Common Image Gathers Research Articles

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.

Three-dimensional angle-domain double-square-root migration in VTI media for the large-scale wide-azimuth seismic data

With the development of oil and gas exploration, the conventional seismic migration imaging technology based on the isotropic assumption no longer meets our current requirements for high-resolution images. Migration in anisotropic media has become an essential requirement for oil and gas exploration. Marine seismic exploration has gradually entered the wide-azimuth and high-density seismic data acquisition stage. However, even for current large high-performance computer clusters, it is still very difficult to implement pre-stack depth migration based on shot gathers. Thus, we present a double-square-root (DSR) equation based on three-dimensional (3D) pre-stack depth migration in midpoint-offset domain for a wide-azimuth dataset in transversely isotropic media with a vertical symmetry axis (VTI media). Considering VTI media, the DSR migration requires extensive memory and computation; we adopted the phase-shift plus interpolation approach to improve the computational efficiency. Then, we extract the angle-domain common-image gathers (ADCIGs) during DSR migration. For real large-scale seismic data, we designed an effective parallel implementation of 3D DSR migration with ADCIGs outputs. Finally, we applied the proposed angle-domain VTI DSR migration on wide-azimuth SEG/EAGE salt dome-based data and real data from the China South Sea. Numerical and practical data illustrate the effectiveness of the proposed method.

Angle- and azimuth-domain common-image gathers by reverse time migration for 3D elastic isotropic media

A 2D algorithm for angle-domain common-image gather (CIG) calculation is extended and modified to produce 3D elastic angle and azimuth CIGs. The elastic seismic data are propagated with the elastic particle displacement wave equation, and then the PP-reflected and PS-converted waves are separated by divergence and curl calculations during application of the excitation-time imaging condition. The incident angles and azimuths are calculated using source propagation directions and the reflector normals. The source propagation direction vector is computed as the spatial gradient of the incident 3C P-wavefield. The vector normal to the reflector is calculated using the Hilbert transform. Ordering the migrated images with respect to incident angles for a fixed azimuth bin, or with respect to azimuths for a fixed incident angle bin, creates angle- or azimuth-domain CIGs, respectively. Sorting the azimuth gathers by the incident angle bins causes a shift to a greater depth for too-high migration velocity and to a smaller depth for too-low migration velocity. For the sorted incident angle gathers, the velocity-dependent depth moveout is within the angle gathers and across the azimuth gathers. This method is compared with three other 3D CIG algorithms with respect to the number of calculations and their disk storage and RAM requirements; it is three to six orders of magnitude faster and requires two to three orders of magnitude less disk space. The method is successfully tested with data for a modified part of the SEG/EAGE overthrust model.

Common image gather conditioning using cycle generative adversarial networks

ABSTRACTSeismically derived amplitude‐versus‐angle attributes along with well constraints are the base inputs into inverting seismic into subsurface properties. Conditioning the common image gathers is a common workflow in quantitative inversion and leads to a more accurate inversion product due to the removal of post‐migration artefacts. Here, we apply a neural network to condition the post‐migration gathers. The network is a cycle generative adversarial network, CycleGAN, which was designed for image‐to‐image translation. This can be considered the same problem as translating an artefact rich seismic gather to an artefact free seismic gather. To assess the feasibility of applying the network to pre‐stack conditioning, synthetic data sets were generated to train different networks for different tasks. The networks were trained to remove white noise, residual de‐multiples, gather flattening and a combination of the above for conditioning. The results show that a trained network was able remove white noise providing a more robust amplitude‐versus‐offset calculation. Another network trained using synthetic gathers with and without multiples assisted in multiple removal. However, instability around primary preservation has been observed so the network works better as a residual de‐multiple method. For gather conditioning, a network was trained with the unpaired artefact‐rich and artefact‐free training data where the artefacts included complex moveout, noise and multiples. When applied to the test data sets, the networks cleaned the artefact‐rich test data and translated complex moveout into flat gathers whilst preserving the amplitude response. Finally, two networks are applied to real data where a gather based on the well logs is used to quantify the match between the conditioned gathers and the raw gathers. The first network used synthetic data to train the network and, when applied to real data, provided a better tie with the well. The second network was trained with synthetic gathers whose properties were constrained by real seismic gathers from near the well. As anticipated, the network trained on the representative training data outperforms the network trained using the unconstrained data. However, the ability of the first network to condition the gather indicates that a sweep of networks can be trained without the need for real data and applied in a manner analogous to the way parameters are adjusted in traditional geophysical methods. The results show that the different neural networks can offer an alternative or augmentation to the existing geophysical workflow for conditioning pre‐stack seismic gathers.

Separating and imaging diffractions in dip domain on the basis of slope analysis

Fracture-cave reservoirs in carbonate rocks are characterized by a large difference in fracture and cavity size, and a sharp variation in lithology and velocity, thereby resulting in complex diffraction responses. Some small-scale fractures and caves cause weak diffraction energy and would be obscured by the continuous reflection layer in the imaging section, thereby making them difficult to identify. This paper develops a diffraction wave imaging method in the dip domain, which can improve the resolution of small-scale diffractors in the imaging section. Common imaging gathers (CIGs) in the dip domain are extracted by Gaussian beam migration. In accordance with the geometric differences of the diffraction being quasilinear and the reflection being quasiparabolic in the dip-domain CIGs, we use slope analysis technique to filter waves and use Hanning window function to improve the diffraction wave separation level. The diffraction dip-domain CIGs are stacked horizontally to obtain diffraction imaging results. Wavefield separation analysis and numerical modeling results show that the slope analysis method, together with Hanning window filtering, can better suppress noise to obtain the diffraction dip-domain CIGs, thereby improving the clarity of the diffractors in the diffraction imaging section.

Extraction of P- and S-wave angle-domain common-image gathers based on first-order velocity-dilatation-rotation equations

Accuracy of angle-domain common-image gathers (ADCIGs) is the key to multi-wave AVA inversion and migration velocity analysis, and of which Poynting vectors of pure P- and S-wave are the decisive factors in obtaining multi-component seismic data ADCIGs. A Poynting vector can be obtained from conventional velocity-stress elastic wave equations, but it focused on the propagation direction of mixed P- and S-wave fields, and neither on the propagation direction of the P-wave nor the direction of the S-wave. The Poynting vectors of pure P- or pure S-wave can be calculated from first-order velocity-dilatation-rotation equations. This study presents a method of extracting ADCIGs based on first order velocity-dilatation-rotation elastic wave equations reverse-time migration algorithm. The method is as follows: calculating the pure P-wave Poynting vector of source and receiver wavefields by multiplication of P-wave particle-velocity vector and dilatation scalar, calculating the pure S-wave Poynting vector by vector multiplying S-wave particle-velocity vector and rotation vector, selecting the Poynting vector at the time of maximum P-wave energy of source wavefield as the propagation direction of incident P-wave, and obtaining the reflected P-wave (or converted S-wave) propagation direction of the receiver wavefield by the Poynting vector at the time of maximum P-(S-) wave energy in each grid point. Then, the P-wave incident angle is computed by the two propagation directions. Thus, the P- and S-wave ADGICs can obtained Numerical tests show that the proposed method can accurately compute the propagation direction and incident angle of the source and receiver wavefields, thereby achieving high-precision extraction of P- and S-wave ADGICs.

Velocity Inversion with an Iterative Normal Incidence Point (NIP) Wave Tomography with Model-Based Common Diffraction Surface (CDS) Stack

Normal Incidence Point (NIP) wave tomography inversion has been recently developed to generate a velocity model using Common Reflection Surface (CRS) attributes, which is called the kinematic wavefield attribute. In this paper, we propose to use the model based Common Diffraction Surface (CDS) stack method attributes instead of data driven Common Reflection Surface attributes as an input data parameter. In this way, the effects of Normal wave on Normal Incidence Point wave calculation are removed. In the proposed method, the velocity model is updated iteratively by an interactive between Common Diffraction Surface attributes and the velocity model produced by Normal Incidence Point wave tomography inversion. We applied the proposed method on a 2D complex land data set in the northeast of Iran. The events in the Common Image Gathers (CIGs) become flat after migrating the pre stack data by using the obtained velocity. This is while the events on the same Common Image Gathers that are processed by the data driven Common Reflection Surface stake method are not well flatted. These results show a great capability of the proposed method to obtain the velocity model compared to the single step Normal Incidence Point wave tomography inversion with Common Reflection Surface attributes.

Surface-offset gathers from elastic reverse time migration and velocity analysis

Angle-domain common-image gathers (ADCIGs) from elastic reverse time migration (ERTM) are valuable tools for seismic elastic velocity estimation. Traditional ADCIGs are based on the concept of common-offset domains, but common-shot domain implementations are often favored for computational cost considerations. Surface-offset gathers (SOGs) built from common-offset migration may serve as an alternative to the common-shot ADCIGs. We have developed a theoretical kinematic framework between these two domains, and we determined that the common SOG gives an alternative measurement of kinematic correctness in the presence of incorrect velocity. Specifically, we exploit analytical expressions for the image misposition between these two domains, with respect to the traveltime perturbation caused by velocity errors. Four formulations of the PP and PS residual moveout functions are derived and provide insightful information of the velocity error, angle, and PS velocity ratio contained in ERTM gathers. The analytical solutions are validated with homogeneous examples with a series of varied parameters. We found that the SOGs may perform in the way of simplicity and linearity as an alternative to the common-shot migration. To make a full comparison with ADCIGs, we have developed a cost-effective workflow of ERTM SOGs. A fast vector P- and S-wave decomposition can be obtained via spatial gradients at selected time steps. A selected ERTM imaging condition is then modified in which the migration is done by offset groups between each source and receiver pair for each P- and S-wave decomposition. Two synthetic (marine and land) examples are used to demonstrate the feasibility of our methods.

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

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.

Multiscale phase inversion for 3D ocean‐bottom cable data

ABSTRACTWe invert three‐dimensional seismic data by a multiscale phase inversion scheme, a modified version of full waveform inversion, which applies higher order integrations to the input signal to produce low‐boost signals. These low‐boost signals are used as the input data for the early iterations, and lower order integrations are computed at the later iterations. The advantages of multiscale phase inversion are that it (1) is less dependent on the initial model compared to full waveform inversion, (2) is less sensitive to incorrectly modelled magnitudes and (3) employs a simple and natural frequency shaping filtering. For a layered model with a three‐dimensional velocity anomaly, results with synthetic data show that multiscale phase inversion can sometimes provide a noticeably more accurate velocity profile than full waveform inversion. Results with the Society of Exploration Geophysicists/European Association of Geoscientists and Engineers overthrust model shows that multiscale phase inversion more clearly resolves meandering channels in the depth slices. However, the data and model misfit functions achieve about the same values after 50 iterations. The results with three‐dimensional ocean‐bottom cable data show that, compared to the full waveform inversion tomogram, the three‐dimensional multiscale phase inversion tomogram provides a better match to the well log, and better flattens angle‐domain common image gathers. The problem is that the tomograms at the well log provide an incomplete low‐wavenumber estimate of the log's velocity profile. Therefore, a good low‐wavenumber estimate of the velocity model is still needed for an accurate multiscale phase inversion tomogram.

A stable and effective strategy for angle gather extraction from reverse time migration using traveltime gradient

ABSTRACTThe generation of angle-domain common imaging gathers (ADCIGs) from reverse time migration (RTM) is essential for velocity updates, migration quality control and amplitude variation with angle (AVA) inversion. However, computational stability and efficiency challenges remain with ADCIGs extracted from RTM. Here, we develop a stable and effective strategy to produce ADCIGs during RTM based on the traveltime gradient. The first arrival traveltime is calculated efficiently using the dynamic programming scheme, and the source-side propagating direction of the local plane-wave can be obtained using the traveltime field gradient. Compared with propagation directions calculated using the local slowness analysis method, the traveltime gradient can also provide stable and accurate source-side directions. Benefitting from the migrated images, we can collect normal direction information for the reflector from the stacked images effectively using the omnidirectional plane-wave destruction (OPWD) method. Construction of subsurface scattering angles is straightforward via combination of the source-side propagation and reflector normal directions. Subsequently, we apply an effective imaging condition based on the excitation criterion in the angle domain to generate ADCIGs. Thanks to conversion from a wavefield-based to a traveltime-based calculation, the proposed method provides more stable and reliable wave propagation directions in complicated areas compared with the Poynting vector (PV) method which is based on the full wavefield. Because traveltime can be calculated efficiently beforehand, the proposed method can be adapted economically to the conventional RTM imaging frame, which reveals significant implementation potential for practical seismic exploration. We demonstrate the stability and effectiveness of this approach for both synthetic and field data.

Gaussian beam velocity tomography based on azimuth-opening angle domain common imaging gathers

Abstract Ray-based tomography in the imaging domain, implemented with seismic migration, is currently widely used in industrial applications. However, conventional ray-based tomography has some inherent problems, such as shadow area, multi-path problem and so on, which limit the inversion accuracy. To alleviate these problems, we proposed Gaussian beam velocity tomography (GBT) based on azimuth-opening angle domain common imaging gathers (ADCIGs). According to the first-order Born and Rytov approximations, we derived a linear relationship between travel-time perturbation and velocity perturbation in the imaging domain, by which we construct the explicit expression of the sensitivity kernel function and use a Gaussian beam operator to compute the kernel. Furthermore, by introducing the preconditioned model regularization, a method of GBT under the constraint of a structure-guided filter is derived. Iterative applications of migration and tomography, both based on a Gaussian beam propagator, embody the idea of integrating velocity inversion and imaging. Numerical tests on both synthetic data and field data demonstrate that Gaussian beam propagator-based travel-time tomography in the imaging domain is effective.

Spatial distribution of gas hydrate deposits in Krishna-Godavari offshore basin, Bay of Bengal

To delineate the occurrences of gas hydrates and free gas in the Krishna-Godavari (KG) basin, Bay of Bengal, we used 3D seismic data to construct a velocity model of high spatial density. We used an automated version of migration velocity analysis to estimate P-wave velocities using Kirchoff prestack time migration. We manually checked all common image gathers (CIGs) to assess the reliability of the auto-picking algorithm. The velocity model was validated against available downhole information from drilling Sites NGHP-01-02, NGHP-01-03, and NGHP-01-10. The model shows a) anomalously high velocities at Site NGHP-01-10 where significant gas hydrates were reported and b) background velocities at Sites NGHP-01-02 and NGHP-01-03 where a negligible amount of hydrate was recovered. A bottom simulating reflector (BSR) is identified in the 3D seismic data, and an average velocity map is prepared above the BSR. Background velocities of marine sediments in the KG basin vary from 1.43 km/s to 1.6 km/s; velocities higher than 1.65 km/s indicate gas hydrate bearing sediments while velocities lower than 1.43 km/s indicate free gas bearing sediments. High velocities observed below seafloor mounds and ridges suggest the presence of gas hydrate in a structurally deformed area. Slope basins are generally devoid of gas hydrates. Free gas is observed at depths of up to several hundred meters below the BSR suggesting the migration of deeper fluid/gas into the gas hydrate stability zone (GHSZ). Zones of gas hydrates and free gas are preferentially oriented along major faults indicating the role of faults in the transportation of free gas and formation of gas hydrates deposits. We identify a free gas bearing horizon at depths (>300 m) below the BSR, which might contribute to the lateral migration of free gas. Gas hydrate deposits in KG basin are classified into two categories: i) leaky deposits which occur in the areas of active seafloor faults, and are characterized by heterogeneous distribution of gas hydrates, and ii) non-leaky deposits which are formed in areas of subsurface faults, and show a relatively homogeneous distribution of gas hydrates. Site NGHP-01-10 is a good example of leaky gas hydrate deposits above a deep-seated gas reservoir.

Traveltime tomography and prestack depth migration for vertical seismic profiling of an angle-domain walkaway on a complex surface

Walkaway VSP cannot obtain accurate velocity field, as it asymmetrically reflects ray path and provides uneven coverage to underground target, thereby presenting issues related to imaging quality. In this study, we propose combining traveltime tomography and prestack depth migration for VSP of an angle-domain walkaway, in a bid to establish accurate two-dimensional and three-dimensional (3D) velocity models. First, residual curvature was defined to update velocity, and an accurate velocity field was established. To establish a high-precision velocity model, we deduced the relationship between the residual depth and traveltime of common imaging gathers (CIGs) in walkaway VSP. Solving renewal velocity using the least squares method, a four-parameter tomographic inversion equation was derived comprising formation dip angle, incidence angle, residual depth, and sensitivity matrix. In the angle domain, the reflected wave was divided into up- and down-transmitted waves and their traveltimes were calculated. The systematic cumulative method was employed in prestack depth migration of a complex surface. Through prestack depth migration, the offset-domain CIGs were obtained, and dip angle was established by defining the stack section horizon. Runge—Kutta ray tracing was employed to calculate the ray path from the reflection point to the detection point, to determine the incident angle, and to subsequently calculate the ray path from the reflection point to the irregular surface. The offset-domain residual depths were mapped to the angle domain, and a new tomographic equation was established and solved. Application in the double complex area of the Tarim Basin showed the four-parameter tomographic inversion equation derived in this paper to be both correct and practical and that the migration algorithm was able to adapt to the complex surface.

Improving seismic image using the common-horizon panel

Generating high-quality seismic images requires accurate velocity models. However, velocity errors are predictably brought into the models. To mitigate the influences of velocity errors, we have used the common-horizon panel (CHP) for migration velocity analysis. CHP provides quantitative information to adjust mispositioned interfaces or correct deformed wavefields, which leads to improved image quality. It is generated by extrapolating seismic gathers to a selected target horizon and applying the time-shift imaging condition. Compared with the commonly used common-image gathers, the events in CHPs are more trackable because geologic interfaces are typically continuous in space. For a correct velocity model, the panel indicates a flat event at zero time lag, whereas in the case of an erroneous velocity model, the event becomes kinematically oscillating. This distinguishing difference provides a practical criterion to verify whether the migration velocity model is correct and to estimate the velocity or wavefield errors based on how much the event deviates from zero time lag. Tests on synthetic and field data sets have shown that the seismic images are improved by using the proposed CHP technique.

Kinematics of common-image gathers — Part 2: Tomographic ray tracing and applications

Tomographic ray tracing is the critical step in ray-based tomographic approaches when we need to represent as precisely as possible the wavepaths of the migration. To be able to update velocities from picked information in the migrated domain, one must be able to back propagate the misfocusing information (e.g., the residual moveout [RMO]) into the model through the tracing of tomographic rays. The complex kinematics associated with some types of migration, ray based or not, will give us RMO curvatures that will be impossible to explain with traditional tomographic ray-tracing methods. We have evaluated a generic method for tracing these rays by fitting constraints unique to each migration approach. We found that, on synthetic and real data, using the correct set of equations in the tomographic ray-tracing engine can make a significant difference in the velocity model update.

A causal imaging condition for reverse time migration using the Discrete Hilbert transform and its efficient implementation on GPU

Abstract Reverse time migration (RTM) has shown a significant advantage over other imaging algorithms for imaging complex subsurface structures. However, low-wavenumber noise severely contaminates the image, which is one of the main issues in the RTM algorithm. To attenuate the undesired low-wavenumber noise, the causal imaging condition based on wavefield decomposition has been proposed. First, wavefield decompositions are performed to separate the wavefields as up-going and down-going wave components, respectively. Then, to preserve causality, it constructs images by correlating wave components that propagate in different directions. We build a causal imaging condition in this paper. Not only does it consider the up/down wavefield decomposition, but it also applies the decomposition on the horizontal direction to enhance the image quality especially for steeply dipping structures. The wavefield decomposition is conventionally achieved by the frequency-wavenumber (F-K) transform that is very computationally intensive compared with the wave propagation process of the RTM algorithm. To improve the efficiency of the algorithm, we propose a fast implementation to perform wavefield separation using the discrete Hilbert transform via the Graphics Processing Unit. Numerical tests on both the synthetic models and a real data example demonstrate the effectiveness of the proposed method and the efficiency of the optimized implementation scheme. This new imaging condition shows its ability to produce high image quality when applied to both the RTM stack image and also the angle domain common image gathers. The comparison of the total elapsed time for different methods verifies the efficiency of the optimized algorithm.

Depth Migration Velocity: Differential Semblance Analysis for Sumatra Forearch Basin

The specific goal of this work is to present a complete velocity map obtained by picking the velocity in Common Image Gather (CIG) map. We simulated a shot gather in order to obtain a synthetic travel time data for depth analysis. We successfully determined the correct migration velocity and presented the velocity interval model. For further study, we also conducted a Semblance analysis in order to obtain a coherency panel between the energy and the depth migration velocity analysis. We successfully interpreted the conventional semblance profile that the correct velocity model maximizes that energy which is represent higher value. For the real case, The data set was acquired by CGGVeritas in 2009 of RMS velocities recorded in 48 CMP points. The results of the semblance analysis shows well coherence with the seismic reflectance data that reveals the Low Velocity Zone of Sumatra fault related to the present of fluid and gas.

Seismic evidence of free gas migration through the gas hydrate stability zone (GHSZ) and active methane seep in Krishna-Godavari offshore basin

Abstract Seismic amplitude versus offset (AVO) analysis was performed on the multichannel seismic data in the vicinity of Site NGHP-01-10, where thick fracture-filled gas hydrate is reported, to understand the fluid migration in fracture dominated gas hydrate system. Amplitude preserved common image gathers (CIG) are used in extracting the seismic amplitude with offset for seafloor, bottom simulating reflectors (BSR), and different horizons within the gas hydrate stability zone (GHSZ). The extracted amplitudes are fitted with three-term Shuey's AVO approximation to estimate the intercept and gradient values. Based on the intercept and gradient values, two distinct classes of seismic AVO responses are observed; class IV AVO (decreasing negative amplitudes with increasing offsets) and class III AVO (increasing negative amplitudes with increasing offsets) for the BSR and other horizons above the BSR. The large negative intercept and gradient values which indicate class III AVO ranges from −0.2 to −1.8 for the inline seismic profile and from −0.01 to −0.3 for the crossline profile. The presence of class III AVO anomaly within the gas hydrate stability zone (GHSZ) provides evidence of existence of free gas which may be migrating along the fault system. Some of the active faults are exposed on the surface and show gas venting signatures such as gas-flares and pockmarks in the multibeam data.