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 nonadaptability 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 nonadaptability 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. INDEX TERMS Deep seismic reflection data, CEEMD, CS, weak signal denoising, OMP. I. INTRODUCTION Deep petroliferous basins have become important areas in current and future exploration [1], [2]. In particular, deep water exploration has seen major breakthroughs in development over several decades [3], [4]. However, deep exploration targets are typically located a region with complex geological structures, and the quality of their seismic data is poor. The associate editor coordinating the review of this manuscript and approving it for publication was Jun Shi. Especially in the slope break zones of deep water and the middle-deep layers, the effective signals are basically submerged in noise [5]. To obtain high-quality imaging of middeep layers, the extraction technology of weak signals has attracted great interest in recent years. Various methods, e.g., the random resonance theory [6], the high-order statistics method [7], the wavelet transform method [8], [9], the SVD (singular value decomposition) method [10], [11], or the EMD (empirical mode decomposition) method [12], can be used to extract weak seismic