University of Tehran Press Journal of the Earth and Space Physics 2538-371X 47 4 2022 01 21 Fuzzy Partitioning of Radon Domain for Estimation of Water Reverberation Energy Fuzzy Partitioning of Radon Domain for Estimation of Water Reverberation Energy 125 132 85435 10.22059/jesphys.2022.331240.1007366 FA Meysam Zarei Ph.D. Student, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran Hosein Hashemi Assistant Professor, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran Majid Bagheri Assistant Professor, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran Journal Article 2021 10 02 The radon transform has a wide application in seismic processing for each project in different areas. Multiple attenuation is mostly summarized in the use of radon analysis in practice, especially in marine data processing. The definition of mute function is the major challenge in parabolic radon transform. In this paper, a method for segmentation of the radon transform by fuzzy inference system is introduced to separate energy parts in the radon domain. We applied a fuzzy inference system based on the property of energy distribution and its attribute in the radon domain. The result of clustering is the partitioning of the radon domain in three major classes: 1- random noise, 2- multiple, and 3- primary and multiple. The result of applying the new method on real data has shown the applicability of the new method for separation of multiple class from other classes that can assist the processor to define the mute function in the absence of other events in the radon domain. The radon transform has a wide application in seismic processing for each project in different areas. Multiple attenuation is mostly summarized in the use of radon analysis in practice, especially in marine data processing. The definition of mute function is the major challenge in parabolic radon transform. In this paper, a method for segmentation of the radon transform by fuzzy inference system is introduced to separate energy parts in the radon domain. We applied a fuzzy inference system based on the property of energy distribution and its attribute in the radon domain. The result of clustering is the partitioning of the radon domain in three major classes: 1- random noise, 2- multiple, and 3- primary and multiple. The result of applying the new method on real data has shown the applicability of the new method for separation of multiple class from other classes that can assist the processor to define the mute function in the absence of other events in the radon domain. https://jesphys.ut.ac.ir/article_85435_09edb762e5cc25613ae47367dc69fa22.pdf