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1.
Single‐component towed‐streamer marine data acquisition records the pressure variations of the upgoing compressional waves followed by the polarity‐reversed pressure variations of downgoing waves, creating sea‐surface ghost events in the data. The sea‐surface ghost for constant‐depth towed‐streamer marine data acquisition is usually characterised by a ghost operator acting on the upgoing waves, which can be formulated as a filtering process in the frequency–wavenumber domain. The deghosting operation, usually via the application of the inverse Wiener filter related to the ghost operator, acts on the signal as well as the noise. The noise power transfer into the deghosted data is proportional to the power spectrum of the inverse Wiener filter and is amplifying the noise strongly at the notch wavenumbers and frequencies of the ghost operator. For variable‐depth streamer acquisition, the sea‐surface ghost cannot be described any longer as a wavenumber–frequency operator but as a linear relationship between the wavenumber–frequency representation of the upgoing waves at the sea surface and the data in the space–frequency domain. In this article, we investigate how the application of the inverse process acts on noise. It turns out that the noise magnification is less severe with variable‐depth streamer data, as opposed to constant depth, and is inversely proportional to the local slant of the streamer. We support this statement via application of the deghosting process to real and numerical random noise. We also propose a more general concept of a wavenumber–frequency ghost power transfer function, applicable for variable‐depth streamer acquisition, and demonstrate that the inverse of the proposed variable‐depth ghost power transfer function can be used to approximately quantify the action of the variable‐depth streamer deghosting process on noise.  相似文献   

2.
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.  相似文献   

3.
A marine source generates both a direct wavefield and a ghost wavefield. This is caused by the strong surface reflectivity, resulting in a blended source array, the blending process being natural. The two unblended response wavefields correspond to the real source at the actual location below the water level and to the ghost source at the mirrored location above the water level. As a consequence, deghosting becomes deblending (‘echo‐deblending’) and can be carried out with a deblending algorithm. In this paper we present source deghosting by an iterative deblending algorithm that properly includes the angle dependence of the ghost: It represents a closed‐loop, non‐causal solution. The proposed echo‐deblending algorithm is also applied to the detector deghosting problem. The detector cable may be slanted, and shot records may be generated by blended source arrays, the blending being created by simultaneous sources. Similar to surface‐related multiple elimination the method is independent of the complexity of the subsurface; only what happens at and near the surface is relevant. This means that the actual sea state may cause the reflection coefficient to become frequency dependent, and the water velocity may not be constant due to temporal and lateral variations in the pressure, temperature, and salinity. As a consequence, we propose that estimation of the actual ghost model should be part of the echo‐deblending algorithm. This is particularly true for source deghosting, where interaction of the source wavefield with the surface may be far from linear. The echo‐deblending theory also shows how multi‐level source acquisition and multi‐level streamer acquisition can be numerically simulated from standard acquisition data. The simulated multi‐level measurements increase the performance of the echo‐deblending process. The output of the echo‐deblending algorithm on the source side consists of two ghost‐free records: one generated by the real source at the actual location below the water level and one generated by the ghost source at the mirrored location above the water level. If we apply our algorithm at the detector side as well, we end up with four ghost‐free shot records. All these records are input to migration. Finally, we demonstrate that the proposed echo‐deblending algorithm is robust for background noise.  相似文献   

4.
作为一种特殊的噪声,鬼波对一次波的波形及频带宽度产生极大的影响,鬼波压制是提高海上地震资料分辨率及保真度的重要因素.以格林公式为基础,详细论述了基于格林函数理论的鬼波压制方法,在不需要地下介质信息的条件下,进行地震数据驱动鬼波压制,并根据"Double Dirichlet"(双狄利克雷)边界条件,预测压力波场和垂直速度波场.建立了基于格林函数理论鬼波压制的处理流程,数值模拟和实际资料处理结果表明,基于格林函数理论鬼波压制方法在很好地去除鬼波的同时极大地拓宽了地震资料的频带,尤其提升了低频端能量,有利于后续资料的处理解释.  相似文献   

5.
In this paper, we propose a novel three‐dimensional receiver deghosting algorithm that is capable of deghosting both horizontal and slanted streamer data in a theoretically consistent manner. Our algorithm honours wave propagation phenomena in a true three‐dimensional sense and frames the three‐dimensional receiver deghosting problem as a Lasso problem. The ultimate goal is to minimise the mismatch between the actual measurements and the simulated wavefield with an L1 constraint applied in the extended Radon space to handle the underdetermined nature of this problem. We successfully demonstrate our algorithm on a modified three‐dimensional EAGE/SEG Overthrust model and a Red Sea marine dataset.  相似文献   

6.
In marine acquisition, reflections of sound energy from the water–air interface result in ghosts in the seismic data, both in the source side and the receiver side. Ghosts limit the bandwidth of the useful signal and blur the final image. The process to separate the ghost and primary signals, called the deghosting process, can fill the ghost notch, broaden the frequency band, and help achieve high‐resolution images. Low‐signal‐to‐noise ratio near the notch frequencies and 3D effects are two challenges that the deghosting process has to face. In this paper, starting from an introduction to the deghosting process, we present and compare two strategies to solve the latter. The first is an adaptive mechanism that adjusts the deghosting operator to compensate for 3D effects or errors in source/receiver depth measurement. This method does not include explicitly the crossline slowness component and is not affected by the sparse sampling in the same direction. The second method is an inversion‐type approach that does include the crossline slowness component in the algorithm and handles the 3D effects explicitly. Both synthetic and field data examples in wide azimuth acquisition settings are shown to compare the two strategies. Both methods provide satisfactory results.  相似文献   

7.
This paper addresses two artefacts inherent to marine towed‐streamer surveys: 1) ghost reflections and 2) too sparse a sampling in the crossline direction. A ghost reflection is generated when an upcoming reflection bounces off the sea surface back into the sensors and can, in principle, be removed by decomposing the measured wavefield into its up‐ and downgoing constituents. This process requires a dense sampling of the wavefield in both directions along and perpendicular to the streamers. A dense sampling in the latter direction is, however, often impossible due to economical and operational constraints. Recent multi‐component streamers have been designed to record the spatial gradients on top of the pressure, which not only benefits the wavefield decomposition but also facilitates a lower‐than‐Nyquist sampling rate of the pressure. In this paper, wavefield reconstruction and deghosting are posed as a joint inverse problem. We present two approaches to establish a system matrix that embeds both a deghosting and an interpolation operator. The first approach is derived with a ghost model, whereas the second approach is derived without a ghost model. The embodiment of a ghost model leads to an even lower sampling rate but relies on a more restrictive assumption on the sea surface.  相似文献   

8.
Most seismic processing algorithms generally consider the sea surface as a flat reflector. However, acquisition of marine seismic data often takes place in weather conditions where this approximation is inaccurate. The distortion in the seismic wavelet introduced by the rough sea may influence (for example) deghosting results, as deghosting operators are typically recursive and sensitive to the changes in the seismic signal. In this paper, we study the effect of sea surface roughness on conventional (5–160 Hz) and ultra‐high‐resolution (200–3500 Hz) single‐component towed‐streamer data. To this end, we numerically simulate reflections from a rough sea surface using the Kirchhoff approximation. Our modelling demonstrates that for conventional seismic frequency band sea roughness can distort results of standard one‐dimensional and two‐dimensional deterministic deghosting. To mitigate this effect, we introduce regularisation and optimisation based on the minimum‐energy criterion and show that this improves the processing output significantly. Analysis of ultra‐high‐resolution field data in conjunction with modelling shows that even relatively calm sea state (i.e., 15 cm wave height) introduces significant changes in the seismic signal for ultra‐high‐frequency band. These changes in amplitude and arrival time may degrade the results of deghosting. Using the field dataset, we show how the minimum‐energy optimisation of deghosting parameters improves the processing result.  相似文献   

9.
海上倾斜缆采集技术具有多样的陷波特征,通过去鬼波处理可获得宽频数据.针对海水面波浪起伏及缆深误差引起的鬼波延迟时间估计误差以及崎岖海底和目的层深度变化使得鬼波和一次反射波的振幅差异系数随偏移距的变化而难以给定一个固定值的问题,本文推导出频率慢度域中鬼波滤波算子以及自适应迭代反演求解上行波算法,该鬼波滤波算子与不同水平慢度对应的鬼波和一次反射波的振幅差异系数以及鬼波延迟时间有关.并基于计算出的理论下行波与实际下行波之间的平方误差最小理论实现自适应反演迭代最优计算该振幅差异系数和鬼波延迟时间.合成的及某海上采集的倾斜缆数据去鬼波处理结果表明,频率慢度域自适应迭代反演算法能较好地去除海上变深度缆鬼波,能达到拓宽地震记录频带目的.  相似文献   

10.
In order to deconvolve the ghost response from marine seismic data, an estimate of the ghost operator is required. Typically, this estimate is made using a model of in‐plane propagation, i.e., the ray path at the receiver falls in the vertical plane defined by the source and receiver locations. Unfortunately, this model breaks down when the source is in a crossline position relative to the receiver spread. In this situation, in‐plane signals can only exist in a small region of the signal cone. In this paper, we use Bayes' theory to model the posterior probability distribution functions for the vertical component of the ray vector given the known source–receiver azimuth and the measured inline component of the ray vector. This provides a model for the ghost delay time based on the acquisition geometry and the dip of the wave in the plane of the streamer. The model is fairly robust with regard to the prior assumptions and controlled by a single parameter that is related to the likelihood of in‐plane propagation. The expected values of the resulting distributions are consistent with the deterministic in‐plane model when in‐plane likelihood is high but valid everywhere in the signal cone. Relaxing the in‐plane likelihood to a reasonable degree radically simplifies the shape of the expected‐value surface, lending itself for use in deghosting algorithms. The model can also be extended to other plane‐wave processing problems such as interpolation.  相似文献   

11.
Low‐frequency passive seismic experiments utilizing arrays of 3‐component broadband seismometers were conducted over two sites in the emirate of Abu Dhabi in the United Arab Emirates. The experiments were conducted in the vicinity of a producing oilfield and around a dry exploration well to better understand the characteristics and origins of microtremor signals (1–6 Hz), which had been reported as occurring exclusively above several hydrocarbon reservoirs in the region. The results of the experiments revealed that a strong correlation exists between the recorded ambient noise and observed meteorological and anthropogenic noises. In the frequency range of 0.15–0.4 Hz, the dominant feature is a double‐frequency microseism peak generated by the non‐linear interactions of storm induced surface waves in the Arabian Sea. We observed that the double‐frequency microseism displays a high variability in spectral amplitude, with the strongest amplitude occurring when Cyclone Gonu was battering the eastern coast of Oman; this noise was present at both sites and so is not a hydrocarbon indicator. Moreover, this study found that very strong microtremor signals in the frequency range of 2–3 Hz were present in all of the locations surveyed, both within and outside of the reservoir boundary and surrounding the dry exploration well. This microtremor signal has no clear correlation with the microseism signals but significant variations in the characteristics of the signals were observed between daytime and nighttime recording periods that clearly correlate with human activity. High‐resolution frequency‐wavenumber (fk) spectral analyses were performed on the recorded data to determine apparent velocities and azimuths of the wavefronts for the microseism and microtremor events. The fk analyses confirmed that the double‐frequency microseism originates from wave activity in the Arabian Sea, while the microtremor events have an azimuth pointing towards the nearest motorways, indicating that they are probably being excited by traffic noise. Results drawn from particle motion studies confirm these observations. The vertical‐to‐horizontal spectral ratios of the data acquired in both experiments show peaks around 2.5–3 Hz with no dependence on the presence or absence of subsurface hydrocarbons. Therefore, this method should not be used as a direct hydrocarbon indicator in these environments. Furthermore, the analyses provide no direct evidence to indicate that earthquakes are capable of stimulating the hydrocarbon reservoir in a way that could modify the spectral amplitude of the microtremor signal.  相似文献   

12.
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.  相似文献   

13.
Currently, the deghosting of towed streamer seismic data assumes a flat sea level and a sea-surface reflection coefficient of ?1; this decreases the precision of deghosting. A new method that considers the rough sea surface is proposed to suppress ghost reflections. The proposed deghosting method obtains the rough sea surface reflection coefficient using Gaussian statistics, and calculates the optimized deghosting operator in the τ/p domain. The proposed method is closer to the actual sea conditions, offers an improved deghosting operator, removes the ghost reflections from marine towed seismic data, widens the bandwidth and restores the low-frequency information, and finally improves the signal-tonoise ratio and resolution of the seismic data.  相似文献   

14.
Recently, new on‐shore acquisition designs have been presented with multi‐component sensors deployed in the shallow sub‐surface (20 m–60 m). Virtual source redatuming has been proposed for these data to compensate for surface statics and to enhance survey repeatability. In this paper, we investigate the feasibility of replacing the correlation‐based formalism that undergirds virtual source redatuming with multi‐dimensional deconvolution, offering various advantages such as the elimination of free‐surface multiples and the potential to improve virtual source repeatability. To allow for data‐driven calibration of the sensors and to improve robustness in cases with poor sensor spacing in the shallow sub‐surface (resulting in a relatively high wavenumber content), we propose a new workflow for this configuration. We assume a dense source sampling and target signals that arrive at near‐vertical propagation angles. First, the data are preconditioned by applying synthetic‐aperture‐source filters in the common receiver domain. Virtual source redatuming is carried out for the multi‐component recordings individually, followed by an intermediate deconvolution step. After this specific pre‐processing, we show that the downgoing and upgoing constituents of the wavefields can be separated without knowledge of the medium parameters, the source wavelet, or sensor characteristics. As a final step, free‐surface multiples can be eliminated by multi‐dimensional deconvolution of the upgoing fields with the downgoing fields.  相似文献   

15.
We present a simple and feasible approach to analyse and identify two‐dimensional effects in central loop transient electromagnetic sounding data and the correspondingly derived quasi two‐dimensional conductivity models. The proposed strategy is particularly useful in minimising interpretation errors. It is based on the calculation of a semi‐synthetic transient electromagnetic tipper at each sounding and for each observational transient time point. The semi‐synthetic transient electromagnetic tipper is derived from the measured vertical component of the induced voltage and the synthetically calculated horizontal component. The approach is computationally inexpensive and involves one two‐dimensional forward calculation of an obtained quasi two‐dimensional conductivity section. Based on a synthetic example, we demonstrate that the transient electromagnetic tipper approach is applicable in identifying which transient data points and which corresponding zones in a derived quasi two‐dimensional subsurface model are affected by two‐dimensional inhomogeneities. The one‐dimensional inversion of such data leads to false models. An application of the semi‐synthetic transient electromagnetic tipper to field data from the Azraq basin in Jordan reveals that, in total, eight of 80 investigated soundings are affected by two‐dimensional structures although the field data can be fitted optimally using one‐dimensional inversion techniques. The largest semi‐synthetic tipper response occurs in a 300 m‐wide region around a strong lateral resistivity contrast. The approach is useful for analysing structural features in derived quasi two‐dimensional sections and for qualitatively investigating how these features affect the transient response. To avoid misinterpretation, these identified zones corresponding to large tipper values are excluded from the interpretation of a quasi two‐dimensional conductivity model. Based on the semi‐synthetic study, we also demonstrate that a quantitative interpretation of the horizontal voltage response (e.g. by inversion) is usually not feasible as it requires the exact sensor position to be known. Although a tipper derived purely from field data is useful as a qualitative tool for identifying two‐dimensional distortion effects, it is only feasible if the sensor setup is sufficiently accurate. Our proposed semi‐synthetic transient electromagnetic tipper approach is particularly feasible as an a posteriori approach if no horizontal components are recorded or if the sensor setup in the field is not sufficiently accurate.  相似文献   

16.
Attenuation in seismic wave propagation is a common cause for poor illumination of subsurface structures. Attempts to compensate for amplitude loss in seismic images by amplifying the wavefield may boost high‐frequency components, such as noise, and create undesirable imaging artefacts. In this paper, rather than amplifying the wavefield directly, we develop a stable compensation operator using stable division. The operator relies on a constant‐Q wave equation with decoupled fractional Laplacians and compensates for the full attenuation phenomena by performing wave extrapolation twice. This leads to two new imaging conditions to compensate for attenuation in reverse‐time migration. A time‐dependent imaging condition is derived by applying Q‐compensation in the frequency domain, whereas a time‐independent imaging condition is formed in the image space by calculating image normalisation weights. We demonstrate the feasibility and robustness of the proposed methods using three synthetic examples. We found that the proposed methods are capable of properly compensating for attenuation without amplifying high‐frequency noise in the data.  相似文献   

17.
Wavefield decomposition forms an important ingredient of various geophysical methods. An example of wavefield decomposition is the decomposition into upgoing and downgoing wavefields and simultaneous decomposition into different wave/field types. The multi‐component field decomposition scheme makes use of the recordings of different field quantities (such as particle velocity and pressure). In practice, different recordings can be obscured by different sensor characteristics, requiring calibration with an unknown calibration factor. Not all field quantities required for multi‐component field decomposition might be available, or they can suffer from different noise levels. The multi‐depth‐level decomposition approach makes use of field quantities recorded at multiple depth levels, e.g., two horizontal boreholes closely separated from each other, a combination of a single receiver array combined with free‐surface boundary conditions, or acquisition geometries with a high‐density of vertical boreholes. We theoretically describe the multi‐depth‐level decomposition approach in a unified form, showing that it can be applied to different kinds of fields in dissipative, inhomogeneous, anisotropic media, e.g., acoustic, electromagnetic, elastodynamic, poroelastic, and seismoelectric fields. We express the one‐way fields at one depth level in terms of the observed fields at multiple depth levels, using extrapolation operators that are dependent on the medium parameters between the two depth levels. Lateral invariance at the depth level of decomposition allows us to carry out the multi‐depth‐level decomposition in the horizontal wavenumber–frequency domain. We illustrate the multi‐depth‐level decomposition scheme using two synthetic elastodynamic examples. The first example uses particle velocity recordings at two depth levels, whereas the second example combines recordings at one depth level with the Dirichlet free‐surface boundary condition of zero traction. Comparison with multi‐component decomposed fields shows a perfect match in both amplitude and phase for both cases. The multi‐depth‐level decomposition scheme is fully customizable to the desired acquisition geometry. The decomposition problem is in principle an inverse problem. Notches may occur at certain frequencies, causing the multi‐depth‐level composition matrix to become uninvertible, requiring additional notch filters. We can add multi‐depth‐level free‐surface boundary conditions as extra equations to the multi‐component composition matrix, thereby overdetermining this inverse problem. The combined multi‐component–multi‐depth‐level decomposition on a land data set clearly shows improvements in the decomposition results, compared with the performance of the multi‐component decomposition scheme.  相似文献   

18.
Anisotropy is often observed due to the thin layering or aligned micro‐structures, like small fractures. At the scale of cross‐well tomography, the anisotropic effects cannot be neglected. In this paper, we propose a method of full‐wave inversion for transversely isotropic media and we test its robustness against structured noisy data. Optimization inversion techniques based on a least‐square formalism are used. In this framework, analytical expressions of the misfit function gradient, based on the adjoint technique in the time domain, allow one to solve the inverse problem with a high number of parameters and for a completely heterogeneous medium. The wave propagation equation for transversely isotropic media with vertical symmetry axis is solved using the finite difference method on the cylindrical system of coordinates. This system allows one to model the 3D propagation in a 2D medium with a revolution symmetry. In case of approximately horizontal layering, this approximation is sufficient. The full‐wave inversion method is applied to a crosswell synthetic 2‐component (radial and vertical) dataset generated using a 2D model with three different anisotropic regions. Complex noise has been added to these synthetic observed data. This noise is Gaussian and has the same amplitude f?k spectrum as the data. Part of the noise is localized as a coda of arrivals, the other part is not localized. Five parameter fields are estimated, (vertical) P‐wave velocity, (vertical) S‐wave velocity, volumetric mass and the Thomsen anisotropic parameters epsilon and delta. Horizontal exponential correlations have been used. The results show that the full‐wave inversion of cross‐well data is relatively robust for high‐level noise even for second‐order parameters such as Thomsen epsilon and delta anisotropic parameters.  相似文献   

19.
A processing method is presented to attenuate the surface ghost using marine twin streamer data. It is an extension to the dephase and sum method which corrects for the phase of the ghost in both streamer outputs and then adds them in an attempt to fill the notches in the amplitude spectrum. The method presented corrects both the phase and the amplitude effect of the surface ghost by combining both signals as a weighted sum. This method is applicable to all types of twin streamer data, ranging from deep exploration data to very shallow high-resolution surveys. Both the synthetic and real data examples shown are of the high-resolution type, using frequencies above 2 kHz and short streamers (active sections of the order of one metre). Both the dephase and sum method and the weighted sum method are applied to synthetic high-resolution data and the results are compared. This has been done for noise-free data, data with a high noise level and data with strong geometrical spreading on the ghost reflections. From these test results it can be concluded that in general the weighted sum method gives better results. The improvement in the signal-to-noise ratio appears to be the same, due to the additive character of both methods. In the case of high-resolution twin streamer data recorded in shallow water, the delay time of the ghost reflection can be of the same order of magnitude as the traveltime of the primary. For this situation, geometrical spreading can have a considerable effect on the amplitude of the ghost reflection. If no correction can be made for the spreading function, it might be better to use the dephase and sum method. Both methods are also applied to a real data set recorded in a high-resolution survey. Because the ghost delay is of the same order of magnitude as the arrival time of the primary, the ghost reflection is strongly affected by geometrical spreading. Since the spreading function of the source is unknown, it cannot be corrected for. This causes the result of the weighted sum method to be less reliable compared to the case where no spreading is involved.  相似文献   

20.
Marine seismic data are always affected by noise. An effective method to handle a broad range of noise problems is a time‐frequency de‐noising algorithm. In this paper we explain details regarding the implementation of such a method. Special emphasis is given to the choice of threshold values, where several different strategies are investigated. In addition we present a number of processing results where time‐frequency de‐noising has been successfully applied to attenuate noise resulting from swell, cavitation, strumming and seismic interference. Our seismic interference noise removal approach applies time‐frequency de‐noising on slowness gathers (τ?p domain). This processing trick represents a novel approach, which efficiently handles certain types of seismic interference noise that otherwise are difficult to attenuate. We show that time‐frequency de‐noising is an effective, amplitude preserving and robust tool that gives superior results compared to many other conventional de‐noising algorithms (for example frequency filtering, τ?p or fx‐prediction). As a background, some of the physical mechanisms responsible for the different types of noise are also explained. Such physical understanding is important because it can provide guidelines for future survey planning and for the actual processing.  相似文献   

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