The Application Of Mathematical Morphology In Seismic Data Processing

Traditionally, seismic data denoising is achieved by the difference of frequency, wave number, time difference and amplitude of the seismic wave like f-k filtering, f-x filtering, bandpass filtering, K-L transform and Radon transform,etc. However, when we use the traditional methods, the resolution ratio was reduced at the same time, so we try seeking a new way,multiscale morphology,to filter the waves by fine difference of seismic wave shape. This paper presents a method for noise attenuation by reducing the e1ect of noise using multiscale morphology. The underlying concept of the work is to assign less importance to features of smaller scales as their possibilities of being noises are more. Features at various scales are extracted by means of morphological filtering. The proposed algorithm has been tested on a set of real seismic data corrupted with different types of noises, removes the noises effectively and remains high resolution at the same time.