Unveiling Potential Field Seperation with Emperical Mode Decomposition

This paper proposes utilizing the Empirical Mode Decomposition (EMD) method for separating potential field data. EMD, a novel data analysis approach, is adept at handling non-stationary and nonlinear data, earning recognition in signal processing for its filtering and decomposition capabilities. Its output, termed “Residual,” resembles the regional anomaly found in potential field data, yet it operates without preset parameters, distinguishing it from contemporary field separation methods. Application of this method to magnetic data from the Jianshandian mine in Hubei, China facilitates the construction of a 2.5D inverse model, aiding in inference generation.