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| An analysis of the influence of velocity error and seismic noise on least squares reverse-time migration |
| Zhen MA1, Cheng-Yu SUN1, Peng-Peng PENG2, Zhen-An YAO3 |
1. School of Geosciences,China University of Petroleum,Qingdao 266580,China
2. Ya'an City Yucheng District Natural Resources and Planning Bureau,Ya'an 625000,China
3. School of Geophysics and Measurement-control Technology,East China University of Technology,Nanchang 330013,China |
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Abstract With the increasingly refined and complicated exploration and development goals,the least-squares inverse-time migration based on inversion theory has gradually become the current development trend.In order to make the least-squares reverse-time migration better for the exploration and development of oil and gas reservoirs,analyzing the imaging effects under different conditions helps to guide the processors to make appropriate adjustments in the actual data processing.For this reason,in view of the migration velocity error and the noise in seismic data in the actual exploration process,the authors made a comparative study of the imaging effects of least-squares reverse-time migration under different conditions.The results show that,in the case of systematic errors in migration velocity,the imaging depth of interface will have errors,and it is difficult for the imaging profile to reflect the actual structure;the influence of smoothed migration velocity errors on least-squares reverse-time migration is much smaller than the systematic error of migration velocity,and proper smoothing can improve the imaging quality,but excessive smoothing can affect the imaging quality;the least-squares reverse-time migration can suppress part of the noise;nevertheless,as the noise in the seismic record increases,the weak reflection gradually cannot be resolved,and it is difficult to reflect the underground structure.
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Received: 27 May 2019
Published: 22 April 2020
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Marmousi model
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Accurate migration velocity imaging results
a—reverse time migration;b—least squares reverse time migration
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Least squares reverse-time migration imaging results with different system error migration velocities
a—migration velocity decreases by 5%;b—migration velocity increases by 5%
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Reverse time migration imaging results with different system error migration velocities
a—migration velocity decreases by 5%;b—migration velocity increases by 5%
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Comparison of normalization data residual convergence curves under different migration velocity errors
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Marmousi model with different smoothness
a—accurate speed(e=0%);b—migration velocity model 1(e=2.7%);c—migration velocity model 2(e=5.24%);d—migration velocity model 3(e=7.28%)
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Least squares reverse-time migration imaging results with different smooth migration velocity
a—velocity without smoothness;b—e=2.7% smoothing speed;c—e=5.24% smoothing speed;d—e=7.28% smoothing speed
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Reverse time migration imaging results with different smooth migration velocity
a—velocity without smoothness;b—e=2.7% smoothing speed;c—e=5.24% smoothing speed;d—e=7.28% smoothing speed
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Comparison of normalized data residuals convergence curves with different smooth migration velocity
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Seismic records with adding different degrees noise
a—seismic record without noise;b—seismic records of ns=5;c—seismic records of ns=1
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Least squares reverse-time migration imaging results of different noisy seismic records
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Reverse time migration imaging results of different noisy seismic records
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