Details

Autor(en) / Beteiligte

• Sun, Miaomiao
• Li, Zhenchun
• Li, Zhina
• Li, Qingyang
• Liu, Yanli
• Wang, Jiao

Titel

A Noise Attenuation Method for Weak Seismic Signals Based on Compressed Sensing and CEEMD

Ist Teil von

• IEEE access, 2020, Vol.8, p.71951-71964

Ort / Verlag

Piscataway: IEEE

Erscheinungsjahr

2020

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• The exploration of deep and subtle oil and gas reservoirs is currently an important means of increasing production in older oil fields. How to effectively identify weak signals with noise is a common problem faced in such reservoirs. Especially for deep seismic reflection data, the application of traditional denoising methods is limited due to the weak energy and small difference frequency band between the effective signals and the noise. A novel method of noise attenuation for weak seismic signals based on compressed sensing and CEEMD (complementary ensemble empirical mode decomposition) was proposed in this work. This method consists of three steps: First, the CEEMD algorithm, a time-frequency analysis method, was introduced into the classic CS (compressed sensing) denoising method to overcome the non-adaptability of CS. CEEMD decomposed the raw seismic signals into sets of IMFs (finite intrinsic mode functions). The IMFs with noise were reconstructed and denoised by CS. In the second step, an enhancement operator was introduced into the penalty term to ensure that the effective signals could be extracted. Finally, the OMP algorithm is adopted to reconstruct the seismic weak signal to prevent the iterative threshold method from damaging weak effective signals. It was demonstrated through the synthetic seismic record and the field seismic data that (a) the CS method can identify the weak signals submerged in the noise by selecting the basic function that is most similar to the effective signals, but it cannot adaptively suppress the high frequency and high wavenumber noise of the complex seismic records; (b) the proposed method overcome the non-adaptability of CS and enhance the edge information described by the curved wave rather than the noises, as a result, the high frequency noise is suppressed while the middle/low frequency noise and weak effective signals are also effectively separated.