This paper presents the theory of optimal beamforming and its application to attenuating the multiples in seismic data of low signal-to-noise (S/N) ratio as a new method over some popular techniques like the f -k and the Radon transform. The key point of the theory is updating the constraint in optimal beamformer design by using adaptive beamformer with the quiescent weighted vector. Real data example shows that the newly developed optimal beamformer can improve the minimum variance unbiased (MVU) beamformer significantly in attenuating multiples in data of low folding and/or low S/N ratio without much extra cost.