地震转换波测深资料数据处理程序包DSCW86

本文介绍天然地震透射转换波(PS)测深资料数据处理软件包——DSCW86。DSCW86由数字滤波、震相识别及资料分析解释组成。数字滤波部分包括:低通滤波、偏振滤波、频率加强滤波、相关滤波及叠加处理等。各种滤波方法的综合应用可以较大程度地提高原始记录的信噪比及分辨率,从而为准确地识别转换波震相提供了基础。在震相识别中采用人机联合的方法,通过偏振分析、功率分析及相位追踪等技术大大提高了震相识别能力。DSCW86还包括所有分析解释图件的计算机描绘,从而减小了工作量,提高了工作效率。     

固体潮观测资料平滑处理方法的研究

固体潮观测数据在进行各种分析之前，需进行平滑处理以便消除各种突跳及错误数据。常用的平滑方法有Ｌｅｃｏｌａｚｅｔ数字滤波法和Ｎａｋａｉ方法。本文讨论了各种方法的特点及存在问题。为了经济、快速而又有效地平滑数据，提出如下建议：对于高精度的观测数据，通常使用数字滤波法处理即可；在少数情况下，数据中出现连续错数，这时可取卅天为时间间隔，在上述滤波法平滑的基础上，分段对数据进行调和分析，如果某几段调和分析的     

1985年乌恰地震强余震（Ms=6.8）加速度记录失真的校正处理

对1985年乌恰地震强余震(Ms=6.8)取得了加速度记录。由于仪器阻尼系统故障,使得部分记录失真。本文采用数字滤波方法对原始记录进行了滤波处理,恢复了加速度记录的真实性。     

软件滤波在土体自振柱试验中的应用

自振柱试验是测量土样动剪切模量和阻尼比的常用方法,但由于噪声等环境因素的影响,土样扭剪自由振动的衰减波曲线有时会因高频干扰出现不平滑现象,难以得到合理的测试结果。软件数字滤波是解决这类问题的有效方法。本文通过多种软件数字滤波方法优缺点的对比,认为平均滤波法和惯性滤波法能有效解决试验数据中的高频干扰问题,并分别选择适当的滤波参数,得到了平滑的自振衰减波曲线;最后,采用平均滤波法处理了两组自振枉试验数据。结果表明,软件滤波法确能有效消除不合理数据,得到符合一般规律的土体动剪切模量和阻尼比试验结果,从而验证了其在土体自振柱试验中的应用价值。     

Vondrak滤波法在定点地形变资料分析中的应用

本文使用天文学数据处理中常用的Ｖｏｎｄｒａｋ平滑滤波法，对库尔勒短水准和呼图壁断层形变资料进行了高通、低通和带通数字滤波处理。结果表明，处理后的资料突出了地震前不同周期的地壳形变异常信息，降低了背景噪声和观测误差的影响。该方法对于识别形变异常有较好的效果。     

快速汉克尔变换及其在正演计算中的应用

在地球物理电(磁)法正演计算中常涉及贝塞尔函数积分,快速汉克尔数字滤波是最常用的计算方法之一.然而不同的汉克尔滤波系数,计算结果的精度也有所差异.本文对比了五组高精度快速汉克尔长滤波系数的计算精度,分析了不同核函数对计算精度的影响;同时将五种滤波系数应用于电阻率测深法、频域电磁测深法、瞬变电磁测深法的正演计算中,比较了不同滤波系数对响应和视电阻率模拟时精度的变化关系.经过大量的模型计算表明:滤波的精度并不单纯的只与滤波系数个数有关,而是多种因素综合作用的结果.本文的研究对于电(磁)法正演计算汉克尔滤波系数的选择具有指导作用,有利于节省计算机资源,提高计算效率.     

叠后储层地震滤波质量控制方法

地震数据的噪声往往覆盖了有用的地质信息,需要对地震数据进行滤波处理.在滤波处理过程中,为减少噪声对地震解释带来的假象,形成了很多相关的技术.但在地震解释滤波质量控制方面所做的研究工作很少.因此,建立叠后储层地震滤波质量控制标准,可以提高地震数据的品质及减少地震解释的假象.根据滤波前后地震资料的合成地震记录相关系数、信噪比地震属性以及时频特征三个方面对叠后储层地震资料滤波处理进行质量控制,通过对比处理前后地震资料发现:滤波后地震资料井震相关系数得到提高;滤波前后均方根地震属性变化大的地方对应信噪比属性值较小,且滤波前后地震剖面及属性与信噪比剖面及属性均具有较好的对应关系;在频谱上,滤波前后频带宽度、主频和能量保持一致.以上对地震滤波处理的控制方法中,经实际结果检验及分析可以看出,滤波前后地震资料的时频特征一致性是保证滤波质量的重要手段,另外信噪比以及与信噪比相关的地震剖面及属性在评价地震资料滤波合理性上也优于合成记录及常规地震属性对地震资料滤波质量的评价.针对叠后断裂检测实例,据该滤波质量控制标准,确保断裂检测精度.     

论组合法滤波的数学物理概念

本文以傅里叶变换为基础,用类似数学滤波中的数学分析方法,比较系统地研究了组合法滤波的数学物理概念及方法的内在规律。可以把方向特性函数P（ω）看作是一种周期“波动”函数,而组合的加权分布函数h（x）则是其离散“频谱”。因此可以引用符合于频谱分析的物理概念来研究反演问题。可以看出,组合滤波的加权分布函数及方向特性分别相当于数学滤波中的滤波因子及频率响应;而数字滤波的移门法等又可以引伸到构成组合法带通滤波中去。二者在数学上有其共性,可以互相引用,在物理上又有各自的特殊性。研究结果给组合法以比较全面的认识,扩大了组合法应用的功能。     

ADAPT系统中数字滤波及仿真分析的用户定制

数字滤波和地震计仿真在分析地震波形有着很广泛的应用。该文描述了常规滤波分析、高级滤波分析和仿真分析在Adapt系统中的实现，同时还列举了几个例子并说明了用户定制的效果。     

地震数据采集器中△-∑AD转换器512 kHz数据流的仿真

根据Δ-∑AD转换器原理,通过编程将给定的输入信号转换为1位串行Δ-∑数据流。用此数据流可以仿真地震数据采集器中的滤波抽样过程,检验设计构造的各级滤波参数能否满足地震观测的需要。为了证明该仿真程序的正确性,本文介绍了利用CS5376A公布的数字滤波参数对数据流进行滤波验证。     

多尺度形态学在地震去噪中的应用

In this paper, multi-scaled morphology is introduced into the digital processing domain for land seismic data. First, we describe the basic theory of multi-scaled morphology image decomposition of exploration seismic waves; second, we illustrate how to use multi-scaled morphology for seismic data processing using two real examples. The first example demonstrates suppressing the surface waves in pre-stack seismic records using multi-scaled morphology decomposition and reconstitution and the other example demonstrates filtering different interference waves on the seismic record. Multi-scaled morphology filtering separates signal from noise by the detailed differences of the wave shapes. The successful applications suggest that multi-scaled morphology has a promising application in seismic data processing.     

高保真VSP波场分离方法研究

三维VSP资料中,各种不同类型的波混杂一起形成复杂的波场.因此,波场分离是三维VSP数据处理关键的第一步.从不同波场的偏振方向和传播方向之差异着手,提出了一种高保真的VSP波场分离方法.首先通过射线追踪和偏振滤波的结合,把复杂波场(分解为简单波场;然后根据简单波场中不同波的传播方向截然相反的特点,进行方向滤波,达到波场分离的目的.实际数据处理表明,与常规波场分离方法相比,本方法大大降低了混波作用以及由此而生的波形畸变.     

地震面波频散的数字计算——方法与试验

在108-乙型数字计算机上进行了地震面波频散处理方法的试验。包括:（1）参数固定的和可变的数值滤波;（2）测定群速度的“移动窗”和“多重滤波”技术;（3）测定相速度的互相关法。应用了快速傅氏变换计算两个台记录的地震面波的互相关函数。使用数字处理技术分析地震面波频散,除了提高计算速度和便于处理之外,还可扩大测量周期的范围至20-70秒,从此可作出对地壳参数性质的更可靠的测定。     

南海南部深部结构的复杂构造地震成像

南海南部海底崎岖、地下构造复杂、二维地震资料中多次波非常发育,在地震数据处理中很难获得令人满意的成像效果,为此本文采用了预测反褶积后F-K域滤波及叠前时间偏移后Radon变换去除多次波的组合方案,有效地衰减了多次波,突出了有效信号能量;采用速度分析点加密法获取了更为准确的速度,实现了陡倾角构造与海山的准确成像;采用百分...     

Instantaneous polarization filtering focused on suppression of surface waves

The different characteristics of polarization of body and Rayleigh waves make it possible to separate these two types of waves by their characteristics and suppress the latter. The moving time-window analysis often is used in polarization filtering but it is difficult to determine a suitable time-window length, resulting in some problems, such as complex eigenvalues and non-convergence. For overcoming these disadvantages, in this paper, we introduce the concept of complex-trace analysis and conduct de-noise processing to suppress undesirable surface waves by instantaneous polarization analysis in the case of horizontal and vertical component seismic recordings from the Hauinan coal mine. The performance of the method is illustrated by examples with synthetic and field data and its effectiveness to remove surface waves from multi-component seismic data is demonstrated.     

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。     

Incorporation of a Non-linear Image Filtering Technique for Noise Reduction in Seismic Data

Seismic noise is a fundamental part of seismic data which cannot be avoided when conducting any seismic survey. It consists of coherent and random noise. Noise removal or filtering is one of the major concerns in the field of seismic processing. In this paper, we introduce an image filtering technique based on a detection-estimation algorithm for Gaussian and random noise removal in seismic data, namely the trilateral filter, based on a statistic called rank-ordered absolute differences. The non-linear and adaptive behaviour of this filter makes it very robust in the presence of random and coherent noise, in addition to its computational simplicity and its ability to automatically identify noise in data. We have modified the strategy of trilateral filtering by adapting the rank-ordered absolute differences formula in order to extract the signal component. We have successfully used this filter for the removal of surface waves and random spiky noise from synthetic and field data. Results are very encouraging and show the superiority of this filter compared with other filters, particularly when used recursively.     

Ground roll wave suppression based on wavelet frequency division and radial trace transform

Ground roll waves interfere with seismic data. The suppression of ground roll waves based on the division of wavelet frequencies considers the low-frequency characteristics of ground roll waves. However, this method will not be effective when the ground roll wave and the effective signal have the same frequency bands because of overlapping. The radial trace transform (RTT) considers the apparent velocity difference between the effective signal and the ground roll wave to suppress the latter, but affects the low-frequency components of the former. This study proposes a ground roll wave suppression method by combining the wavelet frequency division and the RTT based on the difference between the ground roll wave velocity and the effective signal and their energy difference in the wavelet domain, thus making full use of the advantages of both methods. First, we decompose the seismic data into different frequency bands through wavelet transform. Second, the RTT and low-cut filtering are applied to the low-frequency band, where the ground roll waves are appearing. Third, we reconstruct the seismic record without ground roll waves by using the inverse RTT and the remaining frequency bands. The proposed method not only improves the ground roll wave suppression, but also protects the signal integrity. The numerical simulation and real seismic data processing results suggest that the proposed method has a strong ability to denoise while preserving the amplitude.     

Suppression of near‐surface scattered body‐to‐surface waves: a steerable and nonlinear filtering approach

We present an approach based on local‐slope estimation for the separation of scattered surface waves from reflected body waves. The direct and scattered surface waves contain a significant amount of seismic energy. They present great challenges in land seismic data acquisition and processing, particularly in arid regions with complex near‐surface heterogeneities (e.g., dry river beds, wadis/large escarpments, and karst features). The near‐surface scattered body‐to‐surface waves, which have comparable amplitudes to reflections, can mask the seismic reflections. These difficulties, added to large amplitude direct and back‐scattered surface (Rayleigh) waves, create a major reduction in signal‐to‐noise ratio and degrade the final sub‐surface image quality. Removal of these waves can be difficult using conventional filtering methods, such as an filter, without distorting the reflected signal. The filtering algorithm we present is based on predicting the spatially varying slope of the noise, using steerable filters, and separating the signal and noise components by applying a directional nonlinear filter oriented toward the noise direction to predict the noise and then subtract it from the data. The slope estimation step using steerable filters is very efficient. It requires only a linear combination of a set of basis filters at fixed orientation to synthesize an image filtered at an arbitrary orientation. We apply our filtering approach to simulated data as well as to seismic data recorded in the field to suppress the scattered surface waves from reflected body waves, and we demonstrate its superiority over conventional techniques in signal preservation and noise suppression.     

基于EMD与EEMD的最优降噪光滑模型在地震波中的应用

目前地震波在地质构造探测和结构损伤检测中具有广泛的应用。文中将EMD和EEMD算法建立的最优降噪模型应用于地震信号去噪中。首先通过低通滤波和带通滤波算法对比分析降噪效果。然后通过对光滑性系数α取不同的值比较信号的光滑性。并利用模拟信号添加高斯白噪声干扰，在同时考虑将信号光滑性和相似性的情况下用最优降噪光滑模型对数据进行处理，最后用实际地震波验证模型在地震波数据处理中应用的可行性。结果表明，EMD和EEMD最优降噪光滑模型都能对地震波进行降噪和光滑性处理，带通滤波与EEMD算法建立的最优降噪光滑模型效果较好。在实际应用中具有更好的效果。