充填（ＳＦ）和堤岸砂坪（ＬＦ）等六种类型，它们具有不同的宽度和厚度比。通过露头密网格采样和沉积学分析建立了砂体渗透率原型模型，均质模型，幕式模型以及建筑结构要素模型，其中建筑结构模型与原型模型相似性最好，证明了利用建筑结构分析可以建立符合砂体客观实际的储层地质模型。     

区调管理信息系统简介

区调管理信息系统是以中国地质大学华地图形有限公司研制的ＭＡＰＧＩＳ为原型,利用Ｍｉｃｒｏｓｏｆｔ公司面向对象的程序设计语言－ＶｉｓｕａｌＣ＋＋５．０开发工具,运用先进的数据访问对象,（ＤＡＯ）技术开发而成,同时采用ＭｉｃｒｏｓｏｆｔＪｅｔ数据库来实现对区调基础数据资料的组织,其界面友好,操作方便,功能强大,不仅能有效地管理区调数据,还能实现图形数据与属性数据之间的双向查询,ＳＯＬ查询等功能,适合于     

MT二维正演的混合剖分算法及其在线源CSAMT正演计算中的应用

在矩形有限元和三角形有限元方法大地电磁测深（ＭＴ）二维正演计算的基础上，设计了矩形单元粗剖分、程序自动进行三角形单元细剖分的混合剖分算法程序，使得ＭＴ二维模型正演的计算速度大为提高。该方法同时被应用于线电流源变频电磁测深（ＣＳＡＭＴ）ＴＥ极化方式的二维正演计算。文章给出了在不同模型上计算的ＭＴ和线源ＣＳＡＭＴ的响应，分析了计算ＣＳＡＭＴ响应时，计算点离源的距离对视电阻率和相位值计算的影响，比较了ＭＴ和ＣＳＡＭＴ网格剖分的特点，提出了计算ＣＳＡＭＴ响应的改进的边界条件设计     

自相关滤波法提取重磁场中弱异常

在每条测线内自动寻找剩余局部异常最大点处的观测值, 将其作为参考模型, 并沿整条测线进行滑动自相关处理, 对重磁异常处理中的自相关滤波因子进行了改造。理论模型研究表明, 改造后的滤波结果中零等值线能较好的划分异常边界, 对横向叠加异常的分辨能力很强, 能够提取常规方法很难识别的弱异常。对滤波窗口的研究表明, 自相关半径选择3～6个网格节点距为佳。利用改造后的自相关滤波因子进行实际资料处理, 发现了新的找矿远景区。     

Usefulness of adaptive filtering for improved Digital Elevation Model generation

The Digital Elevation Models (DEMs), which represent the variation of elevation in a terrain at spatial level, are an important source of input to a variety of applications for deriving a number of terrain parameters such as relative relief, slope, aspect direction etc. In recent years, Synthetic Aperture Radar Interferometry has been viewed as a powerful approach to derive quality DEMs from a pair of SAR images. Despite the interferometric technique is often limited by several de-correlations several researchers demonstrate its effectiveness in topographic mapping. The DEM accuracy is strongly influenced by the effectiveness of the phase unwrapping technique. In this study an effective adaptive filtering approach has been used to reduce the phase noise due to de-correlation and in improving the accuracy of phase unwrapping. Two well known phase unwrapping approaches such as branch cut and minimum cost flow network have been used. Interferometric data from ASAR sensor onboard ENVISAT satellite have been used. A highly undulated terrain condition near Dehradun city situated in Uttarakhand state of India was selected to investigate the performance of this adaptive filtering approach. The RMS error between the InSAR derived elevations and the map derived elevations was obtained as 7.2 m using adaptive filter. However, elevation map of the study area could not be generated due to high de-correlation effect without the use of adaptive filter. This result clearly demonstrates the effectiveness of adaptive filtering approach for generation of DEM at meter level accuracy, which is sufficient for many engineering applications.     

基于多结构元素形态滤波的大地电磁去噪

数学形态滤波是根据形态学原理创建的一种新型滤波方法,目前在信号处理的诸多领域得到成功运用。本文从形态滤波的基本原理出发,引入了一种多结构元素组成的滤波器用于大地电磁噪声消除。通过数值模拟展示了多结构元素滤波器的滤波效果,表明多结构元素滤波器在小尺度的范围内也有较好的滤波性能。同时,实测大地电磁信号的重构曲线和其视电阻率曲线显示多结构元素形态滤波对大地电磁噪声中的大尺度干扰噪声,如方波噪声和三角波噪声等,有较好的抑制作用,说明多结构元素形态滤波在大地电磁去噪中有较好的应用价值。     

一种基于AR 模型的预测滤波压制随机噪声方法

在地震勘探中,随机噪声是一类不可避免的噪声,它的存在极大地降低了地震资料的信噪比,导致偏移成像效果差甚至不能成像。自适应线性预测滤波方法是在时间--空间域自回归( AR) 模型系数变化的假定下,把自回归( AR) 模型数学表达式进行变换,引入代价函数以提高解的稳定性、唯一性,推导得到压制一维和二维随机噪声的递归算法。通过模拟和实际地震资料验证表明,该方法能较好地压制低信噪比资料中的随机噪声干扰,同时能较好地保护有效地震信号。     

基于时频域极化滤波的勒夫型槽波提取

矿井槽波地震勘探数据中,含有多种类型地震波,包括线性极化的纵波、横波、勒夫型槽波和椭圆极化的瑞利型槽波。由于槽波频散现象严重,不同类型槽波互相重叠,在地震记录上难以区分,合理地进行波场分离是槽波数据处理的重要环节。根据不同类型槽波振动极化特征,提出基于S变换的时频域自适应协方差矩阵极化滤波方法;在时频域中,针对槽波水平双分量信号建立自适应协方差矩阵;利用矩阵对应特征值和特征向量,计算椭圆率和方位角参数来描述槽波极化振动特征;依据极化参数建立极化滤波函数,对槽波地震信号进行波场分离。经过理论合成信号和实际数据测试表明,该方法可以有效地从槽波地震记录中提取出勒夫型槽波,避免其它类型地震波在槽波数据处理过程中产生的干扰,为槽波地震勘探数据处理提供新的技术手段。      

Image Filtering by Factorial Kriging—Sensitivity analysis and application to Gloria side-scan sonar images

Factorial Kriging (FK) is a data- dependent spatial filtering method that can be used to remove both independent and correlated noise on geological images as well as to enhance lineaments for subsequent geological interpretation. The spatial variability of signal, noise, and lineaments, characterized by a variogram model, have been used explicitly in calculating FK filter coefficients that are equivalent to the kriging weighting coefficients. This is in contrast to the conventional spatial filtering method by predefined, data-independent filters, such as Gaussian and Sobel filters. The geostatistically optimal FK filter coefficients, however, do not guarantee an optimal filtering effect, if filter geometry (size and shape) are not properly selected. The selection of filter geometry has been investigated by examining the sensitivity of the FK filter coefficients to changes in filter size as well as variogram characteristics, such as nugget effect, type, range of influence, and anisotropy. The efficiency of data-dependent FK filtering relative to data-independent spatial filters has been evaluated through simulated stochastic images by two examples. In the first example, both FK and data-independent filters are used to remove white noise in simulated images. FK filtering results in a less blurring effect than the data-independent fillers, even for a filter size as large as 9 × 9. In the second example, FK and data-independent filters are compared relative to the extraction of lineaments and components showing anisotropic variability. It was determined that square windows of the filter mask are effective only for removing Isotropie components or white noise. A nonsquare windows must be used if anisotropic components are to be filtered out. FK filtering for lineament enhancement is shown to be resistant to image noise, whereas data-independent filters are sensitive to the presence of noise. We also have applied the FK filtering to the GLORIA side-scan sonar image from the Gulf of Mexico, illustrating that FK is superior to the data-independent filters in removing noise and enhancing lineaments. The case study also demonstrate that variogram analysis and FK filtering can be used for large images if a spectral analysis and optimal filter design in the frequency domain is prohibitive because of a large memory requirement.     

基于自然伽马测井信号的维纳滤波法求取泥质含量

泥质含量是定性、定量评价储层属性的一个重要参数.研究经济、适用、高精度的储层泥质含量求取方法, 对储层的评价、预测含油气远景和计算储层油气储量意义明确.提出了测井自然伽马求取泥质含量的新原理, 认为测井自然伽马信号是地层自然伽马真值通过一个系统的卷积滤波输出.利用测井自然伽马信号和提取的自然伽马真值子波, 采用维纳滤波法求取测井系统逆因子函数, 根据逆因子函数, 用自然伽马测井信号做卷积直接计算泥质含量.本研究在中国西北某油气勘探区有岩心分析资料的K13井进行了试验, 求取的泥质含量精度比测井常规解释方法大幅提高, 在同一勘探区K11、S44、S4等井试验性应用, 效果良好.      

Spatial filtering of exploration geochemical data using EDA and robust statistics

The spatial filtering techniques that are used for the analysis and interpretation of exploration geochemical data to define regional distribution patterns or to outline anomalous areas are, in most cases, based on non-robust statistical methods. The performance of these techniques is heavily influenced by the presence of outliers that commonly exist in the data. This study describes a number of filtering techniques motivated by the development of exploratory data analysis (EDA) and robust statistical procedures. These are the median filter (MF) and the adaptive trimmed mean filter (ATM) for the smoothing of regional geochemical data to reduce spurious variations; two new filters, the fence filter (FF) and the notch filter (NF), have been developed to define geochemical anomalies.The application of the spatial filtering techniques is illustrated by Zn data from approximately 3100 stream sediment samples taken in a regional geochemical survey over 25,000 km² of the western margin of the São Francisco Basin, Brazil. Regional distribution patterns for Zn obtained by the MF and ATM filters are clearly related to known stratigraphic units. Anomaly filtering using the FF and NF has delineated most known base metal and gold occurrences, as well as a number of anomalies located in geologically favourable environments but unrelated to any known mineralization. The two anomaly filters have, for the most part, defined the same anomalies in the study area but only the NF highlights the anomaly associated with the important Morro Agudo Pb-Zn deposit, which is too subtle to be immediately apparent in the unprocessed data.     

Noise Removal from Duplicate Paleoceanographic Time-Series: The Use of Adaptive Filtering Techniques

This study demonstrates that adaptive filters can be used successfully to remove noise from duplicate paleoceanographic time-series. Conventional methods for noise canceling such as fixed filters cannot be applied to paleoceanographic time-series if optimal filtering is to be achieved, because the signal-to-noise ratio is unknown and varies with time. In contrast, an adaptive filter automatically extracts information without any prior initialization of the filter parameters. Two basic adaptive filtering methods, the gradient-based stochastic least-mean-squares (LMS) algorithm and the recursive least-squares (RLS) algorithm have been modified for paleoceanographic applications. The RLS algorithm can be used for noise removal from duplicate records corrupted by stationary noise, for example, carbonate measurements, species counts, or density data. The RLS filter performance is characterized by high accuracy and fast rate of convergence. The modified LMS algorithm out-performs the RLS procedure in a nonstationary environment (e.g., stable isotope records) but at the price of a slower rate of convergence and a reduced accuracy in the final estimate. The application of both algorithms is demonstrated by means of carbonate and stable isotope data.     

VSP波场分离的径向中值滤波方法

在VSP资料中,中值滤波法是一种简单有效的波场分离方法,主要适用于简单线性波场分离。提出并实现的径向中值滤波方法,除具有常规中值滤波方法的优势外,对具有发散状多方向线性同相轴轨迹的干扰波场,其波场分解可一次完成。通过井中地震(VSP)实例测试表明,该方法能够更有效地分离VSP上下行波场,以及P波和P-SV波分解,且在压制面波或提取面波处理方面具有潜在的应用前景。