AUTHOR=Wu Jizhong , Shi Ying , Guo Aihua , Lu Pengfei , Yang Qianqian 

TITLE=High-Resolution Imaging: An Approach by Compensating Absorption and Dispersion in Prestack Time Migration With Effective Q Estimation and Fresnel Zone Identification Based on Deep Learning

JOURNAL=Frontiers in Earth Science

VOLUME=9

YEAR=2022

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2021.771570

DOI=10.3389/feart.2021.771570

ISSN=2296-6463

ABSTRACT=<p>We have developed a migration scheme that can compensate absorption and dispersion with effective <inline-formula id="inf1"><mml:math id="m1" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Q</mml:mi></mml:math></inline-formula> estimation and Fresnel zone identification based on deep learning. We use the U-Net neural network technology in deep learning to automatically identify Fresnel zones from compensated migrated dip-angle gathers and obtain the optimal aperture for migration, avoiding the tedious task of manually modifying the boundaries of Fresnel zones. Instead of the interval <inline-formula id="inf2"><mml:math id="m2" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Q</mml:mi></mml:math></inline-formula> factor, we used an effective <inline-formula id="inf3"><mml:math id="m3" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Q</mml:mi></mml:math></inline-formula> parameter to compensate absorption and dispersion. The effective <inline-formula id="inf4"><mml:math id="m4" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Q</mml:mi></mml:math></inline-formula> is estimated using VSP well data and surface seismic velocity data. The proposed scheme can be incorporated into conventional seismic data processing workflow. A field data set was employed to validate the proposed scheme. Higher resolution imaging results with low noise levels are obtained.</p>