基于SW统计量的自适应时频峰值滤波压制地震勘探随机噪声研究

由于金属矿区地震记录中随机噪声性质复杂且信噪比低,常规降噪方法难以达到预期的滤波效果.时频峰值滤波(TFPF)方法是实现低信噪比地震勘探记录中随机噪声压制的有效方法,但其在复杂地震勘探随机噪声下时窗参数优化问题仍难以解决.本文充分利用地震勘探噪声的统计特性,结合Shapiro-Wilk(SW)统计量辨识地震勘探记录中的微弱有效信号,提出基于SW统计量的自适应时频峰值滤波降噪方法(S-TFPF).在S-TFPF方案中,对于有效信号集中区,S-TFPF方法根据信号频率特征,选择有利于信号保持的较短时窗长度;对于噪声集中区,按噪声方差自适应增加时窗长度,增强随机噪声压制能力.S-TFPF应用于合成记录和共炮点记录的滤波结果表明,与传统时频峰值滤波方法相比,S-TFPF方法可以有效抑制低信噪比地震勘探记录中的随机噪声,更好地恢复出同相轴.     

时间域相邻道地震波衰减成像研究

在时间域中,利用地震记录中的振幅与上升时间信息可以计算出岩石介质的品质因子Q值.由于震源能量难以测量,本文通过共炮点道集相邻道循环对比的方法,消除了震源对计算过程的影响,推导出时间域相邻道振幅与上升时间衰减成像的计算公式,并在振幅衰减成像的计算过程中,去除了非粘滞性衰减成分.为了更全面地综合利用波形信息,并充分利用各种方法的长处,将波速成像、振幅衰减成像、上升时间衰减成像集成到一个处理流程中,通过在岩体结构研究中的实际应用,证明这种综合方法具有灵活、实用、可靠的特点.     

A non-parametric wave type based model for real-time prediction of strong ground motion accelerogram

A wave type based method for real-time prediction of strong ground motion (SGM) accelerogram is developed. Real-time prediction of SGM is requested in predictive building control systems to trigger and control actuator systems achieving the goal of reduction of the structural deformations during an on-going earthquake. It is well known that SGM is a classic example of non-stationary stochastic process with temporal variation of both amplitude and frequency content. The developed non-parametric model considers the non-homogeneity of the seismic process which contains different wave types with the individual frequency contents and time-dependency amplitude distribution pattern. Therefore, an important part of the method is to detect dominant seismic wave phases. Prediction of seismic signal is undertaken by applying frequency adaptive windowing approach, which leads to predict the on-coming signal in time window t+Δt based on the measured data in the time window t. Besides use of the frequency adaptive windowing, constant windowing and semi-adaptive windowing approaches are deployed. The results show that use of the adaptive time windows relevant to dominant frequency of the signal will enable the model to catch and predict the most dominant frequencies. Performance of the proposed model is verified by the use of 97 free-field accelerograms, which were applied to train and validate the prediction model. The selected accelerograms were measured above the soil type C and D according Eurocode 8 and their Moment magnitude are ranging between 6.2 and 7.7. The learning capability of the radial basis function Artificial Neural Network is used to reconstruct the SGM accelerogram. The most significant advantage of the proposed model is the concept of wave type based modeling which has the advantage of a conceptual physical modeling of the seismic process. Comparison of the real-time predicted and the observed accelerograms shows a high correlation when the frequency adaptive approach is applied. This paper lays a foundation for more effective use of real-time predictive control systems and potential for future extension in active structural control as well as in real-time seismology.     

Waveform Retrieval and Phase Identification for Seismic Data from the CASS Experiment

The little destruction to the deployment site and high repeatability of the Controlled Accurate Seismic Source (CASS) shows its potential for investigating seismic wave velocities in the Earth's crust. However, the difficulty in retrieving impulsive seismic waveforms from the CASS data and identifying the seismic phases substantially prevents its wide applications. For example, identification of the seismic phases and accurate measurement of travel times are essential for resolving the spatial distribution of seismic velocities in the crust. Until now, it still remains a challenging task to estimate the accurate travel times of different seismic phases from the CASS data which features extended wave trains, unlike processing of the waveforms from impulsive events such as earthquakes or explosive sources. In this study, we introduce a time-frequency analysis method to process the CASS data, and try to retrieve the seismic waveforms and identify the major seismic phases traveling through the crust. We adopt the Wigner-Ville Distribution (WVD) approach which has been used in signal detection and parameter estimation for linear frequency modulation (LFM) signals, and proves to feature the best time-frequency convergence capability. The Wigner-Hough transform (WHT) is applied to retrieve the impulsive waveforms from multi-component LFM signals, which comprise seismic phases with different arrival times. We processed the seismic data of the 40-ton CASS in the field experiment around the Xinfengjiang reservoir with the WVD and WHT methods. The results demonstrate that these methods are effective in waveform retrieval and phase identification, especially for high frequency seismic phases such as PmP and SmS with strong amplitudes in large epicenter distance of 80–120 km. Further studies are still needed to improve the accuracy on travel time estimation, so as to further promote applicability of the CASS for and imaging the seismic velocity structure.     

基于褶积原理和改进广义S变换的震动波衰减补偿试验研究

为了恢复震动波能量在传播过程中产生的衰减损耗,提出基于褶积原理求取品质因子Q的方法与改进广义S变换相结合的反Q滤波法。通过震动波衰减补偿模型试验,对试验数据进行改进广义S变换的时频特性分析,得出了信号的能量分布情况以及时间频率对应关系;采用基于褶积原理求取品质因子的方法,得到时变Q值;对试验数据进行反Q滤波处理,使震动波能量得到了补偿。结果表明本文提出的反Q滤波法提高了对震动波能量衰减补偿的效果,拓宽了地震资料的频带,提高了地震资料分辨率,有利于进行高分辨率地震勘探、深部信号增强和油气藏预测工作的开展。     

谱比法地震衰减层析反演方法研究

由于地下介质对地震波能量有强烈的吸收作用,降低了地震资料的分辨率以及地震资料处理、解释的精度,因此选择合适的参数对地层吸收衰减情况进行有效描述是对地下构造进行高分辨率、高精度处理及解释的有效途径。目前品质因子Q是对岩石弹性参数进行有效描述的重要参数之一。用品质因子Q来衡量地震波能量在介质中传播的吸收衰减情况,是目前提高地震资料分辨率的有效方法,同时也是提高含油气地层解释精度的有效途径。近些年,许多学者提出了多种计算Q值的方法,其中谱比法是在实际中应用最为广泛的Q值估计方法。本文在前人方法的基础上,对谱比法进行了改进,并结合走时层析方法反演Q值,充分利用谱比法在精度、稳定性等方面的优势以及走时层析方法计算效率高的优点,不仅可以提高反演的精度而且能够保证反演的稳定性,提高计算效率。通过模型试算证明谱比法衰减层析方法能有效估计Q值变化情况,具有较好的发展前景。      

独立分量分析及其在地震信息处理中应用初探

独立分量分析(ICA)是最近才发展起来的一种统计学方法，旨在寻求对非高斯分布数据进行有效表示，使得各个分量在统计学上独立，或者尽最大可能地独立。许多应用中，这种表示意在获取数据的基本结构，包括特征提取和信号分离。本文给出ICA的基本理论和快速算法，并对FastICA稍作改进，在分析地震信号特点的基础上，对其在地震信息处理中应用进行初步探索，表明ICA在地震信号处理中具有应用前景。     

SEISMIC SIGNAL DETECTION AND PARAMETER ESTIMATION*

In the mathematical theory of seismic signal detection and parameter estimation given, the seismic measurements are assumed to consist of a sum of signals corrupted by additive Gaussian white noise uncorrelated to the signals. Each signal is assumed to consist of a signal pulse multiplied by a space-dependent amplitude function and with a space-dependent arrival time. The signal pulse, amplitude, and arrival time are estimated by the method of maximum likelihood. For this signal-and-noise model, the maximum likelihood method is equivalent to the method of least squares which will be shown to correspond to using the signal energy as coherency measure. The semblance coefficient is equal to the signal energy divided by the measurement energy. For this signal model we get a more general form of the semblance coefficient which reduces to the usual expression in the case of a constant signal amplitude function. The signal pulse, amplitude, and arrival time can be estimated by a simple iterative algorithm. The effectiveness of the algorithm on seismic field data is demonstrated.     

小波尺度域含气储层地震波衰减特征

黏弹性衰减因子Q的可靠估计可通过Q反褶积来提高地震资料的分辨率并有助于振幅分析. 本文从小波理论出发,结合地震波在黏弹性介质中的传播方程,推导出小波尺度域地震波能量衰减公式. 能量衰减公式具有下列性质：（1）Q值越大,能量衰减得越慢;Q值越小,能量衰减越严重;（2）尺度越小,信号中保留的能量越少;（3）对于脉冲源来说在理想的无衰减介质(即Q趋近于∞)中传播时,信号在不同尺度内的能量相同. 利用尺度能量公式,可从反射地震资料中直接估计品质因子Q（即衰减因子）,也可以提取不同尺度的能量衰减剖面作为储层描述的属性参数,用来进行岩性识别和指示气藏,与经典的谱比法相比,避免了谱比法所面临的双时窗问题以及进行谱估计的窗选择问题. 理论模型试验表明了本文方法的正确性和有效性.     

Seismic interferometry by tangent‐phase correction

We present a modified interferometry method based on local tangent‐phase analysis, which corrects the cross‐correlated data before summation. The approach makes it possible to synthesize virtual signals usually vanishing in the conventional seismic interferometry summation. For a given pair of receivers and a set of different source positions, a plurality of virtual traces is obtained at new stationary projected points located along the signal wavefronts passing through the real reference receiver. The position of the projected points is estimated by minimizing travel times using wavefront constraint and correlation‐signal tangent information. The method uses mixed processing, which is partially based on velocity‐model knowledge and on data‐based blind interferometry. The approach can be used for selected events, including reflections with different stationary conditions and projected points with respect to those of the direct arrivals, to extend the interferometry representation in seismic exploration data where conventional illumination coverage is not sufficient to obtain the stationary‐phase condition. We discuss possible applications in crosswell geometry with a velocity anomaly and a time lapse.     

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。     

Applications of Savitzky-Golay Filter for Seismic Random Noise Reduction

This article utilizes Savitzky–Golay (SG) filter to eliminate seismic random noise. This is a novel method for seismic random noise reduction in which SG filter adopts piecewise weighted polynomial via leastsquares estimation. Therefore, effective smoothing is achieved in extracting the original signal from noise environment while retaining the shape of the signal as close as possible to the original one. Although there are lots of classical methods such as Wiener filtering and wavelet denoising applied to eliminate seismic random noise, the SG filter outperforms them in approximating the true signal. SG filter will obtain a good tradeoff in waveform smoothing and valid signal preservation under suitable conditions. These are the appropriate window size and the polynomial degree. Through examples from synthetic seismic signals and field seismic data, we demonstrate the good performance of SG filter by comparing it with the Wiener filtering and wavelet denoising methods.     

Weak Seismic Signal Extraction Based on the Curvelet Transform

Seismic signal denoising is a key step in seismic data processing. Airgun signals are easy to be interfered with by noise when it travels a long distance due to the weak energy of active source signal of the airgun. Aiming to solve this problem, and considering that the conventional Curvelet transform threshold processing method does not use the seismic spectrum information, we independently process the Curvelet scale layer corresponding to valid data based on the characteristics of the Curvelet transform of multi-scale, multi-direction and capable of expressing the sparse seismic signals in order to fully excavate the information features. Combined with the Curvelet adaptive threshold denoising the algorithm, we apply the Curvelet transform to denoising seismic signals while retaining the weak information in the signal as much as possible. The simulation experiments show that the improved threshold denoising method based on Curvelet transform is superior to the frequency domain filtering, wavelet denoising and traditional Curvelet denoising method in detailed information extraction and signal denoising of low SNR signals. The calculation accuracy of the relative wave velocity variation of underground medium is improved.     

基于强震动台阵记录的震源破裂长度实时估测方法

本文提出一种通过小孔径台阵波束形成技术快速估测震源破裂长度的方法,同时提出了调整各台站相位的方法,即在每个台站的延时无法确定的情况下,近似地得到每个台站之间相位差的方法。在此基础上,利用自贡强震动观测台阵在汶川地震中得到的主震地震动记录进行了破裂长度的离线快速估测。结果表明,该方法的时效性较好,在地震动加速度峰值到来前约10 s时,便得到了断层破裂长度（约120 km）和相应破裂走向的估测结果,虽然此时的估测结果与最终估测结果（约230 km）有较大的偏差,但从实现快速地震预警的角度来看,还是有较好的实际意义。通过与前人的研究结果进行对比,结果显示该方法低估了东北方向的破裂长度,于是探讨了该现象产生的原因及可能的解决方案。最后对这种算法的计算速度进行了测试分析,结果表明通过并行计算该方法能够满足实时断层破裂长度估测的要求。      

Monitoring viscosity changes from time‐lapse seismic attenuation: case study from a heavy oil reservoir

Heating heavy oil reservoirs is a common method for reducing the high viscosity of heavy oil and thus increasing the recovery factor. Monitoring of these viscosity changes in the reservoir is essential for delineating the heated region and controlling production. In this study, we present an approach for estimating viscosity changes in a heavy oil reservoir. The approach consists of three steps: measuring seismic wave attenuation between reflections from above and below the reservoir, constructing time‐lapse Q and Q^?1 factor maps, and interpreting these maps using Kelvin–Voigt and Maxwell viscoelastic models. We use a 4D relative spectrum method to measure changes in attenuation. The method is tested with synthetic seismic data that are noise free and data with additive Gaussian noise to show the robustness and the accuracy of the estimates of the Q‐factor. The results of the application of the method to a field data set exhibit alignment of high attenuation zones along the steam‐injection wells, and indicate that temperature dependent viscosity changes in the heavy oil reservoir can be explained by the Kelvin–Voigt model.     

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.     

利用互相关函数求地震波衰减

与传统利用单事件波形求介质衰减的方法不同,我们提出一种以一系列事件为源,以源与远处记录波形的互相关函数为基础计算介质品质因子的方法.依据野外现场实验的数据,我们分别以单次和多次激发为源,讨论了事件波形和互相关函数波形的振幅变化及相应的介质品质因子,结果发现,与事件波形一样,互相关函数波形也可以用于计算介质的衰减系数.计算结果表明：（1）实验场地浅层介质在原场条件下的品质因子Q值在40左右;（2）互相关函数的最大幅度与事件波形的振幅随距离具有相同的衰减规律.     

Detection,Estimation of Magnitude,and Relative Location of Weak Aftershocks Using Waveform Cross-Correlation: The Earthquake of August 7, 2016, in the Town of Mariupol

The study of the stress-strain state of a medium in seismically quiet areas is difficult because of the absence of strong events. Under such circumstances, each earthquake, even relatively weak, is of high importance. In this case, all possible information on tectonic stresses and their dynamics, e.g., information on time, location, and magnitude of aftershocks, should be obtained from available seismic data. The earthquake near the town of Mariupol which occurred on August 7, 2016, had a body wave magnitude of 4.5–4.9 from the data of the different seismological centers. We detected 12 aftershocks that occurred within 5 days after the main shock using two seismic arrays (AKASG and BRTR) and one three-component station (KBZ) of the International Monitoring System, as well as two array stations of the Institute of Geosphere Dynamics, Russian Academy of Sciences. For six aftershocks, signals were found at three or more stations. The other aftershocks were detected from the data at two out of three nearest stations. Signal detection and association with aftershocks of the main shock, as well as estimation of magnitude and relative location of the found aftershocks, were carried out using the method of waveform cross-correlation (WFCC). The signals from the main shock that acted as the only master event (ME) for the WFCC method were used as waveform templates. To increase the signal-to-noise ratio and to determine the exact onset time of regular seismic waves from aftershocks, we used waveform templates of different length, from 10 to 180 s depending on the wave type and distance to the station, as well as band filtering in narrow frequency bands. The highest sensitivity of the detector and accuracy of the P-wave onset time estimates were reached when a waveform template included all regular waves from P to L _g . Association of signals with aftershocks was based on back projection of signal arrival times to origin times using the travel time from a master event to the station, which was measured with a very low error, being equal to almost half of the digitization step length. To develop a seismic event hypothesis, the origin times at two or more stations should be spaced within a 2-s interval.     

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.     

MAXIMUM LIKELIHOOD ESTIMATION OF SEISMIC REFLECTION COEFFICIENTS*

A seismic trace is modeled as a moving average (MA) process both in signal and noise: a signal wavelet convolved with a reflection coefficient series plus colored random noise. Seismic reflection coefficients can be estimated from seismic traces using suitable estimation algorithms if the input wavelet is known and vice versa. The maximum likelihood (ML) algorithm is used to estimate the system order and the reflection coefficients. The system order is related to the arrival time of the latest signal in a complex seismic reflection event. The least-squares (LS) method does not provide such information. The ML algorithm makes assumptions only about the Gaussian nature of the noise. It is better suited for seismic applications since the LS method inherits the white noise assumption. The Gauss-Newton (G-N) and Newton-Raphson (N-R) optimization algorithms are used to obtain the ML and the LS estimates. Reflection coefficient estimations are affected by the choice of sampling rate of seismic data. Theoretically, the optimum choice in system identification is the Nyquist rate. Experience with synthetic data confirms the theory. In practice, good estimates of reflection coefficients are possible only up to certain pulse separations (or, equivalently, orders). This is mostly due to numerical problems with the optimization algorithms used and partly due to the limited bandwidth of seismic signals. Good estimates from data simulated using three airgun array pulses recorded with 6–128 Hz filter setting are possible up to about 40.0 ms pulse separations. Successful estimations from pinchout and thin layer simulations and well controlled offshore “bright-spots” are given.