2-D and 3-D Q-Compensated Image-Domain Least-Squares Reverse Time Migration Through the Hybrid Point Spread Functions and the Hybrid Deblurring Filter

去模糊 反褶积 计算机科学 地震偏移 衰减 图像质量 图像复原 点扩散函数 算法 图像分辨率 滤波器(信号处理) 计算机视觉 反演(地质) 图像处理 人工智能 图像(数学) 地质学 光学 物理 古生物学 构造盆地 地震学
作者
Wei Zhang,Jinghuai Gao
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing [Institute of Electrical and Electronics Engineers]
卷期号:61: 1-13
标识
DOI:10.1109/tgrs.2023.3287299
摘要

Image-domain least-squares reverse time migration (IDLSRTM) through point spread functions (PSFs) is a suitable compromise between image quality and computational efficiency for inversion-based imaging tools. However, the conventional IDLSRTM method in acoustic approximation does not account for the subsurface attenuation effects, which may result in the unfocused migration image in attenuated geological environments. To incorporate the attenuation effects and improve the image quality, we develop a Q-compensated IDLSRTM method by using the hybrid PSFs rather than the acoustic PSFs as the blurring functions to deconvolve the adjoint migration image. These hybrid PSFs are estimated by a combination of computation between the viscoacoustic Born modeling and acoustic reverse time migration (RTM) using a series of uniform point scatterers. To further improve the quality of inverted images, we have applied a hybrid deblurring filter to the hybrid PSFs and acoustic RTM image, before the iterative inversion. Through some numerical examples of synthetic and field data, we have demonstrated that the proposed Q-IDLSRTM method combined with the hybrid PSFs and the hybrid deblurring filter can compensate for the attenuation effects and provide seismic images with improved spatial resolution and balanced image amplitudes. Relative to the conventional IDLSRTM methods through acoustic and hybrid PSFs, the proposed method can provide migration images with higher image resolution and better-balanced image amplitudes.
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