Tackling the weathering with low ranks: Handling the complex near surface of land seismic data with low-rank-based methods

Imaging and inversion with seismic data recorded with sources and receivers at the surface are powerful tools to infer knowledge about the subsurface. However, creating an image with seismic data is unfortunately not as easy as taking a picture with a smartphone. The estimated subsurface models in many situations are far from ideal due to the...

Towards 3D near-surface correction without NMO: A rank-based approach

To avoid multiple iterations of normal moveout (NMO) velocity estimation followed by short-wavelength statics estimation usually performed on land data, and to also improve the accuracy and computational efficiency of the latter, a low-rank-based residuals statics (LR-ReS) estimation and correction framework has been recently proposed. The...

Low-rank-based residual statics estimation and correction

Surface consistency forms the basis for short-wavelength statics 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 accurate statics. Existing nonsurface-consistent techniques can be prone to errors due to the...

Obtaining angle-dependent reflectivity using the Marchenko redatuming method

When reflection images are studied, often only the zero-offset reflectivity is considered, however, taking into account the angle-dependent reflectivity can add additional information about the subsurface. This additional information can be used to extract the properties of the subsurface using amplitude variation with offset (AVO) analysis....