Adaptive prediction filtering in t-x-y domain for random noise attenuation using regularized nonstationary autoregression

Seismic data decomposition into spectral components using regularized nonstationary autoregression

Random noise attenuation using f - x regularized nonstationary autoregression

Seismic data interpolation beyond aliasing using regularized nonstationary autoregression

Random noise attenuation of 3D multicomponent seismic data using a fast adaptive prediction filter

Nonstationary predictive filtering for seismic random noise suppression — A tutorial

Streaming orthogonal prediction filter in the t - x domain for random noise attenuation

(a) Marmousi model and (b) trace interpolation with regularized nonstationa...

(a) Curved model (Figure  2c ) with 70% randomly selected traces removed an...

A 3D field data example. (a) Teapot Dome data set. Denoised data using the ...

(a) Aliased synthetic data, (b) trace interpolation with plane-wave destruc...

Conventional processing methods. Stage I: after ground roll removal, (b) es...

Streaming prediction-error filters

5D dealiased seismic data interpolation using nonstationary prediction-error filter

Physics-constrained deep learning for ground roll attenuation

Random noise attenuation using local signal-and-noise orthogonalization

Seismic data interpolation without iteration using a t - x - y streaming prediction filter with varying smoothness

Preserving signal during random noise attenuation through migration enhancement and local orthogonalization

3-d Butterworth Filtering For 3-d High-density Onshore Seismic Field Data

Retrieving the leaked signals from noise using a fast dictionary-learning method