Machine learning-based two-step impedance inversion method and apparatus using seismic data

Abstract

Techniques for a machine learning-based two-step impedance inversion method using seismic data are disclosed. In some embodiments of the disclosed technology, an impedance inversion method includes generating a domain adaptation model configured to predict, based on source data associated with a source area that includes a well, a P-impedance value of a target area that does not include a well, and generating, using the P-impedance value generated by the domain adaptation model, a P-impedance low frequency model configured to predict a final P-impedance value of the target area by performing an inversion. In this way, it is possible to accurately predict P-impedance value of an area where a well does not exist.