Dip Correction for Convolutional Modelling and Elastic Inversion

E-Lecture by Adam Cherrett

Convolutional seismic modelling is a very convenient and fast technique, widely used in geoscience. It is usually applied in the vertical dimension only, which is one of its shortcomings, leading to inaccurate modelling and restricting its applications. This talk concerns a simple pseudo-3D extension to the convolutional model which improves modelling of dipping events and the lateral resolution of seismic data. This same 3D operator, when used to invert images for elastic properties, can reduce artefacts and improve resolution.