Four-dimensional block matching cooperative filtering (BM4D) has a good performance when it is used for seismic signal denoising. But it has to predict noise standard deviation. To overcome this issue , we present a three-dimensional seismic signal denoising algorithm based on BM4D combined with principal component analysis (PCA). We first use PCA to estimate the noise standard deviation of the seismic signal, and then use the result of estimation for BM4D denoising. The experimental results of synthetic and actual 3D seismic signal denoising show that the proposed algorithm is feasible and can not only achieve the good denoising effect, but also avoid the sensitive limitations of noise level estimation. Compared with other five noise estimation algorithms, the experimental results show that the proposed algorithm has advantages in both noise estimation time and accuracy.