Application of amplitude thresholding to aid minimum energy adaptive subtraction for multiple attenuation

Model based multiple prediction approaches require an adaptive subtraction step that is able to correct for differences between the real and predicted multiples. The commonly used subtraction process derives shaping operators, in the least squares sense, to minimize the energy difference between the predicted multiples and the field record. Although the minimum energy assumption allows a computationally efficient adaptive subtraction, it can lead to attenuation of primary information. This abstract illustrates how a simple amplitude clipping approach can significantly improve the effectiveness of the least squares adaptive subtraction and minimize primary attenuation