Fast model building using demigration and single‐step ray migration

Geophysics ◽  
1994 ◽  
Vol 59 (3) ◽  
pp. 439-449 ◽  
Author(s):  
David N. Whitcombe
Keyword(s):  
Model Building ◽  
Relative Size ◽  
Single Step ◽  
Layer By Layer ◽  
Vertical Layer ◽  
Data Set ◽  
Depth Migration ◽  
Layer Cake ◽  
Time Migration ◽  
Seismic Image

This work provides explorationists with simple procedures to perform depth conversion more accurately than can be achieved with simple vertical layer cake depth conversion. The use of image rays, which are inadequate in structurally complex areas, is avoided. Migrated time interpretations are still used and are "demigrated" using the Kirchhoff time migration equations. This backs out the effect of the time migration prior to a ray depth migration and enables the lateral shifts between the time migrated image and a depth migrated image to be quantified. These shifts can be separated into a mismigration component and a refraction component. The relative size of the components define whether time or depth migration is required and may be used to justify a remigration of the seismic image. Furthermore, the tedious layer by layer approach to ray depth migration may be avoided by using the velocity depth model from the vertical layer cake depth conversion of the time‐migrated data for ray depth migration of the unmigrated data for all horizons in a single step. A satisfactory result is usually achieved without the need to iterate. These methods are illustrated with both a synthetic example and a real 3-D data set from the Norwegian North Sea.

3-D prestack Kirchhoff depth migration: From prototype to production in a massively parallel processor environment

Geophysics ◽  
1998 ◽  
Vol 63 (2) ◽  
pp. 546-556 ◽  
Author(s):  
Herman Chang ◽  
John P. VanDyke ◽  
Marcelo Solano ◽  
George A. McMechan ◽  
Duryodhan Epili
Keyword(s):  
Model Building ◽  
Velocity Model ◽  
Production Scale ◽  
Data Set ◽  
Depth Migration ◽  
Prestack Migration ◽  
Prototype Development ◽  
Time Migration ◽  
Intel Paragon ◽  
Kirchhoff Depth Migration

Portable, production‐scale 3-D prestack Kirchhoff depth migration software capable of full‐volume imaging has been successfully implemented and applied to a six‐million trace (46.9 Gbyte) marine data set from a salt/subsalt play in the Gulf of Mexico. Velocity model building and updates use an image‐driven strategy and were performed in a Sun Sparc environment. Images obtained by 3-D prestack migration after three velocity iterations are substantially better focused and reveal drilling targets that were not visible in images obtained from conventional 3-D poststack time migration. Amplitudes are well preserved, so anomalies associated with known reservoirs conform to the petrophysical predictions. Prototype development was on an 8-node Intel iPSC860 computer; the production version was run on an 1824-node Intel Paragon computer. The code has been successfully ported to CRAY (T3D) and Unix workstation (PVM) environments.

Depth-conversion techniques and challenges in complex sub-Andean provinces

2018 ◽  
Vol 6 (1) ◽  
pp. T209-T229 ◽  
Author(s):  
Antonio J. Velásquez ◽  
Héctor Alfonso
Keyword(s):  
Model Building ◽  
Imaging Techniques ◽  
Velocity Model ◽  
Depth Migration ◽  
Hard Data ◽  
Layer Cake ◽  
Velocity Model Building ◽  
Seismic Image ◽  
Diverse Field ◽  
The Right

The reliability of depth conversion in complex land areas is particularly challenging. Accuracy and precision are usually difficult to achieve simultaneously because of the limited amount and quality of seismic data and sparse control from well data. Ideally, depth-migration methods would be the right tools to produce such data for interpreters. However, despite recent significant breakthroughs in seismic imaging, the ability to provide precise depths is not always achievable with depth-imaging techniques. Therefore, depth conversion remains a crucial tool for converting a seismic image and its interpretation to geologic depth. We have developed an overview of the techniques used for depth conversion through a carefully selected set of geologically diverse field examples. We determine the challenges faced while applying each methodology and, more importantly, share our own experiences and pitfalls. We also evaluate the steps taken to overcome these limitations. All these studies highlight the pragmatic application of techniques and their common pitfalls to improve the workflows that can be implemented to solve other depth-conversion problems. Depth-conversion techniques can be classified depending on the approach used for velocity model building (VMB) (i.e., time-depth and instantaneous velocity functions, layer-cake models, or geostatistical velocity interpolations) and also depending on the ray-tracing procedure (i.e., vertical stretching or image ray). To verify the reliability of the VMB, we establish the following criteria for an acceptable velocity model: (1) honors hard data, (2) integrates all the available sources of velocity information, and (3) makes geologic sense. We reinforce the latter in complex areas where geologic control drives the chosen approach. For instance, in cases with strong velocity gradients (e.g., basement-involved structures), vertical depth conversion may not be able to solve all possible scenarios, resulting in an incomplete assessment of the structural uncertainty. To model such situations, we use a time-to-depth conversion based on the image-ray concept.

Use of RTM full 3D subsurface angle gathers for subsalt velocity update and image optimization: Case study at Shenzi field

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB27-WB39 ◽  
Author(s):  
Zheng-Zheng Zhou ◽  
Michael Howard ◽  
Cheryl Mifflin
Keyword(s):  
Model Building ◽  
Transverse Isotropy ◽  
Velocity Model ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Data Set ◽  
Edge Diffraction ◽  
Time Migration ◽  
Image Optimization ◽  
Free Generation

Various reverse time migration (RTM) angle gather generation techniques have been developed to address poor subsalt data quality and multiarrival induced problems in gathers from Kirchhoff migration. But these techniques introduce new problems, such as inaccuracies in 2D subsurface angle gathers and edge diffraction artifacts in 3D subsurface angle gathers. The unique rich-azimuth data set acquired over the Shenzi field in the Gulf of Mexico enabled the generally artifact-free generation of 3D subsurface angle gathers. Using this data set, we carried out suprasalt tomography and salt model building steps and then produced 3D angle gathers to update the subsalt velocity. We used tilted transverse isotropy RTM with extended image condition to generate full 3D subsurface offset domain common image gathers, which were subsequently converted to 3D angle gathers. The angle gathers were substacked along the subsurface azimuth axis into azimuth sectors. Residual moveout analysis was carried out, and ray-based tomography was used to update velocities. The updated velocity model resulted in improved imaging of the subsalt section. We also applied residual moveout and selective stacking to 3D angle gathers from the final migration to produce an optimized stack image.

SaltSeg: Automatic 3D salt segmentation using a deep convolutional neural network

2019 ◽  
Vol 7 (3) ◽  
pp. SE113-SE122 ◽  
Author(s):  
Yunzhi Shi ◽  
Xinming Wu ◽  
Sergey Fomel
Keyword(s):  
Large Scale ◽  
Model Building ◽  
Ground Truth ◽  
Velocity Model ◽  
Training Data ◽  
Data Sets ◽  
Validation Data ◽  
Data Set ◽  
Seismic Image ◽  
Data Generator

Salt boundary interpretation is important for the understanding of salt tectonics and velocity model building for seismic migration. Conventional methods consist of computing salt attributes and extracting salt boundaries. We have formulated the problem as 3D image segmentation and evaluated an efficient approach based on deep convolutional neural networks (CNNs) with an encoder-decoder architecture. To train the model, we design a data generator that extracts randomly positioned subvolumes from large-scale 3D training data set followed by data augmentation, then feed a large number of subvolumes into the network while using salt/nonsalt binary labels generated by thresholding the velocity model as ground truth labels. We test the model on validation data sets and compare the blind test predictions with the ground truth. Our results indicate that our method is capable of automatically capturing subtle salt features from the 3D seismic image with less or no need for manual input. We further test the model on a field example to indicate the generalization of this deep CNN method across different data sets.

Investigation of deep-water Gulf of Mexico subsalt imaging using anisotropic model, data set and RTM — Tempest

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB21-WB26 ◽  
Author(s):  
Fatmir Hoxha ◽  
Jacqueline O’Connor ◽  
Jeff Codd ◽  
David Kessler ◽  
Alex Bridge ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Deep Water ◽  
Model Building ◽  
Earth Model ◽  
Anisotropic Model ◽  
Model Data ◽  
Data Set ◽  
Depth Imaging ◽  
The Tempest ◽  
Time Migration

Performing accurate depth-imaging is an essential part of deep-water Gulf of Mexico exploration and development. Over the years, depth-imaging technology has provided reliable seismic images below complicated salt bodies, and has been implemented in workflows for both prospect generation as well as reservoir development. These workflows include time domain preprocessing using various multiple elimination techniques, anisotropic model building, and depth-imaging using anisotropic reverse time migration (RTM). However, the accuracy of the depth-migrated volumes is basically unknown because they are tested only in the locations where a well is drilled. In order to learn about the accuracy of anisotropic deep water Gulf of Mexico model building, and depth-imaging tools which are used for processing and imaging of field acquired data, we created a 3D vertical transverse isotropic (VTI) anisotropic earth model and a 3D seismic data set representing subsalt Gulf of Mexico geology. The model and data set are referred to as the Tempest data set, the original being created several years ago. The recent model and data set were created incorporating upgraded technology to reflect recent developments in data acquisition, model building and depth-imaging. Our paper presents the new Tempest anisotropic model, data set, and RTM prestack depth-migration (PSDM) results. The Tempest RTM PSDM is being used to learn about the differences between the exact geological model and the RTM PSDM image, helping in the interpretation of real RTM prestack depth-migrated data.

Depth migration by the Gaussian beam summation method

Geophysics ◽  
2010 ◽  
Vol 75 (2) ◽  
pp. S81-S93 ◽  
Author(s):  
Mikhail M. Popov ◽  
Nikolay M. Semtchenok ◽  
Peter M. Popov ◽  
Arie R. Verdel
Keyword(s):  
Wave Equation ◽  
Model Building ◽  
Velocity Structure ◽  
Velocity Model ◽  
Summation Method ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Depth Migration ◽  
Time Migration ◽  
Ray Methods

Seismic depth migration aims to produce an image of seismic reflection interfaces. Ray methods are suitable for subsurface target-oriented imaging and are less costly compared to two-way wave-equation-based migration, but break down in cases when a complex velocity structure gives rise to the appearance of caustics. Ray methods also have difficulties in correctly handling the different branches of the wavefront that result from wave propagation through a caustic. On the other hand, migration methods based on the two-way wave equation, referred to as reverse-time migration, are known to be capable of dealing with these problems. However, they are very expensive, especially in the 3D case. It can be prohibitive if many iterations are needed, such as for velocity-model building. Our method relies on the calculation of the Green functions for the classical wave equation by per-forming a summation of Gaussian beams for the direct and back-propagated wavefields. The subsurface image is obtained by cal-culating the coherence between the direct and backpropagated wavefields. To a large extent, our method combines the advantages of the high computational speed of ray-based migration with the high accuracy of reverse-time wave-equation migration because it can overcome problems with caustics, handle all arrivals, yield good images of steep flanks, and is readily extendible to target-oriented implementation. We have demonstrated the quality of our method with several state-of-the-art benchmark subsurface models, which have velocity variations up to a high degree of complexity. Our algorithm is especially suited for efficient imaging of selected subsurface subdomains, which is a large advantage particularly for 3D imaging and velocity-model refinement applications such as subsalt velocity-model improvement. Because our method is also capable of providing highly accurate migration results in structurally complex subsurface settings, we have also included the concept of true-amplitude imaging in our migration technique.

Noise removal by migration of time-shift images

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. S105-S111 ◽  
Author(s):  
Sheng Xu ◽  
Feng Chen ◽  
Bing Tang ◽  
Gilles Lambare
Keyword(s):  
Time Lag ◽  
Real Data ◽  
Velocity Model ◽  
Noise Removal ◽  
Time Shift ◽  
Reverse Time ◽  
Coherent Noise ◽  
Data Set ◽  
Depth Migration ◽  
Time Migration

When using seismic data to image complex structures, the reverse time migration (RTM) algorithm generally provides the best results when the velocity model is accurate. With an inexact model, moveouts appear in common image gathers (CIGs), which are either in the surface offset domain or in subsurface angle domain; thus, the stacked image is not well focused. In extended image gathers, the strongest energy of a seismic event may occur at non-zero-lag in time-shift or offset-shift gathers. Based on the operation of RTM images produced by the time-shift imaging condition, the non-zero-lag time-shift images exhibit a spatial shift; we propose an approach to correct them by a second pass of migration similar to zero-offset depth migration; the proposed approach is based on the local poststack depth migration assumption. After the proposed second-pass migration, the time-shift CIGs appear to be flat and can be stacked. The stack enhances the energy of seismic events that are defocused at zero time lag due to the inaccuracy of the model, even though the new focused events stay at the previous positions, which might deviate from the true positions of seismic reflection. With the stack, our proposed approach is also able to attenuate the long-wavelength RTM artifacts. In the case of tilted transverse isotropic migration, we propose a scheme to defocus the coherent noise, such as migration artifacts from residual multiples, by applying the original migration velocity model along the symmetry axis but with different anisotropic parameters in the second pass of migration. We demonstrate that our approach is effective to attenuate the coherent noise at subsalt area with two synthetic data sets and one real data set from the Gulf of Mexico.

Hybrid migration: A cost‐effective 3-D depth‐imaging technique

Geophysics ◽  
1997 ◽  
Vol 62 (2) ◽  
pp. 568-576 ◽  
Author(s):  
Young C. Kim ◽  
Worth B. Hurt, ◽  
Louis J. Maher ◽  
Patrick J. Starich
Keyword(s):  
Model Building ◽  
Cost Effective ◽  
Velocity Model ◽  
Depth Image ◽  
Hybrid Technique ◽  
Prestack Depth Migration ◽  
Depth Imaging ◽  
Depth Migration ◽  
Time Migration ◽  
Prestack Time Migration

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.

Salt interpretation enabled by reverse-time migration

Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. VE211-VE216 ◽  
Author(s):  
Jacobus Buur ◽  
Thomas Kühnel
Keyword(s):  
Model Building ◽  
Velocity Model ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Seismic Line ◽  
Depth Migration ◽  
Time Migration ◽  
Velocity Model Building ◽  
Migration Method

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.

scholarly journals Wave-equation time migration

Geophysics ◽  
2020 ◽  
pp. 1-58
Author(s):  
Sergey Fomel ◽  
Harpreet Kaur
Keyword(s):  
Wave Equation ◽  
Time Domain ◽  
Field Data ◽  
Model Building ◽  
Lateral Velocity ◽  
Depth Migration ◽  
Time Migration ◽  
Expensive Model ◽  
Approximate Equations ◽  
Ray Coordinates

Time migration, as opposed to depth migration, suffers from two well-known shortcomings: (1)approximate equations are used for computing Green’s functions inside the imaging operator; (2) in case of lateral velocity variations, the transformation between the image ray coordinates andthe Cartesian coordinates is undefined in places where the image rays cross. We show that thefirst limitation can be removed entirely by formulating time migration through wave propagationin image-ray coordinates. The proposed approach constructs a time-migrated image without relyingon any kind of traveltime approximation by formulating an appropriate geometrically accurateacoustic wave equation in the time-migration domain. The advantage of this approach is that thepropagation velocity in image-ray coordinates does not require expensive model building and canbe approximated by quantities that are estimated in conventional time-domain processing. Synthetic and field data examples demonstrate the effectiveness of the proposed approach and show that theproposed imaging workflow leads to a significant uplift in terms of image quality and can bridge thegap between time and depth migrations. The image obtained by the proposed algorithm is correctlyfocused and mapped to depth coordinates it is comparable to the image obtained by depth migration.

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