AccScience Publishing / JSE / Online First / DOI: 10.36922/JSE026250106
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Improved low-noise waveform feature purification processing for low-signal-to-noise ratio sub-bottom profile data and its application in marine placer exploration

Min Du1 ,  Hua Xue1* ,  Yong Yang1* ,  Shijia Liu1 ,  Miao Yu1
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1 Key Laboratory of Marine Mineral Resources, Ministry of Natural Resources, Guangzhou Marine Geological Survey, China Geological Survey, Guangzhou, Guangdong , China
JSE, 026250106 https://doi.org/10.36922/JSE026250106
Received: 15 June 2026 | Revised: 6 August 2026 | Accepted: 11 August 2026 | Published online: 13 October 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Sub-bottom profile (SBP) measurement is a widely used hydroacoustic geophysical method for continuous imaging of submarine stratigraphy. Conventional processing pipelines rely on basic filtering and envelope extraction, which fail to handle field data with waveform clipping, repeated navigation coordinates, and heavy background noise. Existing commercial seismic software and published algorithms are mainly designed for conventional seismic data and lack customized processing frameworks adapted to high-frequency SBP signals with instrument-specific distortions. This paper proposes a mathematically complete low-noise waveform feature purification (LWFP) processing pipeline tailored for low-signal-to-noise ratio SBP datasets. The integrated workflow contains four interconnected technical modules: (i) Hilbert-wavelet joint envelope reconstruction for restoring clipped waveforms; (ii) two-dimensional adaptive (F–K) sparse filtering for coherent noise attenuation; (iii) self-convolution-based zero-offset multiple suppression; and (iv) weighted-interpolation spatiotemporal coordinate regularization for navigation error correction. Comprehensive quantitative tests were conducted on the test line to validate the processing performance of the proposed method: the signal-to-noise energy gap increased by approximately 27.52 dB after the full LWFP workflow, with only minor amplitude distortion of valid stratigraphic reflections. The optimized profiles enable clear discrimination between mud and sand strata, supporting efficient marine placer delineation when jointly interpreted with single-channel seismic data. This study provides a reproducible, mathematically sound, and equipment-adaptive pipeline that meets the scientific standards of marine geophysical data processing.

Graphical abstract
Keywords
Sub-bottom profile
Low signal-to-noise ratio
Waveform reconstruction
Low-noise waveform feature purification algorithm
Hilbert-wavelet transform
F–K sparse filtering
Zero-offset multiple suppression
Marine placer exploration
Funding
This research was funded by the National Science and Technology Major Project for Deep Earth (Grant No. 2025ZD1009003), the Sub-project of Investigation and Evaluation of Strategic Mineral Resources in Key Sea Areas of China (Grant No. DD202402087), and the National Natural Science Foundation of China (Grant No. 92262304).
Conflict of interest
There is no conflict of interest.
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Journal of Seismic Exploration, Print ISSN: 0963-0651, Published by AccScience Publishing
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