SEGJ Technical Conference

A data processing technique of removing DC railway noise from time domain magnetotelluric data (part 2)

Abstract Even though applying the far remote reference magnetotelluric (MT) method, we require the long recording period to obtain effective data from the data contaminated by strong and coherent noise in DC railway area. In this study, we focused on the electric time series model including a trend component, natural magnetic signal response, correlated noise components, and white noise, then separated to each component with a Kalman filter algorithm. The method was applied to the magnetotelluric data observed near the DC railway and successfully obtained the positive results in the time domain.