Migration velocity analysis based on focusing diffractions generated using the CRS wavefront attributes: Application to real land data

In land seismic data processing, the prestack time migration (PSTM) image remains the standard imaging output, but a reliable migrated image of the subsurface depends on the accuracy of the migration velocity model. We have adopted two new algorithms for time-domain migration velocity analysis based on wavefield attributes of the common-reflection-surface (CRS) stack method. These attributes, extracted from multicoverage data, were successfully applied to build the velocity model in the depth domain through tomographic inversion of the normal-incidence-point (NIP) wave. However, there is no practical and reliable method for determining an accurate and geologically consistent time-migration velocity model from these CRS attributes. We introduce an interactive method to determine the migration velocity model in the time domain based on the application of NIP wave attributes and the CRS stacking operator for diffractions, to generate synthetic diffractions on the reflection events of the zero-offset (ZO) CRS stacked section. In the ZO data with diffractions, the poststack time migration (post-STM) is applied with a set of constant velocities, and the migration velocities are then selected through a focusing analysis of the simulated diffractions. We also introduce an algorithm to automatically calculate the migration velocity model from the CRS attributes picked for the main reflection events in the ZO data. We determine the precision of our diffraction focusing velocity analysis and the automatic velocity calculation algorithms using two synthetic models. We also applied them to real 2D land data with low quality and low fold to estimate the time-domain migration velocity model. The velocity models obtained through our methods were validated by applying them in the Kirchhoff PSTM of real data, in which the velocity model from the diffraction focusing analysis provided significant improvements in the quality of the migrated image compared to the legacy image and to the migrated image obtained using the automatically calculated velocity model.

Joint inversion of the reflectivity and the velocity model

During linearized waveform inversion, the presence of small inaccuracies in the background subsurface model can lead to unfocused seismic events in the final image. The effect on the amplitude can mislead the interpretation. We present a joint inversion scheme in the model domain of the reflectivity and the background velocity model. The idea is to unify the inversion of the background and the reflectivity model into a single framework instead of treating them as decoupled problems. We show that with this method, we can obtain a better estimate of the reflectivity than that obtained with conventional linearized waveform inversion. Conversely, the background model is improved by the joint inversion with the reflectivity in comparison with wave-equation migration velocity analysis. We perform tests on 2D synthetics and 3D field data that demonstrate both benefits.

Differential semblance optimisation based on the adaptive quadratic Wasserstein distance

As the robustness for the wave equation-based inversion methods, wave equation migration velocity analysis (WEMVA) is stable for overcoming the multipathing problem and has become popular in recent years. As a rapidly developed method, differential semblance optimisation (DSO) is convenient to implement and can automatically detect the moveout existing in common image gathers (CIGs). However, by implementing in the image domain with the target of minimising moveouts and improving coherence of the CIGs, the DSO method often suffers from imaging artefacts caused by uneven illumination and irregular observation geometry, which may produce poor velocity updates with artefact contamination. To deal with this issue, in this paper, by introducing Wiener-like filters, we modify the conventional image matching-based objective function to a new one by introducing the quadratic Wasserstein metric technique. The new misfit function measures the distance of two distributions obtained by the convolutional filters and target functions. With the new misfit function, the adjoint sources and the corresponding gradients are improved. We apply the new method to two numerical examples and one field dataset. The corresponding results indicate that the new method is robust to compensate low frequency components of velocity models.

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 limited acquisition geometry and seismic frequency band, the ADCIGs extracted by reverse time migration (RTM) suffer from illumination gaps, migration artifacts, and low resolution. We have developed a reflection angle-domain pseudo-extended 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 pseudo-extended 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 dataset and improving image quality thanks to preconditioners. Numerical tests on synthetic and field data verify that the proposed method can compensate for illumination gaps, suppress migration artifacts, and improve resolution of the ADCIGs and the stacked images. Therefore, compared with RTM, the proposed 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.

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.

Application of the migration velocity analysis to a long-offset seismic data in the Ulleung basin, offshore Korea

<p>In order to obtain subsurface velocity for field seismic data, a time processing based on semblance velocity analysis has been performed so far. However, since the results of the time processing do not provide velocity information in the depth domain, it is difficult to know the exact subsurface velocity. In this study, to generate accurate velocity, the depth processing using the migration velocity analysis (MVA), which generates more reasonable subsurface velocity structure than the result from the time processing, is applied to the field marine seismic data obtained from Ulleung basin (offshore Korea). A marine seismic source is generated by air-gun (2,289 cu. in.). The long-offset (5.7 km) multichannel seismic (MCS) data were recorded by 456 receivers. The source and receiver spacings are 25 m and 12.5 m, respectively. The seismic survey line is about 168 L-km. The MVA workflow is composed of building a starting velocity model, sorting data to common offset gathers, Kirchhoff prestack depth migration (PSDM), sorting to common reflection point (CRP) gathers, picking residual moveout (RMO), and updating the velocity model. We repeatedly applied the MVA workflow until the remarkable events in the CRP gather were flat. From the results, we could confirm that the depth processing using MVA is successfully applied to field dataset and generates reasonable velocity structure in depth.</p>