Angle-domain Common-image Gathers Research Articles

A fast anisotropic decoupled operator of elastic wave propagation in the space domain for P-/S-wave-mode decomposition and angle calculation, with its application to elastic reverse time migration in a TI medium

The conventional anisotropic P-/S-wave-mode decomposition and angle calculation usually are performed in the wavenumber domain and require multiple Fourier transforms and rely on strong model assumptions. Therefore, it is difficult to use in production due to the prohibitively high computational cost. To tackle this problem, we develop a fast anisotropic P-/S-wave-mode decomposition approach in the space domain and further apply this decomposition to the vertical transversely isotropic (VTI)/tilted transversely isotropic (TTI) elastic reverse time migration (ERTM) and the associated angle-domain common-image gathers (ADCIGs). To start with, we solve the Christoffel equation of the VTI media and obtain an anisotropic-Helmholtz (AH) operator that represents the P- and S-wave polarizations in the wavenumber domain. The decoupled operators for the P-/S-wave decomposition are then derived in terms of the AH operator. To improve the efficiency and model adaptability, we convert the decoupled operators from the wavenumber domain to the space domain as a function of the model parameters and phase angle. By further eliminating the phase-angle term, such space-domain decoupled operators lead to the approximate P- and S-wave components which are proven to achieve the same effect as the accurate P and S wavefields applied in the angle calculation and ERTM images. A fast space-domain AH decomposition approach is thus obtained and can be used for P-/S-wave-mode decomposition, ADCIGs, and ERTM. In addition, we extend our approach to the TTI media by using the coordinate transform. Three examples are used to demonstrate the effectiveness and feasibility of our method.

Extracting angle-domain common-image gathers in VTI media using ansiotropic-Helmholtz P/S wave-mode decomposition

Common-image gathers are extensively used in amplitude versus angle (AVA) and migration velocity analysis (MVA). The current state of methods for anisotropic angle gathers extraction use slant-stack, local Fourier transform or low-rank approximation, which requires much computation. Based on an anisotropic-Helmholtz P/S wave-mode decomposition method, we propose a novel and efficient approach to produce angle-domain common-image gathers (ADCIGs) in the elastic reverse time migration (ERTM) of VTI media. To start with, we derive an anisotropic-Helmholtz decomposition operator from the Christoffel equation in VTI media, and use this operator to derive the decomposed formulations for anisotropic P/S waves. Second, we employ the first-order Taylor expansion to calculate the normalized term of decomposed formulations and obtain the anisotropic-Helmholtz decomposition method, which generates the separated P/S wavefields with correct amplitudes and phases. Third, we develop a novel way that uses the anisotropic-Helmholtz decomposition operator to define the polarization angles for anisotropic P/S waves and substitute these angles to decomposing formulations. The polarization angles are then calculated directly from the separated vector P- and S-wavefields and converted to the phase angles. The ADCIGs are thusly produced by applying the phase angles to VTI ERTM. In addition, we develop a concise approximate expression of residual moveout (RMO) for PP-reflections of flat reflectors in VTI media, which avoids the complex transformations between the group angles and the phase angles. The approximate RMO curves show a good agreement with the exact solution and can be used as a tool to assess the migration velocity errors. As demonstrated by two selected examples, our ADCIGs not only produce the correct kinematic responses with regards to different velocity pertubatation, but also generate the reliable amplitude responses versus different angle. The final stacking images of ADCIGs data exhibit the identical imaging effect as that of VTI ERTM.

A robust migration velocity analysis method based on adaptive differential semblance optimization

Migration velocity analysis (MVA) is an efficient tool to reconstruct low wavenumber components of the model. Compared with data domain methods, the MVA methods are implemented in image domain by processing imaging results directly through minimizing moveouts and improving the coherence of the common image gathers (CIGs), such as angle domain common image gathers (ADCIGs) or subsurface offset domain image gathers (ODCIGs). As one of the wave-equation based migration velocity analysis (WEMVA) methods, differential semblance optimization (DSO) can automatically detect the moveout existed in the CIGs and is convenient to implement. However, referring to the CIGs contaminated by spurious imaging artefacts caused by uneven illumination and irregular observation geometry, the traditional DSO method may produce poor velocity update with oscillations, which can prevent rapid convergence to a correct velocity model. To deal with this issue and extend the solution space, we introduce an adaptive DSO (ADSO) method by replacing the traditional image matching with energy distribution matching. By reducing dependence on the imaging results and introducing a variable weighting function in the calculation of the adjoint sources, the amplitude of the inverted model can be evenly distributed and free of artefacts. Three numerical examples show that the ADSO method is robust with little artefacts presenting in the gradients. Combined with the improved gradient, the ADSO can lead to a stable update.

Computing dip-angle gathers using Poynting vector for elastic reverse time migration in 2D transversely isotropic media

Angle-domain common-image gathers (ADCIGs) have wide applications in seismic imaging. For isotropic elastic reverse time migration (ERTM), we can produce dip-angle ADCIGs by using conventional Poynting vectors. Seismic anisotropy widely occurrs in Earth materials, such as in the shales and fractured reservoirs. ERTM based on the isotropic elastic wave equation is unable to accurately image anisotropic structures, leading to noise, discontinuous reflection events and mispositioning in migration results. Hence, conducting ERTM and generating dip-angle ADCIGs for anisotropic media require solving the anisotropic elastic wave equation. However, it is challenging to compute the gathers using the conventional Poynting vector for anisotropic elastic media. In this study, we derive the group and phase Poynting vectors, in which we use the optical flow method to stabilize the phase-related Poynting vectors. This approach admits efficient calculation of dip-angle ADCIG in anisotropic media. It also suppresses noise in anisotropic ERTM. The results of numerical experiments demonstrate the effectiveness of the proposed method.

Deprimary reverse time migration angle gathers with a stabilized Poynting vector

Deprimary reverse time migration (RTM) mitigates the problem of low-wavenumber noise and false events in conventional RTM, and the generation of high-quality angle-domain common-image gathers or angle gathers during deprimary RTM greatly extends its further applications in velocity model updating and subsurface parameter inversion. Poynting-vector-based methods are the most efficient approach to extract angle gathers from RTM or deprimary RTM. However, the instability problem of Poynting-vector-based methods seriously degrades the quality of the generated angle gathers. The instability problem arises from the oscillatory nature of the Poynting vector. To overcome this issue, we propose a novel approach by harnessing the extra simulated Hilbert transformed wavefield in deprimary RTM. Our approach consists of adding the conventional Poynting vector with an ancillary one derived from the Hilbert transformed wavefield, which allows us to eliminate the oscillatory nature of the conventional Poynting vector and obtain a stable algorithm to extract high-quality angle gathers from RTM or deprimary RTM. By using numerical examples with two synthetic data sets and a field data set from the deepwater Gulf of Mexico, we prove the effectiveness of our method in generating high-quality angle gathers.

Wave-equation migration velocity analysis via the optimal-transport-based objective function

Wave-equation migration velocity analysis builds a kinematically accurate macrovelocity model containing the large-scale structures of the model for seismic imaging or full-waveform inversion (FWI). Differential semblance optimization formulates the misfit function in the subsurface domain by applying a penalty to the unfocused subsurface-offset gathers or the nonflattened angle gathers. Such a penalty leads to gradients with strong artifacts and spurious oscillations, which then leads to slow convergence. We formulate the misfit function using the optimal transport (OT) among neighboring traces in angle-domain common-image gathers (CIGs). Specifically, we measure the unflatness of the gathers by comparing the Wasserstein distance of adjacent traces. Because CIGs are ideal to form a probability distribution, which is required by OT, it is natural to use OT to measure the time shifts between two distributions. Our objective function exhibits well-behaved convex and unimodal properties in a simple model with a single interface, and it is expected to be minimum for the correct velocity when the angle gathers are flat. A synthetic data set example on the Marmousi model indicates the ability of our method to provide an initial model for FWI that allows FWI to converge. We also apply the approach on a marine field data set to further demonstrate its effectiveness in estimating the macrovelocity model.

Residual moveout in angle gathers for converted waves

Multicomponent seismic data have been increasingly collected, for example, with ocean-bottom node/cable surveys. Although the converted waves recorded in multicomponent seismic data have the potential to better illuminate the areas underneath complex structures than P-waves, they have not been widely used in depth imaging. Common industry practice is still limited to P-waves only mainly because the successful imaging of converted waves in prestack depth migration relies on accurate velocity models for P- and S-waves. However, the S-wave velocity model estimation via analysis of converted-wave moveout and tomography is still immature. We derive a general residual moveout (RMO) relation as a function of incident angle or as a reflection angle for converted waves, which can be used for converted-wave tomography based on angle-domain common-image gathers. Our derivation does not have certain limitations, such as slowly changing reflection angles or constant P/S-wave velocity ratios, as in existing algorithms available in the literature. Therefore, the proposed RMO equations are more accurate and can be helpful for S-wave velocity model building. The derived equations are validated using different numerical tests.

First-order particle velocity equations of decoupled P- and S-wavefields and their application in elastic reverse time migration

The separation of P- and S-wavefields is considered to be an effective approach for eliminating wave-mode crosstalk in elastic reverse time migration (RTM). At present, the Helmholtz decomposition method is widely used for isotropic media. However, it tends to change the amplitudes and phases of the separated wavefields compared with the original wavefields. Other methods used to obtain pure P- and S-wavefields include the application of the elastic wave equations of the decoupled wavefields. To achieve high computational accuracy, staggered-grid finite-difference (FD) schemes are usually used to numerically solve the equations by introducing an additional stress variable. However, the computational cost of this method is high because a conventional hybrid wavefield (the P- and S-wavefields are mixed together) simulation must be created before the P- and S-wavefields can be calculated. We have developed the first-order particle velocity equations to reduce the computational cost. The equations can describe four types of particle-velocity wavefields: the vector P-wavefield, the scalar P-wavefield, the vector S-wavefield, and the vector S-wavefield rotated in the direction of the curl factor. Without introducing the stress variable, only the four types of particle velocity variables are used to construct the staggered-grid FD schemes; therefore, the computational cost is reduced. We also develop an algorithm to calculate the P and S propagation vectors using the four particle velocities, which is simpler than the Poynting vector. Finally, we apply the velocity equations and propagation vectors to elastic RTM and angle-domain common-image gather computations. These numerical examples illustrate the efficiency of our methods.

Angle-domain common-image gathers from plane-wave least-squares reverse time migration

Angle-domain common-image gathers (ADCIGs) that can be used for migration velocity analysis and amplitude-versus-angle analysis are important for seismic exploration. However, because of the limited acquisition geometry and seismic frequency band, ADCIGs extracted by reverse time migration (RTM) suffer from illumination gaps, migration artifacts, and low resolution. We have developed a reflection angle-domain pseudoextended plane-wave least-squares RTM method for obtaining high-quality ADCIGs. We build the mapping relations between the ADCIGs and the plane-wave sections using an angle-domain pseudoextended Born modeling operator and an adjoint operator, based on which we formulate the extraction of ADCIGs as an inverse problem. The inverse problem is iteratively solved by a preconditioned stochastic conjugate-gradient method, allowing for reduction in computational cost by migrating only a subset instead of the whole data set and improving the image quality thanks to preconditioners. Numerical tests on synthetic and field data verify that our method can compensate for illumination gaps, suppress migration artifacts, and improve resolution of the ADCIGs and the stacked images. Therefore, compared to RTM, our method provides a more reliable input for migration velocity analysis and amplitude-versus-angle analysis. Moreover, it also provides much better stacked images for seismic interpretation.

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

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.

Acoustic full-waveform inversion to match far-offset reflections with pseudo-horizontal particle acceleration data

In the early stage of acoustic full-waveform inversion (AFWI), it is important to exploit the long-wavelength features of the gradient and suppress its short-wavelength features to update the background velocity. However, due to strong near-offset PP reflections and multiples within the pressure data, conventional AFWI sometimes primarily reconstructs the short-wavelength features of a given model and fails to converge on a reliable subsurface P-wave velocity model. Therefore, this study, we propose the usage of pseudo-horizontal particle acceleration (pseudo-ax) data for AFWI, rather than the original pressure data. Because the amplitudes of PP reflections are implicitly weighted according to the reflection angle in pseudo-ax data, the near-offset PP reflections and multiples of the pseudo-ax data are much weaker than those of the pressure data. As a result, AFWI using pseudo-ax data focuses on reconstructing the longer-wavelength features of a given model in the early iterations, and then gradually reconstructs short-wavelength features as the inversion process continues. Using synthetic and real data examples for the Volve oilfield in the North Sea, we examined the effects and feasibility of this strategy. In the synthetic data example, the proposed strategy rapidly reduced far-offset data misfits related to long-wavelength feature updates and achieved smaller model misfits than the conventional strategy. The real data example showed that the velocity model reconstructed using the proposed strategy flattened some of the reflectors at the angle-domain common-image gathers (ADCIGs) better than the velocity model obtained using the conventional strategy. These findings demonstrate that our strategy converges closer to the real P-wave velocity model than the conventional strategy by building a hierarchical velocity model from long- to short-wavelength structures.

Extracting angle domain common image gather with variable density acoustic-wave equation

Abstract Angle domain common image gathers (ADCIGs), commonly regarded as important prestacked gathers, provide the information required for velocity model construction and the phase and amplitude information needed for subsurface structures in oil/gas exploration. Based on the constant-density acoustic-wave equation assumption, the ADCIGs generated from reverse time migration ignore the fact that the subsurface density varies with location. Consequently, the amplitude versus angle (AVA) analysis extracted from these ADCIGs is not accurate. To partially solve this problem and to improve the accuracy of the AVA analysis, we developed amplitude-preserving ADCIGs suitable for density variations with the assumption of acoustic approximation. The Poynting vector approach, which is efficient and computationally inexpensive, was used to calculate the high-resolution wavefield propagation. The ADCIGs generated from the velocity and density perturbations match the theoretical AVA relationship better than ADCIGs with constant density. The extraction of the AVA analysis of the various combinations of the subsurface medium indicates that the density is non-negligible, especially when the density contrast is sharp. Numerical examples based on a layered model verify our conclusions.

Angle domain common image gathers from reverse time migration by combining the Poynting vector with directional decomposition

ABSTRACTAngle domain common image gathers are crucial for seismic applications such as the migration velocity analysis and amplitude variation with angle analysis. Angle domain common image gathers are the gather of reflection coefficients when seismic waves incident at different angles on the same image point. The curvature of gathers can be used to update the migration velocity model. The amplitude variation of gathers characterizes different rock properties. Estimating the wavefield propagation direction is the most important step in the process of generating angle domain common image gathers. The wavefront propagation direction is perpendicular to the wavefront. Accurately estimating the wavefield propagation direction is crucial for calculating the reflection angle. Existing methods cannot provide the propagation direction with the high angular resolution when the subsurface structure is complex, meaning overlapped wave events exist. We propose a new method to overcome this problem. The proposed method separates overlapped waves with a directional filter bank after the up‐going and down‐going wavefield decomposition. Then, we apply the Poynting vector method to decomposed wavefield slices to determine the propagation directions of corresponding wavefield components. The key feature of the proposed method is that it does not require spatial local windows, and it is computationally efficient. Numerical tests demonstrate that our proposed method can accurately obtain the propagation direction of seismic waves in a wavefield including overlapped waves. The angle domain common image gathers generated using our proposed method have improved image quality with more accurate amplitudes and less noise compared with the angle domain common image gathers produced by the conventional Poynting vector method. It means our proposed method provides high‐quality prestack angle gathers for seismic attribute analysis.

Least-squares inversion-based elastic reverse time migration with PP- and PS-angle-domain common-imaging gathers

Elastic angle-domain common-imaging gathers (ADCIGs) extracted from elastic reverse time migration (ERTM) play a pivotal part in elastic migration velocity analysis, elastic amplitude variation with angle, and attribute interpretation. In practice, however, elastic ADCIGs often suffer from unbalanced amplitude behavior, poor resolution, and low-wavenumber artifacts because of insufficient velocity information, limited recording aperture, uneven illumination, and other inaccuracies of the migration operator. We have developed a new method to improve the quality of elastic ADCIGs extracted from ERTM by posing ERTM imaging as an inverse problem whose misfit function measures the difference between simulated and observed data. The misfit function can be minimized by updating elastic offset-domain common-imaging gathers (ODCIGs) using an optimization method. Based on the transformation between ADCIGs and ODCIGs, the forward operator generates multicomponent seismic data from elastic ODCIGs by applying a scattering condition, and the adjoint operator generates elastic ODCIGs from ERTM using a subsurface space-shift imaging condition. Compared with elastic ODCIGs extracted from ERTM, our method effectively improves the focusing of elastic ODCIGs to produce elastic ADCIGs with higher resolution, fewer artifacts, and improved amplitude coherency across different reflection angles. Several synthetic examples were used to validate the effectiveness of the method.

Pseudo-acoustic anisotropic reverse-time migration of an ocean-bottom cable dataset acquired in the North Sea

ABSTRACT To improve the computational efficiency of reverse-time migration (RTM) for vertically transverse isotropic (VTI) media, various acoustic approximations of the elastic wave equations have been presented. Among these, the pseudo-acoustic wave equation, which combines differential and scalar operators, has the advantage that it does not produce shear wave artefacts. In this study, we investigate the feasibility of pseudo-acoustic anisotropic RTM (PA-RTM) for the analysis of synthetic and observed ocean-bottom cable (OBC) datasets of the Volve oil field in the North Sea. To analyse the influence of anisotropic parameters on RTM images and the sensitivity of data components to seismic anisotropy, we perform PA-RTM using synthetic data by incorporating various background models, as well as pressure wavefields and vertical particle acceleration. The synthetic experiments demonstrate that the anisotropic parameter ε plays an important role, whereas δ is negligible in PA-RTM for VTI media, and that vertical particle acceleration is less affected by seismic anisotropy than the pressure wavefields. Our experiments using observed data show that reflectors are better imaged by PA-RTM than by isotropic-RTM, particularly near the reservoir below the strongly anisotropic region, which is supported by angle-domain common image gathers. These results indicate that PA-RTM using only the vertical component is a suitable option for VTI media when insufficient seismic anisotropy data are available.

Reflection Angle-Domain Pseudoextended Least-Squares Reverse Time Migration Using Hybrid Regularization

Angle-domain common image gathers (ADCIGs) describe the reflectivity variation over reflection angles which are important for seismic exploration. The ADCIGs could be obtained using reverse time migration (RTM). However, because of the limitation of seismic frequency band and acquisition geometry, RTM produces the ADCIGs with low fidelity. We propose a reflection angle-domain pseudoextended least-squares RTM method to improve the quality of the ADCIGs in which the Poynting vector is used to efficiently calculate the angles. We first extend the inverted model in the reflection angle domain and derive a feasible pseudoextended Born modeling operator which can map the reflection angle-domain extended model to seismic data. The modeling operator, associated with an adjoint operator, are then used to build a pseudoextended linearized inversion framework for inverting the angle-dependent reflectivity. Taking advantage of the simplicity and coherency of the ADCIGs, we impose a series of low-rank constraints on the extended angle dimension and a sparse constraint on the whole dimension to ensure the production of high-quality ADCIGs. The proposed method is finally solved by a regularized conjugate gradient algorithm. We conduct several numerical examples on a flat layer model, the Marmousi model, and the Sigsbee2A salt model to test the validity and superiority of the proposed method. The results demonstrate that the proposed method could produce the ADCIGs and the stacked image with higher fidelity than RTM, which provides a reliable input for migration velocity analysis, anisotropic model building, and amplitude versus angle analysis.

True Amplitude Angle Gathers from Reverse Time Migration by Wavefield Decomposition at Excitation Amplitude Time

Reservoir parameter estimation is one of the goals of amplitude-versus-angle (AVA) inversion and angle-domain common image gathers are the basis of AVA inversion. Therefore, the accuracy of kinematic and kinetic information on angle gathers is very important for reservoir characterization. Reverse time migration is one of the most physically accurate migration method. Generating angle gathers from reverse time migration with the Poynting vector method is very efficient. However, due to inaccurate angle measurement and uneven illumination, angle gathers calculated by the Poynting vector method are often not suitable for AVA inversion. In this paper, we propose an efficient method of angle gathers with accurate angular information and amplitude from reverse time migration. We firstly decompose source and receiver wavefield to their up-going and down-going parts by using analytic wavefield. We calculate propagation directions for source down-going wavefield and receiver up-going wavefield by the Poynting vector method and form the angle gathers with these angle information and decomposed wavefield. To reduce memory storage and improve computational efficiency, we decompose wavefield at excitation amplitude time by using a local spatial Fourier transform. We also use a spatial smoothed Poynting vector to improve the stability of angle measurement. We apply an illumination compensation image condition to recover the true amplitude. Numerical examples on Marmousi model and the SEAM two-dimensional (2D) model demonstrate the advantages of our proposed method. The angle gathers based on our method are cleaner with more focus on events energy and better continuity, suffering from less low-frequency noise in the shallow parts and with a distinct cutoff at large angle where reflection terminates. At last, we demonstrate the effectiveness of proposed method on a 2D marine field data example.

Amplitude-Versus-Angle Analysis of Local Angle-Domain Common Image Gathers With Prestack Gaussian-Beam Migration of Seismic Data

The analysis of seismic reflection amplitude versus angle/amplitude versus offset (AVA/AVO) is an important tool for investigating the physical properties of subsurface rocks and/or reservoirs. We propose to generate local angle-domain common image gathers (ADCIGs) from the surface-recorded seismic data for AVA analysis via Gaussian-beam migration (GBM) using a deconvolution imaging condition. The traditional seismic reflection amplitude analysis is often based on the AVO response from common middle point (CMP) gathers. However, the AVO analysis based on the horizontally layered medium assumption can achieve success only in simple geological cases. Our approach provides an AVA response during the migration process that reveals true local physical properties in the image domain even if the image point is at a tilted interface or has a complicated overburden geological structure. We test our approach with a two-layer velocity model with a tilted interface, and with the benchmark Marmousi2 model that has a complicated geological structure. From these two numerical examples, we demonstrate that our method faithfully provides the AVA response that can be used to further interpret the rock/reservoir physical properties.

Suppressing migration image artifacts using a support vector machine method

Reverse time migration (RTM) can produce high-quality images of complex subsurface structures when using seismic data acquired by a reasonably dense data acquisition geometry. However, RTM produces significant image artifacts when using data from a sparse data acquisition geometry because of incomplete cancellation of migration “smiles.” These artifacts obscure migration images of actual geology, leading to possible misidentification of important geologic features of interest. A specularity filter based on the semblance equation is commonly used in the dip-angle angle-domain common image gather (ADCIG) to preserve signals while suppressing image artifacts. In dip-angle ADCIG, the signals are assumed to have higher semblance scores because they are horizontally more coherent than the artifacts. However, this assumption fails when the image artifacts are severe. We have developed a new approach to suppressing migration image artifacts using a support vector machine (SVM) method. We first develop multiple criteria to distinguish between the signals and artifacts in the dip-angle ADCIG, rather than using only the semblance criterion. We then calculate the weights using a supervised SVM method. The weights approach one for valid signal points, and approach zero for artifact points. Finally, we apply the weights to the dip-angle ADCIG to preserve the effective signals and suppress the image artifacts. We verify the effectiveness of our method, denoted as SVM filtering, using numerical tests on synthetic and field data to produce migration images with improved signal-to-noise ratios and reduced aliasing artifacts.

Imaging Enhancement in Angle-Domain Common-Image-Gathers Using the Connected-Component Labeling Method

The quality of seismic migration images strongly depends on accurate velocity models. However, migration velocity models often contain errors causing artifacts which degrade seismic resolution and fidelity. Here, we propose a method to enhance seismic migration images using processes in angle-domain common-image-gathers (ADCIGs), without requiring modification to the velocity model. The ADCIGs impacted from velocity errors show non-flat gathers and scattered noise. To enhance the imaging quality in ADCIGs, these problems need to be treated prior to stacking. Ideally, layers in ADCIGs should be flat without smearing amplitudes through all angles. Using this principle, we iteratively process one reflection at a time by isolating it into a local window and then flattening it. Also, we apply internal processing steps to enhance the signal. The algorithm for segregating a reflection, referred to as the connected-component labeling (CCL) method, is the primary method for extracting any feature that has a continuous form within the ADCIGs. Moreover, this method is insensitive to scattered noise so it is a suitable approach for classifying reflections or noise. To test the efficiency of this algorithm, we create ADCIGs containing relatively poor-quality images using an inaccurate migration velocity model. The primary objective of this test is to show how well the CCL method can select various forms of reflections in the presence of various levels of noise. The results show that the CCL method is capable of individually decomposing a reflection, which can facilitate processing in the internal workflow. Finally, we evaluate the quality of processed migration images by comparing our processed Poynting-vector reverse time migration (PVRTM) images with reverse time migration applied Laplacian filter and partial stacked PVRTM. These comparable migration images are benchmarked against a baseline synthetic reflector model. The essential improvements of our method are addressed by the migration sections, namely the removal of diffraction artifacts at both small and large scales and the improvement of phase coherency. The final stacked migration image produced with our methods shows clearer geological features that are capable of delivering a more reliable seismic interpretation.