Further improvement of temporal resolution of seismic data by autoregressive (AR) spectral extrapolation

Seismic data have still no enough temporal resolution because of band-limited nature of available data even if it is deconvolved. However, lower and higher frequency information belonging to seismic data is missing and it is not directly recovered from seismic data. In this paper, a method originally applied by Honarvar et al. [Honarvar, F., Sheikhzadeh, H., Moles, M., Sinclair, A.N., 2004. Improving the time-resolution and signal–noise ratio of ultrasonic NDE signals. Ultrasonics 41, 755–763.] which is the combination of the most widely used Wiener deconvolution and AR spectral extrapolation in frequency domain is briefly reviewed and is applied to seismic data to improve temporal resolution further. The missing frequency information is optimally recovered by forward and backward extrapolation based on the selection of a high signal–noise ratio (SNR) of signal spectrum deconvolved in signal processing technique. The combination of the two methods is firstly tested on a variety of synthetic examples and then applied to a stacked real trace. The selection of necessary parameters in Wiener filtering and in extrapolation are discussed in detail. It is used an optimum frequency windows between 3 and 10 dB drops by comparing results from these drops, while frequency windows are used as standard between 2.8 and 3.2 dB drops in study of Honarvar et al. [Honarvar, F., Sheikhzadeh, H., Moles, M., Sinclair, A.N., 2004. Improving the time-resolution and signal–noise ratio of ultrasonic NDE signals. Ultrasonics 41, 755–763.]. The results obtained show that the application of the purposed signal processing technique considerably improves temporal resolution of seismic data when compared with the original seismic data. Furthermore, AR based spectral extrapolated data can be almost considered as reflectivity sequence of layered medium. Consequently, the combination of Wiener deconvolution and AR spectral extrapolation can reveal some details of seismic data that cannot be observed in raw signal or which lost during the previous processing.     

Vibroseis deconvolution: A comparison of pre and post correlation vibroseis deconvolution data in real noisy data

Vibroseis is a source used commonly for inland seismic exploration. This non-destructive source is often used in urban areas with strong environmental noise. The main goal of seismic data processing is to increase the signal/noise ratio where a determinant step is deconvolution. Vibroseis seismic data do not meet the basic minimum-phase assumption for the application of spiking and predictive deconvolution, therefore various techniques, such as phase shift, are applied to the data, to be able to successfully perform deconvolution of vibroseis data.This work analyzes the application of deconvolution techniques before and after cross-correlation on a real data set acquired for high resolution prospection of deep aquifers. In particular, we compare pre-correlation spiking and predictive deconvolution with Wiener filtering and with post-correlation time variant spectral whitening deconvolution. The main result is that at small offsets, post cross-correlation spectral whitening deconvolution and pre-correlation spiking deconvolution yield comparable results, while for large offsets the best result is obtained by applying a pre-cross-correlation predictive deconvolution.     

Using the Wiener–Levinson algorithm to suppress ground-roll

In land seismic surveys, the seismic data are mostly contaminated by ground-roll noise, high amplitude and low frequency. Since the ground-roll is coherent with reflections and depends on the source, the spectral band of seismic signal and ground-roll always overlap, which can be clearly seen in the spectral domain. So, separating them in time or frequency domain commonly causes waveform distortions and information missing due to cut-off effects. Therefore, the combination of these factors leads to search for alternative filtering methods or processes. We applied the conventional Wiener–Levinson algorithm to extract ground-roll from the seismic data. Then, subtracting it from the seismic data arithmetically performs the ground-roll suppression. To set up the algorithm, linear or nonlinear sweep signals are used as reference noise trace. The frequencies needed in creating a reference noise trace using analytical sweep signal can be approximately estimated in spectral domain. The application of the proposed method based on redesigning of Wiener–Levinson algorithm differs from the usual frequency filtering techniques since the ground-roll is suppressed without cutting signal spectrum. The method is firstly tested on synthetics and then is applied to a shot data from the field. The result obtained from both synthetics and field data show that the ground-roll suppression in this way causes no waveform distortion and no reduction of frequency bandwidth of the data.     

Sparsity‐enhanced wavelet deconvolution

We propose a three‐step bandwidth enhancing wavelet deconvolution process, combining linear inverse filtering and non‐linear reflectivity construction based on a sparseness assumption. The first step is conventional Wiener deconvolution. The second step consists of further spectral whitening outside the spectral bandwidth of the residual wavelet after Wiener deconvolution, i.e., the wavelet resulting from application of the Wiener deconvolution filter to the original wavelet, which usually is not a perfect spike due to band limitations of the original wavelet. We specifically propose a zero‐phase filtered sparse‐spike deconvolution as the second step to recover the reflectivity dominantly outside of the bandwidth of the residual wavelet after Wiener deconvolution. The filter applied to the sparse‐spike deconvolution result is proportional to the deviation of the amplitude spectrum of the residual wavelet from unity, i.e., it is of higher amplitude; the closer the amplitude spectrum of the residual wavelet is to zero, but of very low amplitude, the closer it is to unity. The third step consists of summation of the data from the two first steps, basically adding gradually the contribution from the sparse‐spike deconvolution result at those frequencies at which the residual wavelet after Wiener deconvolution has small amplitudes. We propose to call this technique “sparsity‐enhanced wavelet deconvolution”. We demonstrate the technique on real data with the deconvolution of the (normal‐incidence) source side sea‐surface ghost of marine towed streamer data. We also present the extension of the proposed technique to time‐varying wavelet deconvolution.     

Seismic data reconstruction using multidimensional prediction filters

In this paper we discuss a beyond‐alias multidimensional implementation of the multi‐step autoregressive reconstruction algorithm for data with missing spatial samples. The multi‐step autoregressive method is summarized as follows: vital low‐frequency information is first regularized adopting a Fourier based method (minimum weighted norm interpolation); the reconstructed data are then used to estimate prediction filters that are used to interpolate higher frequencies. This article discusses the implementation of the multi‐step autoregressive method to data with more than one spatial dimension. Synthetic and real data examples are used to examine the performance of the proposed method. Field data are used to illustrate the applicability of multidimensional multi‐step autoregressive operators for regularization of seismic data.     

S变换谱分解技术在深反射地震弱信号提取中的应用

在深反射地震资料处理中,当来自深部的有效弱信号和噪声干扰频带差异较小且难以区分时,传统滤波方法的应用会受到限制.谱分解方法是一种使用离散傅里叶变换,基于信号的频率-振幅谱等信息生成高分辨率地震图像的方法,通常用来识别介质物性横向分布特征,处理复杂介质内频谱变化和局部相位的不稳定性等问题,包括定位复杂断层和小尺度断裂等.S变换作为一种新的时频分析方法,具有自动调节分辨率的能力,近些年来被广泛应用到勘探地震、大地电磁等数据处理中,逐渐成为地球物理方法中噪声压制的有效方法之一.与常规石油反射地震资料相比,深反射主动源地震为了探测深部结构信息,常采用大药量激发方式、长排列观测系统等,导致深部有效信号基本湮灭在噪声干扰之中.针对深反射数据特点,本文结合谱分解和S变换技术,首先设计了简单的脉冲函数实验数据,证实S变换方法的有效性,同时说明谱分解方法的效果受所用时频分析方法影响较大,而其中决定分辨能力的变换窗函数的选取尤为重要.在此基础上,分别应用到深反射地震资料的单道和叠加剖面实际数据上,对比分析了传统变换谱分解和S变换谱分解的应用效果,单道资料对比结果表明:相比传统谱分解,S变换谱分解方法具有自动调节分辨率的能力,能够精确的标定深反射地震资料中弱信号不同时刻的频率分量;叠加剖面资料应用结果表明:由S变换谱分解得到的剖面结果与其他谱分解方法结果整体上具有较高的一致性,同时清晰地刻画出原叠加剖面上被噪声湮灭的低频细节特征,提高了剖面的分辨率及同相轴连续性;对比结果明显看出,Gabor变换谱分解方法得到的结果同相轴较为破碎,分析原因认为这是由Gabor变换的时频分解方法的定长窗函数所致,窗口大小不会随着信号频率的变化来调节长度,只能在处理的过程中根据一定的记录长度范围选取窗函数参数,而S变换谱分解方法在窗函数的选取时,通过时变信号的局部频率特征自动调节窗口长度,能够更好的刻画各个频段的细节特征,在深反射剖面成像应用中效果尤为明显.本文结果表明S变换谱分解技术在深地震叠加剖面上的应用有效地提高了来自深部弱反射信号的信噪比和分辨率,并刻画出了叠加剖面上所不具有的低频细节特征,在实际深反射地震资料处理中能有效保护低频弱信号获得更好的成像效果.本文为深地震反射资料中弱信号的保护处理找到一种有效的方法.     

Drill‐bit seismic interferometry with and without pilot signals*

We use different interferometry approaches to process the seismic signals generated by a drill‐bit source in one well and recorded by seismic receivers located both in a second borehole and at the surface near the source well. We compare the standard interferometry results, obtained by using the raw drill‐bit data without a pilot signal, with the new interferometry results obtained by using the drill‐bit seismograms correlated with a reference pilot signal. The analysis of the stationary phase shows that the final results have different S/N levels and are affected by the coherent noise in the form of rig arrivals. The interferometry methods are compared by using different deconvolution approaches. The analysis shows that the results agree with the conventional drill‐bit seismograms and that using the reference pilot signal improves the quality of the drill‐bit wavefields redatumed by the interferometry method.     

叠前地震资料提高分辨率处理方法及应用

对于隐蔽性油气藏和复杂构造油气藏,地震反射资料难以满足精度要求,需要开展地震资料提高分辨率处理.为此,使用反Q滤波、广义S变换、谱整形技术及谱白化技术等方法处理了涠西南地区叠前地震资料,并且分析了四种提高分辨率方法的应用效果.结果表明,四种方法都能提高主频、拓宽频带,其中反Q滤波的效果最好,广义S变换效果次之.反Q滤波结果中波组的低频和中高频能量分配合理,并且在中高频段反Q滤波结果的信噪比明显高于其它三种方法.此外,使用不同Q值对反Q滤波结果影响比较大.随着Q值增加,主频和带宽都稍有降低的趋势,但是信噪比提高了.当Q值大于200.0时信噪比改善的空间已经很小,这时再提高Q值,换来的只是主频降低和带宽缩小.     

IMPULSE RESPONSE MODELS FOR NOISY VIBROSEIS† DATA*

A new method of Vibroseis deconvolution has been recently proposed by the authors. This discussion describes the effects of noise on the application of this method. The initial deconvolution step involves estimating the spectrum of the Vibroseis wavelet by homomorphic filtering. It is shown that noise causes problems with phase estimation. Hence, the Vibroseis wavelet is assumed to be zero phase. Examples demonstrate that zero phase cepstral filtering is a robust wavelet estimation approach for noisy data. The second step of the deconvolution method forms an impulse response model by a spectral extension method. Although this step can improve the resolution of seismic arrivals, it must be applied with caution in view of the deleterious effects of noise.     

时频域相位滤波在远震接收函数噪声压制中的应用

宽频带地震观测数据中有效信号和干扰噪声经常发生混频效应,常规的频率域滤波方法很难将二者分离.地震波信号属于时变非平稳信号,时频分析方法能够同时得到地震波信号随着时间和频率变化的振幅和相位特征,S变换是其中较为高效的时频分析工具之一.本文以S变换为例,提出了基于相位叠加的时频域相位滤波方法.与传统叠加方法相比,相位叠加方法对强振幅不敏感,对波形一致性相当敏感,更加利于有效弱信号信息的检测.时频域相位滤波方法滤除与有效信号不相干的背景噪声,保留了相位一致的有效信号成分,显著提高了信噪比.运用理论合成的远震接收函数数据和实际的宽频带地震观测数据检验结果显示该方法较传统的带通滤波方法相比,即使在信噪较低且混频严重条件下,时频域相位滤波方法的滤波效果依然很明显,有助于识别能量较弱的有效信号.     

CORRECTING FOR COLOURED PRIMARY REFLECTIVITY IN DECONVOLUTION1

Statistical deconvolution, as it is usually applied on a routine basis, designs an operator from the trace autocorrelation to compress the wavelet which is convolved with the reflectivity sequence. Under the assumption of a white reflectivity sequence (and a minimum-delay wavelet) this simple approach is valid. However, if the reflectivity is distinctly non-white, then the deconvolution will confuse the contributions to the trace spectral shape of the wavelet and reflectivity. Given logs from a nearby well, a simple two-parameter model may be used to describe the power spectral shape of the reflection coefficients derived from the broadband synthetic. This modelling is attractive in that structure in the smoothed spectrum which is consistent with random effects is not built into the model. The two parameters are used to compute simple inverse- and forward-correcting filters, which can be applied before and after the design and implementation of the standard predictive deconvolution operators. For whitening deconvolution, application of the inverse filter prior to deconvolution is unnecessary, provided the minimum-delay version of the forward filter is used. Application of the technique to seismic data shows the correction procedure to be fast and cheap and case histories display subtle, but important, differences between the conventionally deconvolved sections and those produced by incorporating the correction procedure into the processing sequence. It is concluded that, even with a moderate amount of non-whiteness, the corrected section can show appreciably better resolution than the conventionally processed section.     

Spectral bandwidth enhancement of GPR profiling data using multiple-frequency compositing

The amplitude spectrum of ground penetrating radar (GPR) reflection data acquired with a particular antenna set is normally concentrated over a spectral bandwidth of a single octave, limiting the resolving power of the GPR wavelet. Where variously-sized GPR targets are located at numerous depths in the ground, it is often necessary to acquire several profiles of GPR data using antennas of different nominal frequencies. The most complete understanding of the subsurface is obtained when those frequency-limited radargrams are jointly interpreted, since each frequency yields a particular response to subsurface reflectivity. The application of deconvolution to GPR data could improve image quality, but is often hindered by limited spectral bandwidth.We present multiple-frequency compositing as a means of combining data from several frequency-limited datasets and improving the spectral bandwidth of the GPR profile. A multiple-frequency composite is built by summing together a number of spatially-coincident radargrams, each acquired with antennae of different centre frequency. The goal of the compositing process is therefore to produce a composite radargram with balanced contributions from frequency-limited radargrams and obtain a composite wavelet that has properties approximating a delta function (i.e. short in duration and having a broad, uniform spectral bandwidth).A synthetic investigation of the compositing process was performed using Berlage wavelets as proxies for GPR source pulses. This investigation suggests that a balanced, broad bandwidth, effective source pulse is obtained by a compositing process that equalises the spectral maxima of frequency-limited wavelets prior to summation into the composite. The compositing of real GPR data was examined using a set of 225, 450 and 900 MHz GPR common offset profiles acquired at a site on the Waterloo Moraine in Ontario, Canada. The most successful compositing strategy involved derivation of scaling factors from a time-variant least squares analysis of the amplitude spectra of each frequency-limited dataset. Contributions to the composite from each nominal acquisition frequency are clear, and the trace averaged amplitude spectrum of the corresponding composite is broadened uniformly over a bandwidth approaching two-octaves. Improvements to wavelet resolution are clear when a composite radargram is treated with a spiking deconvolution algorithm. Such improvement suggests that multiple-frequency compositing is a useful imaging tool, and a promising foundation for improving deconvolution of GPR data.     

Repeatability analysis of land time‐lapse seismic data: CO2CRC Otway pilot project case study

Time‐lapse seismics is the methodology of choice for remotely monitoring changes in oil/gas reservoir depletion, reservoir stimulation or CO₂ sequestration, due to good sensitivity and resolving power at depths up to several kilometres. This method is now routinely applied offshore, however, the use of time‐lapse methodology onshore is relatively rare. The main reason for this is the relatively high cost of commercial seismic acquisition on land. A widespread belief of a relatively poor repeatability of land seismic data prevents rapid growth in the number of land time‐lapse surveys. Considering that CO₂ sequestration on land is becoming a necessity, there is a great need to evaluate the feasibility of time‐lapse seismics for monitoring. Therefore, an understanding of the factors influencing repeatability of land seismics and evaluating limitations of the method is crucially important for its application in many CO₂ sequestration projects. We analyse several repeated 2D and 3D surveys acquired within the Otway CO₂ sequestration pilot project (operated by the Cooperative Research Centre for Greenhouse Technologies, CO2CRC) in Australia, in order to determine the principal limitations of land time‐lapse seismic repeatability and investigate the influence of the main factors affecting it. Our findings are that the intrinsic signal‐to‐noise ratio (S/N, signal to coherent and background noise levels) and the normalized‐root‐mean‐square (NRMS) difference are controlled by the source strength and source type. However, the post‐stack S/N ratio and corresponding NRMS residuals are controlled mainly by the data fold. For very high‐fold data, the source strength and source type are less critical.     

基于频谱分析识别电磁波信号干扰与地震异常

处理北京地区2009-2012年5个高采样率数字CNEM08-Ⅰ型电扰动台站数据,通过频谱分析,研究数字电磁波正常本底信号,地铁、地电供电、电磁感应等于扰信号,以及地震异常信号的频谱特征.结果表明：在时间域,数字电磁波的持续型干扰信号与震前电磁波信号表现相似,为连续高值脉冲信号;而在频域,数字电磁波干扰信号往往影响频带较窄,优势频率能量突出,优势频率频带窄到近乎以谱线的形式出现,谱线具有离散性、谐波性、衰减性特征;而震前信号具有连续的较宽频带,衰减较慢.     

基于频率搬移的地震资料约束测井资料外推

于地震资料本身频带有限的特性,导致在利用地震资料作为约束条件进行测井资料外推时存在奇异性. 文中利用通信中常用的频率搬移技术,将频带有限的地震资料转化成一种频带拓宽的伪超分辨率资料来控制测井资料的外推,从而解决地震资料约束下的测井资料外推技术中的奇异性问题. 并利用同相轴自动追踪和时频分析技术,解决子波时变的问题,实现沿地层自适应地外推测井资料. 对实际资料的测井速度和反射系数外推结果表明, 此法具有较好的应用前景.     

Signal-purity-spectrum-based colored deconvolution

Signal to noise ratio (SNR) and resolution are two important but contradictory characteristics used to evaluate the quality of seismic data. For relatively preserving SNR while enhancing resolution, the signal purity spectrum is introduced, estimated, and used to define the desired output amplitude spectrum after deconvolution. Since a real reflectivity series is blue rather than white, the effects of white reflectivity hypothesis on wavelets are experimentally analyzed and color compensation is applied after spectrum whitening. Experiments on real seismic data indicate that the cascade of the two processing stages can improve the ability of seismic data to delineate the geological details.     

基于波动方程的上下缆地震数据鬼波压制方法研究

本文发展基于波动方程的上下缆鬼波压制方法,推导了上下缆地震波场频率波数域波动方程延拓合并公式.基于Fourier变换的波场解析延拓确保上下缆资料振幅相位的一致性,消除了长拖缆远偏移距信号的计算误差,同时具有较高的计算效率;上下缆地震波场的波动方程法合并有效解偶鬼波干涉,实现综合利用上下缆地震数据压制鬼波.理论模型数据和实际采集地震数据的测试表明了方法的有效性.     

Marine,seabed, and land seismic equipment for broadband acquisition: a review

The broadband capabilities of marine, seabed, and land seismic equipment are reviewed with respect to both the source and the receiver sides. In marine acquisition, the main issue at both ends of the spectrum relates to ghosts occurring at the sea surface. Broadband deghosting requires towing at variable depth to introduce notch diversity or using new equipment like multi‐component and/or low‐noise streamers. As a result, a doubling of the bandwidth from about three to six octaves (2.5–200 Hz) has been achieved. Such improvement is not yet observed for seabed surveys in spite of deghosting being a standard process on the receiver side. One issue may be related to the coupling of the particle motion sensor, particularly at high frequencies. For land acquisition, progress came from the vibrators. New shakers and control electronics using broadband sweeps made it possible to add two more octaves to the low‐frequency signal (from 8 to 2 Hz). Whereas conventional 10 Hz geophones are still able to record such low frequencies, 5 Hz high gain geophones or digital accelerometers enhance them to keep the signal above the noise floor. On the high end of the bandwidth, progress is not limited by equipment specifications. Here, the issue is related to a low signal‐to‐noise ratio due to the strong absorption that occurs during signal propagation. To succeed in enlarging the bandwidth, these improved equipment and sweeps must be complemented by a denser spatial sampling of the wavefield by point–source and point–receiver acquisition.     

克拉玛依南地震波谱变化初探

利用单台数字地震波形资料,开展地震波谱分析。首先选择研究区中2001年以来信噪比较高的68个地震(4.0≥Ms≥3.0),测定地震波谱特征量和应力降,然后讨论这些量随时间的变化特征及其与中强震的对应关系,以此作为监视研究区内应力状态变化的测震学指标。     

基于保角变换的双谱域相位谱估计方法及其在地震子波估计中的应用(英文)

地震子波估计是地震资料处理与解释中的重要环节,它的准确与否直接关系到反褶积及反演等结果的好坏。高阶谱(双谱和三谱)地震子波估计方法是一类重要的、新兴的子波估计方法,然而基于高阶谱的地震子波估计往往因为高阶相位谱卷绕的原因,导致子波相位谱求解产生偏差,进而影响了混合相位子波估计的效果。针对这一问题,本文在双谱域提出了一种基于保角变换的相位谱求解方法。通过缩小傅里叶相位谱的取值范围,有效避免了双谱相位发生卷绕的情况,从而消除了原相位谱估计中双谱相位卷绕的影响。该方法与最小二乘法相位谱估计相结合,构成了基于保角变换的最小二乘地震子波相位谱估计方法,并与最小二乘地震子波振幅谱估计方法一起,应用到了地震资料混合相位子波估计中。理论模型和实际资料验证了该方法的有效性。同时本文将双谱域地震子波相位谱估计中保角变换的思想推广到三谱域地震子波相位谱估计中。