scholarly journals Frequency-Domain Common Image Gathers for Quickly Checking the Accuracy of Migration Velocity

2021 ◽  
Vol 9 ◽  
Author(s):  
Haemin Kim ◽  
Yongchae Cho ◽  
Yunseok Choi ◽  
Seungwon Ko ◽  
Changsoo Shin
Keyword(s):  
Frequency Domain ◽  
Deviant Behavior ◽  
Computational Cost ◽  
Real Data ◽  
Velocity Model ◽  
Complex Velocity ◽  
Hybrid Domain ◽  
The Common ◽  
Low Computational Cost ◽  
Complex Velocity Model

The common image gather (CIG) method enables qualitative and quantitative evaluation of the velocity model through the image. The most common such methods are offset-domain common image gather (ODCIG) and angle-domain common image gather (ADCIG). The challenge is that it requires a great deal of additional computation besides migration. We, therefore, introduce a new CIG method that has low computational cost: frequency-domain common image gather (FDCIG). FDCIG simply rearranges data using a gradient (partial image) calculated in the process of obtaining a migration image to represent it in the frequency-depth domain. We apply the FDCIG method to the layered model to show how FDCIGs behave when the velocity model is inaccurate. We also introduced the 3-D SEG/EAGE salt model to show how to apply the FDCIG method in the hybrid domain. Last, we applied 2-D real data. These sample field data also indicate that even in a complex velocity model, deviant behavior by FDCIG appears intuitively if the background velocity is inaccurate.

Joint inversion of seismic traveltime and frequency-domain airborne electromagnetic data for hydrocarbon exploration

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. U9-U22 ◽  
Author(s):  
Jide Nosakare Ogunbo ◽  
Guy Marquis ◽  
Jie Zhang ◽  
Weizhong Wang
Keyword(s):  
Frequency Domain ◽  
Joint Inversion ◽  
Sedimentary Environment ◽  
Computational Cost ◽  
Velocity Model ◽  
Two Dimensions ◽  
Hydrocarbon Exploration ◽  
Three Dimensions ◽  
Data Sets ◽  
The One

Geophysical joint inversion requires the setting of a few parameters for optimum performance of the process. However, there are yet no known detailed procedures for selecting the various parameters for performing the joint inversion. Previous works on the joint inversion of electromagnetic (EM) and seismic data have reported parameter applications for data sets acquired from the same dimensional geometry (either in two dimensions or three dimensions) and few on variant geometry. But none has discussed the parameter selections for the joint inversion of methods from variant geometry (for example, a 2D seismic travel and pseudo-2D frequency-domain EM data). With the advantage of affordable computational cost and the sufficient approximation of a 1D EM model in a horizontally layered sedimentary environment, we are able to set optimum joint inversion parameters to perform structurally constrained joint 2D seismic traveltime and pseudo-2D EM data for hydrocarbon exploration. From the synthetic experiments, even in the presence of noise, we are able to prescribe the rules for optimum parameter setting for the joint inversion, including the choice of initial model and the cross-gradient weighting. We apply these rules on field data to reconstruct a more reliable subsurface velocity model than the one obtained by the traveltime inversions alone. We expect that this approach will be useful for performing joint inversion of the seismic traveltime and frequency-domain EM data for the production of hydrocarbon.

Fast and accurate dynamic raytracing in heterogeneous media

1990 ◽  
Vol 80 (5) ◽  
pp. 1284-1296
Author(s):  
Claude F. Lafond ◽  
Alan R. Levander
Keyword(s):  
Shooting Method ◽  
Heterogeneous Media ◽  
Velocity Model ◽  
Travel Times ◽  
Complex Velocity ◽  
Geometrical Spreading ◽  
Imaging Condition ◽  
Depth Migration ◽  
Velocity Models ◽  
Complex Velocity Model

Abstract We have developed a fast and accurate dynamic raytracing method for 2.5-D heterogeneous media based on the kinematic algorithm proposed by Langan et al. (1985). This algorithm divides the model into cells of constant slowness gradient, and the positions, directions, and travel times of the rays are expressed as polynomials of the travel path length, accurate to the second other in the gradient. This method is efficient because of the use of simple polynomials at each raytracing step. We derived similar polynomial expressions for the dynamic raytracing quantities by integrating the raytracing system and expanding the solutions to the second order in the gradient. This new algorithm efficiently computes the geometrical spreading, amplitude, and wavefront curvature on individual rays. The two-point raytracing problem is solved by the shooting method using the geometrical spreading. Paraxial corrections based on the wavefront curvature improve the accuracy of the travel time and amplitude at a given receiver. The computational results for two simple velocity models are compared with those obtained with the SEIS83 seismic modeling package (Cerveny and Psencik, 1984); this new method is accurate for both travel times and amplitudes while being significantly faster. We present a complex velocity model that shows that the algorithm allows for realistic models and easily computes rays in structures that pose difficulties for conventional methods. The method can be extended to raytracing in 3-D heterogeneous media and can be used as a support for a Gaussian beam algorithm. It is also suitable for computing the Green's function and imaging condition needed for prestack depth migration.

Improving the least-squares image by using angle information to avoid cycle skipping

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. S581-S598 ◽  
Author(s):  
Bin He ◽  
Yike Liu ◽  
Yanbao Zhang
Keyword(s):  
Least Squares ◽  
Real Data ◽  
Velocity Model ◽  
Migration Velocity ◽  
Common Source ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Propagation Angle ◽  
Time Migration ◽  
The Common

In the past few decades, the least-squares reverse time migration (LSRTM) algorithm has been widely used to enhance images of complex subsurface structures by minimizing the data misfit function between the predicted and observed seismic data. However, this algorithm is sensitive to the accuracy of the migration velocity model, which, in the case of real data applications (generally obtained via tomography), always deviates from the true velocity model. Therefore, conventional LSRTM faces a cycle-skipping problem caused by a smeared image when using an inaccurate migration velocity model. To address the cycle-skipping problem, we have introduced an angle-domain LSRTM algorithm. Unlike the conventional LSRTM algorithm, our method updates the common source-propagation angle image gathers rather than the stacked image. An extended Born modeling operator in the common source-propagation angle domain is was derived, which reproduced kinematically accurate data in the presence of velocity errors. Our method can provide more focused images with high resolution as well as angle-domain common-image gathers (ADCIGs) with enhanced resolution and balanced amplitudes. However, because the velocity model is not updated, the provided image can have errors in depth. Synthetic and field examples are used to verify that our method can robustly improve the quality of the ADCIGs and the finally stacked images with affordable computational costs in the presence of velocity errors.

Study on oscillating flow of moderate kinetic Reynolds numbers using complex velocity model and phase Doppler anemometer

2014 ◽  
Vol 130 ◽  
pp. 830-837 ◽  
Author(s):  
Gang Xiao ◽  
Tianxue Zhou ◽  
Mingjiang Ni ◽  
Conghui Chen ◽  
Zhongyang Luo ◽  
...  
Keyword(s):  
Velocity Model ◽  
Reynolds Numbers ◽  
Oscillating Flow ◽  
Complex Velocity ◽  
Phase Doppler Anemometer ◽  
Complex Velocity Model

Prestack depth imaging of ocean-bottom node data

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCA57-WCA63 ◽  
Author(s):  
Mathias Alerini ◽  
Bärbel Traub ◽  
Céline Ravaut ◽  
Eric Duveneck
Keyword(s):  
Real Data ◽  
Velocity Model ◽  
Quality Data ◽  
Ocean Bottom ◽  
Model Estimation ◽  
Data Set ◽  
Depth Imaging ◽  
The North ◽  
Multiple Attenuation ◽  
The Common

Ocean-bottom node acquisitions provide high-quality data but usually have large distances between the nodes because of cost. This makes the use of conventional processing difficult and has led to relatively little interest in such data for industrial purposes. We have considered a three-step workflow specifically designed for prestack depth imaging of P-waves recorded by ocean-bottom nodes. It consists of multiple attenuation, velocity model estimation, and prestack depth migration. Whereas multiple attenuation and tomography use data in the common-receiver domain, migration is performed in the common-angle domain. One of the main features is the handling of the sparse receiver geometry during velocity model estimation: the reciprocity of the PP-Green’s functions is used to obtain the required tomographic input using only the common-receiver gathers. The tomographic method also provides an estimate of the geologic dip, which is used to limit the migration operator. This provides migrated images free of migration smiles. The workflow contains no additional assumptions compared to those used to process ocean-bottom cable data. We validate the workflow on a 2D line extracted from a 3D real data set acquired in the North Sea. The results show that it is possible to use ocean-bottom data efficiently for prestack depth imaging.

Migration velocity analysis using residual diffraction moveout in the poststack depth domain

Geophysics ◽  
2013 ◽  
Vol 78 (3) ◽  
pp. S125-S135 ◽  
Author(s):  
Tiago A. Coimbra ◽  
J. Jadsom S. de Figueiredo ◽  
Jörg Schleicher ◽  
Amélia Novais ◽  
Jessé C. Costa
Keyword(s):  
Computational Cost ◽  
Synthetic Data ◽  
Velocity Model ◽  
Migration Velocity ◽  
Local Velocity ◽  
Migration Velocity Analysis ◽  
Incorrect Model ◽  
Gradient Models ◽  
Low Computational Cost ◽  
Constant Gradient

Diffraction events contain more direct information on the medium velocity than reflection events. We have developed a method for migration velocity improvement and diffraction localization based on a moveout analysis of over- or undermigrated diffraction events in the depth domain. The method uses an initial velocity model as input. It provides an update to the velocity model and diffraction locations in the depth domain as a result. The algorithm is based on the focusing of remigration trajectories from incorrectly migrated diffraction curves. These trajectories are constructed by applying a ray-tracing-like approach to the image-wave equation for velocity continuation. The starting points of the trajectories are obtained from fitting an ellipse or hyperbola to the picked uncollapsed diffraction events in the depth-migrated domain. Focusing of the remigration trajectories points out the approximate location of the associated diffractor, as well as local velocity attributes. Apart from the migration needed at each iteration, the method has a very low computational cost, but relies on the identification and picking of uncollapsed diffractions. We tested the feasibility of the method using synthetic data examples from three simple constant-gradient models and the Sigsbee2B data. Although we were able to build a complete velocity model in this example, we think of our technique as one for local velocity updating of a slightly incorrect model. Our tests showed that, within regions where the assumptions are satisfied, the method can be a powerful tool.

Frequency-domain wave-equation traveltime inversion with a monofrequency component

Geophysics ◽  
2021 ◽  
Vol 86 (6) ◽  
pp. R913-R926
Author(s):  
Jianhua Wang ◽  
Jizhong Yang ◽  
Liangguo Dong ◽  
Yuzhu Liu
Keyword(s):  
Wave Equation ◽  
Frequency Domain ◽  
Time Domain ◽  
Computational Cost ◽  
Velocity Model ◽  
Receiver Side ◽  
Data Set ◽  
Traveltime Inversion ◽  
Velocity Models ◽  
The Time Domain

Wave-equation traveltime inversion (WTI) is a useful tool for background velocity model building. It is generally formulated and implemented in the time domain, in which the gradient is calculated by temporally crosscorrelating the source- and receiver-side wavefields. The time-domain source-side snapshots are either stored in memory or are reconstructed through back propagation. The memory requirements and computational cost of WTI are thus prohibitively expensive, especially for 3D applications. To partially alleviate this problem, we provide an implementation of WTI in the frequency domain with a monofrequency component. Because only one frequency is used, it is affordable to directly store the source- and receiver-side wavefields in memory. There is no need for wavefield reconstruction during gradient calculation. In such a way, we have dramatically reduced the memory requirements and computational cost compared with the traditional time-domain WTI realization. For practical implementation, the frequency-domain wavefield is calculated by time-domain finite-difference forward modeling and is transformed to the frequency domain by an on-the-fly discrete Fourier transform. Numerical examples on a simple lateral periodic velocity model and the Marmousi model demonstrate that our method can obtain accurate background velocity models comparable with those from time-domain WTI and frequency-domain WTI with multiple frequencies. A field data set test indicates that our method obtains a background velocity model that well predicts the seismic wave traveltime.

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