2.5-D wave equations and high‐frequency asymptotics

Geophysics ◽  
1995 ◽  
Vol 60 (2) ◽  
pp. 556-562 ◽  
Author(s):  
John W. Stockwell

The need for modeling 3-D seismic data in a 2-D setting has motivated investigators to create so‐called 2.5-D modeling methods. One such method proposed by Liner involves the use of an approximate 2.5-D wave operator for constant‐density media. The traveltimes and amplitudes predicted by high‐frequency asymptotic ray series (WKBJ) analysis of the Liner 2.5-D wave equation match those predicted by Bleistein’s 2.5-D ray‐theoretic development in constant wavespeed media. However, high‐frequency analysis indicates that the Liner 2.5-D variable wavespeed equation will have a maximum amplitude error of ±35% in a linear c(z) model where the wavespeed doubles or halves from the beginning to the end of a raypath. These amplitudes are comparable to those produced by converting 2-D data to 2.5-D using correction factors of the type proposed by Emersoy and Oristaglio and Deregowski and Brown, with the exception being that the Liner equation lacks the half derivative waveform correction present in these operators. An alternate method of constructing 2.5-D wave operators based on the WKBJ analysis is proposed. This method permits variable density (acoustic) 2.5-D wave operators to be derived.

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. T157-T168 ◽  
Author(s):  
Gang Fang ◽  
Sergey Fomel ◽  
Qizhen Du ◽  
Jingwei Hu

We evaluated a new spectral method and a new finite-difference (FD) method for seismic-wave extrapolation in time. Using staggered temporal and spatial grids, we derived a wave-extrapolation operator using a lowrank decomposition for a first-order system of wave equations and designed the corresponding FD scheme. The proposed methods extend previously proposed lowrank and lowrank FD wave extrapolation methods from the cases of constant density to those of variable density. Dispersion analysis demonstrated that the proposed methods have high accuracy for a wide wavenumber range and significantly reduce the numerical dispersion. The method of manufactured solutions coupled with mesh refinement was used to verify each method and to compare numerical errors. Tests on 2D synthetic examples demonstrated that the proposed method is highly accurate and stable. The proposed methods can be used for seismic modeling or reverse-time migration.


2021 ◽  
Author(s):  
Dustin Blymyer ◽  
Klaas Koster ◽  
Graeme Warren

Abstract Summary Compressive sensing (CS) of seismic data is a new style of seismic acquisition whereby the data are recorded on a pseudorandom grid rather than along densely sampled lines in a conventional design. A CS design with a similar station density will generally yield better quality data at a similar cost compared to a conventional design, whereas a CS design with a lower station density will reduce costs while retaining quality. Previous authors (Mosher, 2014) have shown good results from CS surveys using proprietary methods for the design and processing. In this paper we show results obtained using commercially available services based on published algorithms (Lopez, 2016). This is a necessary requirement for adoption of CS by our industry. This report documents the results of a 108km2 CS acquisition and processing trial. The acquisition and processing were specifically designed to establish whether CS can be used for suppression of backscattered, low velocity, high frequency surface waves. We demonstrate that CS data can be reconstructed by a commercial contractor and that the suppression of backscattered surface waves is improved by using CS receiver gathers reconstructed to a dense shot grid. We also show that CS acquisition is a reliable alternative to conventional acquisition from which high-quality subsurface images can be formed.


Geophysics ◽  
2019 ◽  
Vol 85 (1) ◽  
pp. V71-V80 ◽  
Author(s):  
Xiong Ma ◽  
Guofa Li ◽  
Hao Li ◽  
Wuyang Yang

Seismic absorption compensation is an important processing approach to mitigate the attenuation effects caused by the intrinsic inelasticity of subsurface media and to enhance seismic resolution. However, conventional absorption compensation approaches ignore the spatial connection along seismic traces, which makes the compensation result vulnerable to high-frequency noise amplification, thus reducing the signal-to-noise ratio (S/N) of the result. To alleviate this issue, we have developed a structurally constrained multichannel absorption compensation (SC-MAC) algorithm. In the cost function of this algorithm, we exploit an [Formula: see text] norm to constrain the reflectivity series and an [Formula: see text] norm to regularize the reflection structural characteristic of the compensation data. The reflection structural characteristic operator, extracted from the observed stacked seismic data, is the core of the structural regularization term. We then solve the cost function of SC-MAC by the alternating direction method of multipliers. Benefiting from the introduction of reflection structure constraint, SC-MAC improves the stability of the compensation result and inhibits the amplification of high-frequency noise. Synthetic and field data examples demonstrate that our proposed method is more robust to random noise and can not only improve the resolution of seismic data, but also maintain the S/N of the compensation seismic data.


Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. V201-V221 ◽  
Author(s):  
Mehdi Aharchaou ◽  
Erik Neumann

Broadband preprocessing has become widely used for marine towed-streamer seismic data. In the standard workflow, far-field source designature, receiver and source-side deghosting, and redatuming to mean sea level are applied in sequence, with amplitude compensation for background [Formula: see text] delayed until the imaging or postmigration stages. Thus, each step is likely to generate its own artifacts, quality checking can be time-consuming, and broadband data are only obtained late in this chained workflow. We have developed a unified method for broadband preprocessing — called integrated broadband preprocessing (IBP) — which enables the joint application of all the above listed steps early in the processing sequence. The amplitude, phase, and amplitude-variation-with-offset fidelity of IBP are demonstrated on pressure data from the shallow, deep, and slanted streamers. The integration allows greater sparsity to emerge in the representation of seismic data, conferring clear benefits over the sequential application. Moreover, time sparsity, full dimensionality, and early amplitude [Formula: see text] compensation all have an impact on broadband data quality, in terms of reduced ringing artifacts, improved wavelet integrity at large crossline angles, and fewer residual high-frequency multiples.


Author(s):  
R. V. Craster ◽  
J. Kaplunov ◽  
A. V. Pichugin

An asymptotic procedure based upon a two-scale approach is developed for wave propagation in a doubly periodic inhomogeneous medium with a characteristic length scale of microstructure far less than that of the macrostructure. In periodic media, there are frequencies for which standing waves, periodic with the period or double period of the cell, on the microscale emerge. These frequencies do not belong to the low-frequency range of validity covered by the classical homogenization theory, which motivates our use of the term ‘high-frequency homogenization’ when perturbing about these standing waves. The resulting long-wave equations are deduced only explicitly dependent upon the macroscale, with the microscale represented by integral quantities. These equations accurately reproduce the behaviour of the Bloch mode spectrum near the edges of the Brillouin zone, hence yielding an explicit way for homogenizing periodic media in the vicinity of ‘cell resonances’. The similarity of such model equations to high-frequency long wavelength asymptotics, for homogeneous acoustic and elastic waveguides, valid in the vicinities of thickness resonances is emphasized. Several illustrative examples are considered and show the efficacy of the developed techniques.


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