Abstract: DAS ( Distributed fiber Acoustic Sensing) is a new sensing technology. However, the effective signals in DAS data are covered by a variety of complex and strong noise with a very low signal-to-noise ratio, which seriously affects the subsequent signal inversion and interpretation. Therefore, an attention-guided deep network (ADNet: Attention-guided Denoising convolutional neural Network) is proposed for DAS exploration data intelligent denoising. Compared to traditional methods, an attention-guiding module is introduced into the network to generate an attention-characteristic map, so that the deep network focuses on the parts with strong characteristics to improve the performance of network model in denoising. Through testing and comparing with traditional methods, it is proved that ADNet has great advantages in noise reduction and efficiency improvement.

Key words: attentional mechanism； , distributed fiber acoustic sensing (DAS)； , borehole profile； , signal to noise ratio； , noise suppression