Anisotropic Kirchhoff prestack time migration and velocity model building in multicomponent processing

2004 ◽  
Author(s):  
Pål Kristiansen ◽  
Paul Fowler ◽  
Everett Mobley
Geophysics ◽  
1997 ◽  
Vol 62 (2) ◽  
pp. 568-576 ◽  
Author(s):  
Young C. Kim ◽  
Worth B. Hurt, ◽  
Louis J. Maher ◽  
Patrick J. Starich

The transformation of surface seismic data into a subsurface image can be separated into two components—focusing and positioning. Focusing is associated with ensuring the data from different offsets are contributing constructively to the same event. Positioning involves the transformation of the focused events into a depth image consistent with a given velocity model. In prestack depth migration, both of these operations are achieved simultaneously; however, for 3-D data, the cost is significant. Prestack time migration is much more economical and focuses events well even in the presence of moderate velocity variations, but suffers from mispositioning problems. Hybrid migration is a cost‐effective depth‐imaging approach that uses prestack time migration for focusing; inverse migration for the removal of positioning errors; and poststack depth migration for proper positioning. When lateral velocity changes are moderate, the hybrid technique can generate a depth image that is consistent with a velocity field. For very complex structures that require prestack depth migration, the results of the hybrid technique can be used to create a starting velocity model, thereby reducing the number of iterations for velocity model building.


Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. VE211-VE216 ◽  
Author(s):  
Jacobus Buur ◽  
Thomas Kühnel

Many production targets in greenfield exploration are found in salt provinces, which have highly complex structures as a result of salt formation over geologic time. Difficult geologic settings, steep dips, and other wave-propagation effects make reverse-time migration (RTM) the migration method of choice, rather than Kirchhoff migration or other (by definition approximate) one-way equation methods. Imaging of the subsurface using any depth-migration algorithm can be done successfully only when the quality of the prior velocity model is sufficient. The (velocity) model-building loop is an iterative procedure for improving the velocity model. This is done by obtaining certain measurements (residual moveout) on image gathers generated during the migration procedure; those measurements then are input into tomographic updating. Commonly RTM is applied around salt bodies, where building the velocity model fails essentially because tomography is ray-trace based. Our idea is to apply RTM directly inside the model-building loop but to do so without using the image gathers. Although the process is costly, we migrate the full frequency content of the data to create a high-quality stack. This enhances the interpretation of top and bottom salt significantly and enables us to include the resulting salt geometry in the velocity model properly. We demonstrate our idea on a 2D West Africa seismic line. After several model-building iterations, the result is a dramatically improved velocity model. With such a good model as input, the final RTM confirms the geometry of the salt bodies and basically the salt interpretation, and yields a compelling image of the subsurface.


2020 ◽  
Vol 17 (3) ◽  
pp. 525-538 ◽  
Author(s):  
Yimin Sun ◽  
Young Seo Kim ◽  
Shan Qu ◽  
Eric Verschuur

Abstract Joint migration inversion is a recently proposed technology, accommodating velocity model building and seismic migration in one integrated process. Different from the widely accepted full waveform inversion technology, it uses imaging parameters, i.e. velocities and reflectivities of the subsurface, to parameterize its solution space. The unique feature of this new technology is its explicit capability to exploit multiples in its inversion scheme, which are treated as noise by most current technologies. In this paper, we comprehensively evaluate the state-of-the-art joint migration inversion technology from various angles: we first benchmark its performance, on both velocity model building and seismic imaging, against that of the well-accepted workflow comprising full waveform inversion and reverse-time migration using a fully controlled 2D realistic synthetic dataset. Next, we demonstrate its application on a 2D field dataset. Last, we use another 2D synthetic dataset to clearly illustrate the challenges the current joint migration inversion technology is facing. With this paper, we transparently reveal the pros of cons of the current joint migration inversion, and we will also point out the imminent research directions joint migration inversion technology should focus on in the next phase for it to be more widely accepted by the geophysics community.


Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. S47-S55 ◽  
Author(s):  
Parsa Bakhtiari Rad ◽  
Benjamin Schwarz ◽  
Dirk Gajewski ◽  
Claudia Vanelle

Diffraction imaging can lead to high-resolution characterization of small-scale subsurface structures. A key step of diffraction imaging and tomography is diffraction separation and enhancement, especially in the full prestack data volume. We have considered point diffractors and developed a robust and fully data-driven workflow for prestack diffraction separation based on wavefront attributes, which are determined using the common-reflection-surface (CRS) method. In the first of two steps, we apply a zero-offset-based extrapolation operator for prestack diffraction separation, which combines the robustness and stability of the zero-offset CRS processing with enhanced resolution and improved illumination of the finite-offset CRS processing. In the second step, when the finite-offset diffracted events are separated, we apply a diffraction-based time migration velocity model building that provides high-quality diffraction velocity spectra. Applications of the new workflow to 2D/3D complex synthetic data confirm the superiority of prestack diffraction separation over the poststack method as well as the high potential of diffractions for improved time imaging.


2014 ◽  
Vol 33 (9) ◽  
pp. 1024-1028 ◽  
Author(s):  
Matthew Karazincir ◽  
Retti Orumwense

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