MATLAB programs for the synthetic models

The separation of residual gravity anomaly from regional gravity has considerably been studied for many years in gravity explorations. In addition, it is considered as a critical step in gravity data inversion. Some techniques have been developed for regional–residual anomaly separation both in space and frequency domains. One of these techniques for computing the regional anomaly is nonlinear filtering. In this paper, some techniques such as low-pass filtering, Butterworth, upward continuation, and nonlinear filtering are used to on synthetic gravity data in present of random noise and noise free for the purpose of residual–regional anomaly separation. The obtained results of techniques are compared with each other. The results have shown that separation methods are so efficient where synthetic models are located in shallow depth. Moreover, it is found that in comparison with other separation techniques, nonlinear filtering is more efficient in residual–regional anomaly separation and upward continuation technique is more efficient than Butterworth filter and low-pass filter. In addition, all of the obtained results have shown that Butterworth and low-pass filters are the same.     

双边滤波在探地雷达数据去噪处理中的应用

在探地雷达数据的采集过程中,受外界因素影响会不可避免地混入噪声,严重干扰有效回波的识别与解译.为此,利用双边滤波算法进行探地雷达数据的去噪处理,通过在探地雷达正演记录加入高斯白噪声来模拟实测的探地雷达记录,利用双边滤波器对含噪声的合成记录进行滤波处理,结果表明双边滤波算法能除去大部分高斯噪声,突出有效回波信息,峰值信噪...     

Denoising and improving the quality of seismic data using combination of DBM filter and FX deconvolution

Seismic data denoising, random noise attenuation (RNA) and spike-like noise suppression, is a main consideration for improving the quality of records. RNA could increase signal to noise ratio (S/N) to avoid misinterpretation of seismic data. In this research, a novel method is created by using the combination of frequency-offset deconvolution (FXD) and decision-based median (DBM) filter for RNA from seismic data. The method is applied in two main phases; FXD is focused to remove the Gaussian noise and DBM filter is focused to attenuate the impulsive noise and spikes. To implement and verify the method, three types of data are used: two synthetic models (a model with linear events and a model with hyperbolic events) and an observed seismic section. The ability of the proposed method (FXD-DBM) in comparison of applying each in seismic RNA application is proven. The noise level is reduced obviously, and hence, the S/N of all examined seismic records is increased considerably after denoising by the combination of FX deconvolution and DBM filter. About the real seismic section, suppressing random noise and spikes show up improving the seismic reflector continuity and hence enhancing the interpretability of data. Moreover, some masked events by random noise are clarified in different parts of data after denoising using the planned method.     

Shearlet变换在GPR数据随机噪声压制中的应用

随机噪声是探地雷达(ground penetrating radar,GPR)数据处理存在的主要问题之一,直接影响到GPR数据后续处理及最终解释的准确性和可靠性。为了有效地去除随机噪声,同时更好地保留GPR信号的有效信息,本文提出基于Shearlet变换的GPR数据随机噪声去除方法。作为一种非自适应多尺度、多方向性的几何分析方法,Shearlet变换能够近乎最优地表示含奇异点的高维曲线。在Shearlet域,GPR数据能够得到更加稀疏的表示,通过阈值去噪的方法,有效地去除了随机噪声,使信噪比提高了4dB,最大程度地保留了GPR有效信号。利用理论和实际数据进行验证,体现了Shearlet变换阈值去噪方法的有效性和准确性。     

分形技术在探地雷达资料处理解释中的应用

将分形理论应用到探地雷达 (GPR)资料处理解释中 ,以提高探地雷达剖面的分辨率。通过建立相应的GPR的fBm模型 ,采用逐次随机增加方法 (SuccessiveRandomAdditions)对GPR数据进行细分。实验分析表明 ,分形处理是一种提取GPR高分辨率信息的非常有效的方法 ,其效果要比常规处理 (如线性滤波等 )明显 ;最后用分形技术对实际探地雷达检测剖面进行了处理 ,取得了较好效果     

不同滤波算法在土壤湿度同化中的应用

为研究不同滤波算法在土壤湿度同化中的有效性,以及土壤湿度模拟结果对模型参数的敏感性,结合简单生物圈模型SiB2,设置敏感性实验,探求土壤饱和水力传导度对土壤湿度模拟结果的影响;并在此基础上,采用集合卡尔曼滤波（EnKF）、无迹卡尔曼滤波（UKF）和无迹粒子滤波（UPF）开展土壤湿度实时同化实验。结果表明：土壤饱和水力传导度能显著影响土壤湿度模拟精度;利用EnKF、UKF、UPF同化站点观测数据,均能改善土壤湿度模拟结果;3种同化方法在不同土壤层的同化效果不同,在土壤表层,EnKF的有效性优于UKF和UPF,在根域层和土壤深层,3种滤波方法有效性在降雨前后相差较大。因此,针对性地选择同化方法,是提高土壤湿度模拟精度的有效手段。     

随机介质中的探地雷达叠前逆时偏移成像

为了更好地分析探地雷达(GPR)叠前逆时偏移算法对实际地下随机分布介质的成像效果,采用随机过程的谱分解和混合型自相关函数理论构建了不同自相关长度的GPR随机介质模型。基于时域有限差分法(FDTD)构建了GPR叠前逆时偏移成像算法,其中FDTD用于计算正传和反传电磁波场,归一化互相关成像条件用于获取逆时偏移成像剖面。在此基础上,利用该算法对两个随机介质模型的多偏移距正演数据进行计算,并与相应背景介质为均匀介质的逆时偏移结果进行对比。结果表明:电磁波在随机介质中散射强烈,反射波扭曲变形、不连续,形成了明显的随机扰动,致使逆时偏移成像剖面的空间分辨率更低,低频噪声更强;自相关长度是影响随机介质中异常体成像效果的主要因素,自相关长度越小,异常体的成像越清晰,自相关长度越大,异常体的成像效果越差,且不易被识别。     

瞬时属性估计器在探地雷达数据处理中的应用

为了提高浅层埋藏目标识别的瞬时物理属性的精度,根据极平坦频率特性有限脉冲相应滤波器的思想,首次提出用它作为微分器和延时器组成解析信号瞬时属性估计器（FIFM）,对探地雷达信号的瞬时属性进行提取。结果表明,瞬时属性剖面的分辨率得到了明显的提高;采用瞬时属性估计器进行探地雷达信号瞬时参数的研究是一种非常有效的方法,可用于公路、桥梁、隧道等结构物的无损检测数据分析。      

Multiscale analysis of noisy 3D GPR data using the directional continuous wavelet transform

Here, we present a new technique of noise effect attenuation in the 3D ground-penetrating radar (GPR) data analysis using the 2D directional continuous wavelet transform (DCWT). The proposed technique is based on the application of a Gaussian low pass filter to the modulus of the 2D DCWT for low scales. After application of the low pass filter, maxima of the CWT are mapped for all range of scales. Application to a noisy GPR data shows that the proposed idea can improve GPR data analysis by the continuous wavelet transform.     

An Empirical Method for Optimal Robust Regional-Residual Separation of Geophysical Data

Prior to interpretation and further analysis, many datasets must first be separated into regional and residual components. Traditional techniques are either subjective (e.g., graphical methods) or nonrobust (e.g., all least-squares based methods). Bathymetric data, with their broad spectrum, pose serious difficulties to these traditional methods, in particular those based on spectral decomposition. Spatial median filters offer a solution that is robust, objective, and often defines regional components similar to those produced graphically by hand. Characteristics of spatial median filters in general are discussed and a new empirical method is presented for determining the width of the robust median filter that accomplishes an optimal separation of a gridded dataset into its regional and residual components. The method involves tracing the zero-contour of the residual component and evaluating the ratio between the volume enclosed by the surface inside this contour and the contour's area. The filter width giving the highest ratio (or mean amplitude) is called the Optimal Robust Separator (ORS) and is selected as the optimal filter producing the best separation. The technique allows a unique and objective determination of the regional field and enables researchers to undertake reproducible separations of regional and residual components. The ORS method is applied to both synthetic data and bathymetry/topography of the Hawaiian Islands; ways to improve the technique using alternative diagnostic quantities are discussed.     

Seismic random noise attenuation using artificial neural network and wavelet packet analysis

In this paper, we present a method for attenuating background random noise and enhancing resolution of seismic data, which takes advantage of semi-automatic training of feed forward back propagation (FFBP) artificial neural network (ANN) in a multiscale domain obtained from wavelet packet analysis (WPA). The images of approximations and details of the input seismic sections are calculated and utilized to train neural network to model coherent events by an automatic algorithm. After the modeling of coherent events, the remainder data are assumed to be related to background random noise. The proposed method is applied on both synthetic and real seismic data. The results are compared with that of the adaptive Wiener filter (AWF) in synthetic shot gather and real common midpoint gather and also with that of band-pass filtering on real common offset gather. The comparison indicates substantially higher efficiency of the proposed method in attenuating random noise and enhancing seismic signals.     

Estimating geometrical parameters of cylindrical targets detected by ground-penetrating radar using template matching algorithm

In the current research, the ground-penetrating radar (GPR) method has been employed to identify physical and geometrical parameters of buried cylindrical structures using the pattern recognition approach. To achieve this goal, the well-established mathematical relationships between geometrical parameters of cylindrical target (radius, burial depth, and horizontal location) and the associated GPR hyperbolic response characteristics are employed using the template matching method. In order to validate the applicability of the template matching method in providing estimates of such parameters, the method is first examined on GPR responses of synthetic models with known geometrical parameters followed by applying on real data using two different similarity criteria including 2-D spatial convolution and normalized cross correlation in the wave number domain. In the first step, the GPR responses of 71 synthetic models encompassing one, two, and three horizontal cylinders were produced using the improved 2-D finite difference in frequency domain. Then, appropriate preprocessing sequences to reduce random noise caused by forward modeling were applied on synthetic data. The proposed algorithm applied on several synthetic model responses could estimate the known geometrical parameters of the buried cylinders with acceptable accuracy (maximum error of 15%). The template matching algorithm was also used to extract geometrical parameters of water and wastewater pipes buried in Imam Hossein Square, Isfahan city, as real GPR data. Depending on environmental conditions and subsurface host formation, the real GPR data normally contain a variety of noises; therefore, a series of appropriate objective preprocessing and processing stages were designed in order to apply on real GPR images before deploying template matching algorithm. The applicability of the template matching algorithm on real data and validity of the estimated parameters were proved based on assessing the accuracy of the estimated geometrical parameters of respective pipes through GPR response versus the measured parameters. The proposed algorithm was designed in such a way that all steps of estimating geometrical parameters of buried cylindrical targets are automatically carried out.     

探地雷达在桥塔塔基岩溶勘查中的应用及信号分析

以湖南省张家界—花垣县高速公路岩溶勘查为例,探讨探地雷达在竖直型岩溶勘查中的应用和效果;同时,说明复信号分析方法在探地雷达数据处理中的有效性。竖向岩溶的横向规模小,在雷达图像中相应的异常范围比较窄,异常不易分辨。首先对原始采集信号进行二维空间域滤波,再对信号进行Hilbert变换,提取雷达信号的瞬时振幅、瞬时相位和瞬时频率,然后对这些处理后的信号进行综合分析。研究结果表明,二维空间域滤波可大大消除高频噪声的干扰,提高信号的信噪比,多参数综合分析可提高探地雷达解释的精度,最终的钻探成果也验证了反演解释结果的正确性。     

移动平台全张量重力梯度数据的噪声抑制

全张量重力梯度仪器测量数据中包含了大量的白噪声和有色噪声。传统的数字滤波器只能滤除某一频段外的噪声,对于混叠在重力梯度有用信号频段范围内的有色噪声不能很好的对其进行分离。为了同时滤除白噪声和有色噪声,笔者利用卡尔曼滤波器采用增广矩阵法将全张量重力梯度数据中的有色噪声进行估计,在抑制白噪声的同时将有用信号和有色噪声分离,并利用数字滤波器与卡尔曼滤波器的优点,将其结合生了更好的滤波效果,得到了更高质量的梯度信号。通过模型试验验证了本方法对噪声的滤波能力,并满足高精度重力梯度数据处理要求。     

Adaptive boxcar background filtering for real-time GPR utility detection

Ground Penetrating Radar (GPR) investigation tools are increasingly used for real-time detection of underground utilities. Background noise is an annoying problem, because it sometimes masks the reflection from objects of interest. This study introduces an efficient background removal algorithm, which is so simple that it can be incorporated into GPR logging devices. The algorithm is based on the recently published outliers-out algorithm for stacking seismic data. Experiments conducted on both synthetic and field GPR data show that proposed background removal algorithm yields much better results than the commonly used average trace subtraction algorithm in a relatively comparable computational time.     

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.     

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.     

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。     

Co-Phased Median Filters, Some Peculiarities of Sweep Signal Processing

Median filters are nonlinear and a theoretical analysis of their behavior is very difficult and so are rarely used for the processing of seismic data. However, they are able to preserve steps, sharp discontinuities and edges that are lost using most other standard filters. As seismic data are mostly harmonic or frequency modulated signals in the frequency range 1 to 10 Hz, the median filter must be adapted so as to suppress noise but not unduly distort the signal. This can be accomplished by using a median filter whose length is n times that of signal period where n is even. By use of weighted-order statistics, samples of the signals closest in phase can be obtained. To illustrate the method, a signal from a frequency band of 6.3–7.5 Hz was processed and the quality of the signal enhanced two fold over the quality of the signal without processing.     

基于SVD的叠后地震资料随机噪声分离方法

笔者提出基于SVD的叠后地震资料随机噪声分离方法,在地震剖面的同相轴水平或接近水平时可以有效地分离出地震剖面中的随机噪声,提高地震剖面的分辨率。为了说明SVD随机噪声分离方法的有效性和高效性,建立模型试验,在合成地震记录中加入随机噪声,之后进行实际地震资料处理,分别用SVD方法和基于小波变换的分层阈值方法对加入随机噪声的合成记录和加入随机噪声的实际资料进行随机噪声分离处理。对比发现,SVD随机噪声分离方法相比于基于小波变换的分层阈值方法更加有效且高效。