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Results
ABSTRACT We apply a two-stage iterative soft and hard thresholding algorithm to retrieve the super-resolution reflectivity distribution by solving a sparse-constrained optimization problem based on compressive sensing principles. We add an -norm regularization term to the objective function of the least-squares Kirchhoff migration. The proposed algorithm has been applied to a complex synthetic dataset. Compared with -norm and -norm regularizaiton, results show that the super-resolution method with the -norm regularization can clearly suppress migration artifacts and improve spatial resolution. Presentation Date: Wednesday, October 19, 2016 Start Time: 8:00:00 AM Location: 171/173 Presentation Type: ORAL
ABSTRACT Data to data migration is an effective method to use freesurface related multiples in migration which can provide extra illumination of the subsurface; however, the migrated images usually contain many migration artifacts. As they honor the imaging condition, it is difficult to be eliminated directly. In angle domain common image gathers (ADCIGs), the true events are flat and the artifacts can be identified and separated. The subsurface item is added in the source and receiver wavefields to obtain horizontal offset common image gathers (HOCIGs). Using slant stack, we can transform HOCIGs from offset domain to angle domain and obtain ADCIGs. Then the ADCIGs are processed with highresolution parabolic Radon transform to remove the artifacts easier. We apply the workflow of artifacts elimination to marine data and suppress most cross-talks energy generated by the cross-correlation of undesired seismic events. It shows the final images in migration of multiples can be valuable complements for the conventional migration images using primaries only. Presentation Date: Tuesday, October 18, 2016 Start Time: 3:20:00 PM Location: Lobby D/C Presentation Type: POSTER
Automatic 3D fracture plane identification with spatial constraints
Xue, Qingfeng (Institute of Geology and Geophysics Chinese Academy of Sciences) | Wang, Yibo (Institute of Geology and Geophysics Chinese Academy of Sciences) | Chang, Xu (Institute of Geology and Geophysics Chinese Academy of Sciences)
ABSTRACT We present an automatic 3D fracture plane identification workflow for the source locations which are derived from acoustic emission data. The proposed workflow utilizes spatial constrains and contains two steps. Firstly, acoustic emission data belonging to a single fracture are separated by a spatial constraints based clustering method. Secondly, the fracture planes are generated by least squares fitting. Results from real rock experiments verify the effectiveness of proposed workflow. Presentation Date: Wednesday, October 19, 2016 Start Time: 4:00:00 PM Location: 150 Presentation Type: ORAL
- Information Technology > Artificial Intelligence > Representation & Reasoning > Constraint-Based Reasoning (0.91)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Clustering (0.69)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Spatial Reasoning (0.61)
3D P- and S-wave separation and elastic reverse time migration
Zhou, Xiyan (Institute of Geology and Geophysics Chinese Academy of Sciences (IGGCAS)) | Chang, Xu (Institute of Geology and Geophysics Chinese Academy of Sciences (IGGCAS)) | Wang, Yibo (Institute of Geology and Geophysics Chinese Academy of Sciences (IGGCAS)) | Yao, Zhenxing (Institute of Geology and Geophysics Chinese Academy of Sciences (IGGCAS))
ABSTRACT Reverse time migration (RTM) can handle diving-wave, without dip and extreme lateral velocity limitation. Elastic reverse time migration inherits the advantage of traditional RTM, and uses P- and S-wave to get more subsurface information. However, if we just employ cross-correlation imaging condition of the corresponding components of source and receiver wavefields, the cross-talk between P- and S-wave will be generated. So, P- and S-wave separation is a vital step for elastic RTM. Most elastic RTM use divergence and curl operators to decompose P- and S-wave. Those separated wavefileds have different physical meaning with the input wavefileds. In addition, the divergence and curl operator will change the amplitude and phase information. In this paper, we present a 3D elastic wavefields separation method. This method separates P- and S-wave in elastic propagating equation, based on stress-particle-velocity, staggered-grid finite difference. We use this method to separate forward source wavefields and backward receiver wavefields into P- and S-wave components, then we do cross-correlation imaging condition with the corresponding wavefields to get PP and PS migration results. We use a 3D salt model to illustrate the validity of our method. Presentation Date: Wednesday, October 19, 2016 Start Time: 8:50:00 AM Location: Lobby D/C Presentation Type: POSTER