Improving subsalt imaging by image conditioning and enhancement with reverse time migration vector image partitions: A Gulf of Mexico case study

Author(s):  
Chunpeng Zhao* ◽  
Olga Kroumova Zdraveva ◽  
Alfonso Gonzalez ◽  
Ryan King ◽  
Ruoyu Gu ◽  
...  
2020 ◽  
Author(s):  
Mandy Wong ◽  
Michael Kiehn ◽  
Eric Duveneck ◽  
Jason McCrank ◽  
Vicente Oropeza Bacci ◽  
...  

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB119-WB126 ◽  
Author(s):  
Elive Menyoli ◽  
Shengwen Jin ◽  
Shiyong Xu ◽  
Stuart Graber

Marine wide-azimuth data in the Gulf of Mexico, reverse time migration (RTM) and anisotropic velocity models have led to significant improvement in subsalt imaging. However, imaging of some steeply dipping subsalt targets such as three-way closures against salt is still difficult. This can be attributed to poor illumination and noise contaminations from various shot records. We apply the visibility analysis method that quantitatively determines which shot records contribute most energy on a specific subsalt prospect area. As a result we selectively migrate only those shot records thereby reducing noise contamination from low energy contributing shot records, improving signal continuity and better trap definition in the target area. Like conventional illumination analysis, the computation takes into account the overburden velocity distribution, acquisition geometry, target reflectivity and dip angle. We used 2D and 3D synthetic data examples to test the concepts and applicability of the method. A Gulf of Mexico case study example using wide-azimuth data demonstrated its use in an industry scale project. It is shown that for the particular 60°–65° subsalt target of interest only 30% of the wide-azimuth shot records are sufficient for the imaging. By reducing noise, the image results show significant improvement in the subsalt area compared to the full shot record RTM volume.


Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB175-WB182 ◽  
Author(s):  
Yan Huang ◽  
Bing Bai ◽  
Haiyong Quan ◽  
Tony Huang ◽  
Sheng Xu ◽  
...  

The availability of wide-azimuth data and the use of reverse time migration (RTM) have dramatically increased the capabilities of imaging complex subsalt geology. With these improvements, the current obstacle for creating accurate subsalt images now lies in the velocity model. One of the challenges is to generate common image gathers that take full advantage of the additional information provided by wide-azimuth data and the additional accuracy provided by RTM for velocity model updating. A solution is to generate 3D angle domain common image gathers from RTM, which are indexed by subsurface reflection angle and subsurface azimuth angle. We apply these 3D angle gathers to subsalt tomography with the result that there were improvements in velocity updating with a wide-azimuth data set in the Gulf of Mexico.


Geophysics ◽  
2015 ◽  
Vol 80 (5) ◽  
pp. S175-S185 ◽  
Author(s):  
Yike Liu ◽  
Hao Hu ◽  
Xiao-Bi Xie ◽  
Yingcai Zheng ◽  
Peng Li

2017 ◽  
Vol 5 (3) ◽  
pp. SN1-SN11 ◽  
Author(s):  
Chong Zeng ◽  
Shuqian Dong ◽  
Bin Wang

Least-squares reverse time migration (LSRTM) overcomes the shortcomings of conventional migration algorithms by iteratively fitting the demigrated synthetic data and the input data to refine the initial depth image toward true reflectivity. It gradually enhances the effective signals and removes the migration artifacts such as swing noise during conventional migration. When imaging the subsalt area with complex structures, many practical issues have to be considered to ensure the convergence of the inversion. We tackle those practical issues such as an unknown source wavelet, inaccurate migration velocity, and slow convergence to make LSRTM applicable to subsalt imaging in geologic complex areas such as the Gulf of Mexico. Dynamic warping is used to realign the modeled and input data to compensate for minor velocity errors in the subsalt sediments. A windowed crosscorrelation-based confidence level is used to control the quality of the residual computation. The confidence level is further used as an inverse weighting to precondition the data residual so that the convergence rates in shallow and deep images are automatically balanced. It also helps suppress the strong artifacts related to the salt boundary. The efficiency of the LSRTM is improved so that interpretable images in the area of interest can be obtained in only a few iterations. After removing the artifacts near the salt body using LSRTM, the image better represents the true geology than the outcome of conventional RTM; thus, it facilitates the interpretation. Synthetic and field data examples examine and demonstrate the effectiveness of the adaptive strategies.


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