The random interfering noise contained in seismic record, if not removed properly, will inevitably pose a threat on the fracture development zone prediction accuracy because of greatly disturbing the key edge detection algorithm used in predicting step. Therefore, it is necessary to remove noise from seismic data and improve the quality of original seismic data. In this study, the independent component analysis(ICA) denoising technique, a blind source separation method, is used to decompose the seismic data into different levels of background and target reflection response of reservoir, and effectively make a distinction between effective signal and the random noise,which makes the processing result better than the conventional denoising algorithm. The processing ensures that the signal information basically does not suffer any losses and proffers a better lateral consistency in waveform characteristics. The field results show that, by applying the denoising method to the seismic data before edge detection, a robust fracture prediction result of fracture development zone distribution is achieved corresponding to the regional characteristics of fracture development, and it is in accordance with the drilling results of fracture development characteristics. This study improves the reliability of the fracture prediction of igneous rock zones.