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Low-rank-based residual statics estimation and correction
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DOI：10.1190/geo2022-0415.1.png)
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Abstract
En 中文
Surface consistency forms the basis for short-wavelength stat-ics estimation. When raypaths in the near surface diverge from a normal incidence or when the normal moveout (NMO) velocity is inaccurate, surface-consistent methods may fail to estimate accu-rate statics. Existing nonsurface-consistent techniques can be prone to errors due to the need to construct pilot traces or pick horizons while imposing additional computational costs. To over-come these limitations and correct for the surface-and nonsur-face-consistent statics, we have developed a low-rank-based residual statics (LR-ReS) estimation and correction framework. The method makes use of the redundant nature of seismic data by using its low-rank structure in the midpoint-offset-frequency domain. Due to the near-surface effect, the low-rank structure is destroyed. Therefore, we estimate the statics by means of low-rank approximation and crosscorrelation. To alleviate the need for accurate rank selection for low-rank approximation and improved statics estimation, we implement the method in an iter-ative and multiscale fashion. Because the low-rank approximation deteriorates at high frequencies, we use its better performance at low frequencies and exploit the common statics among the differ-ent frequency bands. The LR-ReS estimation and correction can be applied to data without an NMO correction, which makes stat-ics estimation independent of the NMO velocity errors. Conse-quently, it can reduce the multiple iterations of the NMO velocity estimation and short-wavelength statics correction commonly needed for conventional methods to improve their performance. Moreover, the LR-ReS estimation does not require windowing of a noise-free area containing aligned primaries or mute to avoid the NMO stretch effect, which enables statics correction of the wavefield of all offsets. To evaluate the performance of our method, we apply it to simulated data and a challenging field data set affected by complex weathering layers and noise, which in-dicate a substantial improvement compared with conventional short-wavelength statics correction.
Keywords:
SINGULAR-VALUE DECOMPOSITION
MATRIX COMPLETION
RECONSTRUCTION
INVERSION
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