A joint filtering method for in-seam seismic signals based on envelope fluctuation awareness and local IMF selection and reconstruction

Severe noise in underground coal mine seismic signals degrades first-break picking accuracy and subsequent data interpretation. To address this, a joint filtering method for in-seam seismic signals based on envelope fluctuation awareness and local Intrinsic Mode Function (IMF) selection and reconstruction is proposed. Initially, an energy-based evaluation metric screens globally decomposed IMFs to reconstruct a preliminary signal retaining primary information. The Hilbert transform then extracts its envelope. Utilizing local envelope fluctuation characteristics, an adaptive discrimination factor precisely localizes weak in-seam wave responses. Subsequently, a sliding window applies local mode decomposition on these target regions. The resulting components are adaptively filtered by evaluating their energy ratio, envelope peak ratio, contrast, and correlation, retaining effective modes and eliminating noise. Validations on both synthetic and field-acquired seismic data demonstrate that the proposed method significantly suppresses complex interference, substantially improves the signal-to-noise ratio, and facilitates first-arrival identification. This approach successfully isolates effective signals from highly noisy records, offering strong application potential for geological exploration in complex environments.