Improved seismic image by Q-compensated reverse time migration: Application to crosswell field data, west Texas

Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. B61-B67 ◽  
Author(s):  
Tieyuan Zhu ◽  
Jerry M. Harris
Keyword(s):  
Image Resolution ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
High Frequencies ◽  
Time Migration ◽  
West Texas ◽  
Final Formula ◽  
Seismic Image ◽  
Internal Structures ◽  
Sonic Logs

To test the effectiveness of the [Formula: see text]-compensated reverse time migration ([Formula: see text]-RTM) method, we applied it to crosswell seismic data from western Texas. This crosswell field survey was aimed at determining the boundaries and even the internal features of the reservoir. In this area, the reservoir geologic body exhibits strong attenuation that reduces high frequencies more rapidly. Thus, conventional acoustic RTM produces a dimmed image (reduced amplitude and low resolution) of the reservoir area and structures underneath. In contrast, [Formula: see text]-RTM is able to compensate for the attenuation effects during imaging. The [Formula: see text] and [Formula: see text] profiles needed for [Formula: see text]-RTM were produced by joint traveltime and frequency shift tomography. Preprocessing of the data was carried out to reduce noise, remove tube waves, and to separate up- and downgoing wavefields. Along with recovered high wavenumbers, the final [Formula: see text]-RTM image provided many details about geologic layers and structures. The lateral and vertical extent and internal structures within the reservoir unit were clearly determined. These geologic features were also correlated to the velocity profile and sonic logs. We concluded that [Formula: see text]-RTM imaging practically improved the image resolution in attenuating geologic media.

Some Aspects of Seismic Data Reverse Time Migration for Salt Tectonics Geology of the Dnieper-Donets Basin

2021 ◽  
Author(s):  
Pavlo Kuzmenko ◽  
Viktor Buhrii ◽  
Carlo D'Aguanno ◽  
Viktor Maliar ◽  
Hrigorii Kashuba ◽  
...  
Keyword(s):  
Seismic Data ◽  
Full Range ◽  
Donets Basin ◽  
Salt Tectonics ◽  
Imaging Method ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Seismic Image ◽  
Complex Geology

Abstract Processing of the seismic data acquired in areas of complex geology of the Dnieper-Donets basin, characterized by the salt tectonics, requires special attention to the salt dome interpretation. For this purpose, Kirchhoff Depth Imaging and Reverse Time Migration (RTM) were applied and compared. This is the first such experience in the Dnieper-Donets basin. According to international experience, RTM is the most accurate seismic imaging method for steep and vertical geological (acoustic contrast) boundaries. Application of the RTM on 3D WAZ land data is a great challenge in Dnieper-Donets Basin because of the poor quality of the data with a low signal-to-noise ratio and irregular spatial sampling due to seismic acquisition gaps and missing traces. The RTM algorithm requires data, organized to native positions of seismic shots. For KPSDM we used regularized data after 5D interpolation. This affects the result for near salt reflection. The analysis of KPSDM and RTM results for the two areas revealed the same features. RTM seismic data looked more smoothed, but for steeply dipping reflections, lateral continuity of reflections was much improved. The upper part (1000 m) of the RTM has shadow zones caused by low fold. Other differences between Kirchhoff data and RTM are in the spectral content, as the former is characterized by the full range of seismic frequency spectrum. Conversely, beneath the salt, the RTM has reflections with steep dips which are not observed on the KPSDM. It is possible to identify new prospects using the RTM seismic image. Reverse Time Migration of 3D seismic data has shown geologically consistent results and has the potential to identify undiscovered hydrocarbon traps and to improve salt flank delineation in the complex geology of the Dnieper-Donets Basin's salt domes.

Elastic least-squares reverse time migration in vertical transverse isotropic media

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. S539-S553 ◽  
Author(s):  
Jidong Yang ◽  
Hejun Zhu ◽  
George McMechan ◽  
Houzhu Zhang ◽  
Yang Zhao
Keyword(s):  
Wave Equation ◽  
Least Squares ◽  
Transversely Isotropic ◽  
Image Resolution ◽  
Total Variation Regularization ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Isotropic Media ◽  
Band Limited

Using adjoint-based elastic reverse time migration, it is difficult to produce high-quality reflectivity images due to the limited acquisition apertures, band-limited source time function, and irregular subsurface illumination. Through iteratively computing the Hessian inverse, least-squares migration enables us to reduce the point-spread-function effects and improve the image resolution and amplitude fidelity. By incorporating anisotropy in the 2D elastic wave equation, we have developed an elastic least-squares reverse time migration (LSRTM) method for multicomponent data from the vertically transversely isotropic (VTI) media. Using the perturbed stiffness parameters [Formula: see text] and [Formula: see text] as PP and PS reflectivities, we linearize the elastic VTI wave equation and obtain a Born modeling (demigration) operator. Then, we use the Lagrange multiplier method to derive the corresponding adjoint wave equation and reflectivity kernels. With linearized forward modeling and adjoint migration operators, we solve a linear inverse problem to estimate the subsurface reflectivity models for [Formula: see text] and [Formula: see text]. To reduce the artifacts caused by data over-fitting, we introduce total-variation regularization into the reflectivity inversion, which promotes a sparse solution in terms of the model derivatives. To accelerate the convergence of LSRTM, we use source illumination to approximate the diagonal Hessian and use it as a preconditioner for the misfit gradient. Numerical examples help us determine that our elastic VTI LSRTM method can improve the spatial resolution and amplitude fidelity in comparison to adjoint migration.

Reverse time migration via frequency-adaptive multiscale spatial grids

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. S41-S55 ◽  
Author(s):  
Yongchae Cho ◽  
Richard L. Gibson, Jr.
Keyword(s):  
Coarse Grid ◽  
Image Resolution ◽  
Imaging Method ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Fine Grid ◽  
Wave Modeling ◽  
Time Migration ◽  
Wave Solutions ◽  
Spatial Grid

Reverse time migration (RTM) is widely used because of its ability to recover complex geologic structures. However, RTM also has a drawback in that it requires significant computational cost. In RTM, wave modeling accounts for the largest part of the computing cost for calculating forward- and backward-propagated wavefields before applying an imaging condition. For this reason, we have applied a frequency-adaptive multiscale spatial grid to enhance the efficiency of the wave simulations. To implement wave modeling for different values of the spatial grid interval, we apply a model reduction technique, the generalized multiscale finite-element method (GMsFEM), which solves local spectral problems on a fine grid to simulate wave propagation on a coarser grid. We can enhance the speed of computation without sacrificing accuracy by using coarser grids for lower frequency waves, while applying a finer grid for higher frequency waves. In the proposed method, we can control the size of the coarse grid and level of heterogeneity of the wave solutions to tune the trade-off between speedup and accuracy. As we increase the expected level of complexity of the wave solutions, the GMsFEM wave modeling can capture more detailed features of waves. After computing the forward and backward wavefield on the coarse grid, we reproject the coarse wave solutions to the fine grid to construct the RTM gradient image. Although wave solutions are computed on a coarse grid, we still obtain the RTM images without reducing the image resolution by projecting coarse wave solutions to the fine grid. We determine the efficiency of the proposed imaging method using the Marmousi-2 model. We compare the RTM images using GMsFEM with a fixed coarse mesh and a multiple frequency-adaptive coarse meshes to indicate the image quality and computational speed of the new approach.

Q-compensated reverse-time migration

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. S77-S87 ◽  
Author(s):  
Tieyuan Zhu ◽  
Jerry M. Harris ◽  
Biondo Biondi
Keyword(s):  
Image Resolution ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Pass Filter ◽  
Low Pass Filter ◽  
High Attenuation ◽  
Phase Dispersion ◽  
Time Migration ◽  
Amplitude Attenuation ◽  
Attenuation And Dispersion

Reduced amplitude and distorted dispersion of seismic waves caused by attenuation, especially strong attenuation, always degrades the resolution of migrated images. To improve image resolution, we evaluated a methodology of compensating for attenuation ([Formula: see text]) effects in reverse-time migration ([Formula: see text]-RTM). The [Formula: see text]-RTM approach worked by mitigating the amplitude attenuation and phase dispersion effects in source and receiver wavefields. Source and receiver wavefields were extrapolated using a previously published time-domain viscoacoustic wave equation that offered separated amplitude attenuation and phase dispersion operators. In our [Formula: see text]-RTM implementation, therefore, attenuation- and dispersion-compensated operators were constructed by reversing the sign of attenuation operator and leaving the sign of dispersion operator unchanged, respectively. Further, we designed a low-pass filter for attenuation and dispersion operators to stabilize the compensating procedure. Finally, we tested the [Formula: see text]-RTM approach on a simple layer model and the more realistic BP gas chimney model. Numerical results demonstrated that the [Formula: see text]-RTM approach produced higher resolution images with improved amplitude and phase compared to the noncompensated RTM, particularly beneath high-attenuation zones.

An approach for attenuation-compensating multidimensional constant-Q viscoacoustic reverse time migration

Geophysics ◽  
2020 ◽  
Vol 85 (1) ◽  
pp. S33-S46
Author(s):  
Ali Fathalian ◽  
Daniel O. Trad ◽  
Kristopher A. Innanen
Keyword(s):  
Wave Propagation ◽  
Wave Equation ◽  
Velocity Model ◽  
Seismic Wave Propagation ◽  
Image Resolution ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Phase Dispersion ◽  
Time Migration ◽  
Amplitude Attenuation

Simulation of wave propagation in a constant-[Formula: see text] viscoacoustic medium is an important problem, for instance, within [Formula: see text]-compensated reverse time migration (RTM). Processes of attenuation and dispersion influence all aspects of seismic wave propagation, degrading the resolution of migrated images. To improve the image resolution, we have developed a new approach for the numerical solution of the viscoacoustic wave equation in the time domain and we developed an associated viscoacoustic RTM ([Formula: see text]-RTM) method. The main feature of the [Formula: see text]-RTM approach is compensation of attenuation effects in seismic images during migration by separation of amplitude attenuation and phase dispersion terms. Because of this separation, we are able to compensate the amplitude loss effect in isolation, the phase dispersion effect in isolation, or both effects concurrently. In the [Formula: see text]-RTM implementation, an attenuation-compensated operator is constructed by reversing the sign of the amplitude attenuation and a regularized viscoacoustic wave equation is invoked to eliminate high-frequency instabilities. The scheme is tested on a layered model and a modified acoustic Marmousi velocity model. We validate and examine the response of this approach by using it within an RTM scheme adjusted to compensate for attenuation. The amplitude loss in the wavefield at the source and receivers due to attenuation can be recovered by applying compensation operators on the measured receiver wavefield. Our 2D and 3D numerical tests focus on the amplitude recovery and resolution of the [Formula: see text]-RTM images as well as the interface locations. Improvements in all three of these features beneath highly attenuative layers are evident.

scholarly journals Least-squares reverse-time migration with sparsity constraints

2021 ◽  
Vol 18 (2) ◽  
pp. 304-316
Author(s):  
Di Wu ◽  
Yanghua Wang ◽  
Jingjie Cao ◽  
Nuno V da Silva ◽  
Gang Yao
Keyword(s):  
Side Effects ◽  
Least Squares ◽  
Synthetic Data ◽  
Image Resolution ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
L1 Norm ◽  
Constrained Least Squares ◽  
Time Migration ◽  
Sparsity Constraints

Abstract Least-squares reverse-time migration (RTM) works with an inverse operation, rather than an adjoint operation in a conventional RTM, and thus produces an image with a higher resolution and more balanced amplitude than the conventional RTM image. However, least-squares RTM introduces two side effects: sidelobes around reflectors and high-wavenumber migration artifacts. These side effects are caused mainly by the limited bandwidth of seismic data, the limited coverage of receiver arrays and the inaccuracy of the modeling kernel. To mitigate these side effects and to further boost resolution, we employed two sparsity constraints in the least-squares inversion operation, namely the Cauchy and L1-norm constraints. For solving the Cauchy-constrained least-squares RTM, we used a preconditioned nonlinear conjugate-gradient method. For solving the L1-norm constrained least-squares RTM, we modified the iterative soft thresholding method. While adopting these two solution methods, the Cauchy-constrained least-squares RTM converged faster than the L1-norm constrained least-squares RTM. Application examples with synthetic data and laboratory modeling data demonstrated that the constrained least-squares RTM methods can mitigate the side effects and promote image resolution.

Preserving the discontinuities in least-squares reverse time migration of simultaneous-source data

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. S185-S196 ◽  
Author(s):  
Yangkang Chen ◽  
Hanming Chen ◽  
Kui Xiang ◽  
Xiaohong Chen
Keyword(s):  
Least Squares ◽  
Singular Spectrum Analysis ◽  
Low Rank ◽  
Superior Performance ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Seismic Image ◽  
Recorded Data ◽  
Simultaneous Source

The simultaneous-source shooting technique can accelerate field acquisition and improve spatial sampling but it will cause strong interferences in the recorded data and artifacts in the final image. The previously proposed structural smoothing operator can effectively attenuate artifacts for relatively simple reflection structures during least-squares inversion, but it will cause damage to complicated reflection events such as discontinuities. To preserve discontinuities in a seismic image, we apply the singular spectrum analysis (SSA) operator to attenuate artifacts during least-squares inversion. Considering that global SSA cannot deal with overcomplicated data very well, we use local SSA to remove noise and to better preserve the steeply dipping components. The local SSA operator corresponds to a local low-rank constraint applied in the inversion process. The migration operator used in the study is the reverse time migration (RTM) operator. Tests using the Marmousi model showed the superior performance of the proposed algorithm in preserving the discontinuities of seismic images.

scholarly journals One-step data-domain least-squares reverse time migration

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. R361-R368 ◽  
Author(s):  
Qiancheng Liu ◽  
Daniel Peter
Keyword(s):  
Least Squares ◽  
Wiener Filter ◽  
Real Data ◽  
Image Resolution ◽  
Inversion Algorithm ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Iterative Inversion ◽  
One Step

Least-squares reverse time migration (LSRTM) is an iterative inversion algorithm for estimating the broadband-wavenumber reflectivity model. Although it produces superior results compared with conventional reverse time migration (RTM), LSRTM is computationally expensive. We have developed a one-step LSRTM method by considering the demigrated and observed data to design a deblurring preconditioner in the data domain using the Wiener filter. For the Wiener filtering, we further use a stabilized division algorithm via the Taylor expansion. The preconditioned observed data are then remigrated to obtain a deblurred image. The total cost of this method is about two RTMs. Through synthetic and real data experiments, we see that one-step LSRTM is able to enhance image resolution and balance source illumination at low computational costs.

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