Multiple Seismic Reflection Attenuation Using High-Resolution Radon Filter Method: A Case Study for 2D Land Seismic Data, South of Iraq

This article presents the pre-stack attenuation of multiple noises from a 2-D land seismic survey acquired on the Iraq-Kuwait border in southern Iraq. The processing workflow is performed using the Geovation software from CGG that employs a de-aliased High-Resolution Radon with a non-iterative process for seismic reflection data. First, we apply noise attenuation, surface deconvolution (predictive), and normal move-out (NMO) correction, which is executed using the root-mean-square velocity (RMS velocity) to flatten the primary event, and the Common Mid-Point gathers (CMP gathers) are converted into the Radon domain using a least-squares-parabolic Radon transform. Several tests are performed on some parameters to predict the multiple events using a High-Resolution de-aliased multiple attenuation (RAMUR) algorithm aimed to attenuate multiple events. RAMUR algorithms compute a model of primary and multiple events based on data decomposition into user-defined parabolas and are performed using a high-resolution, de-aliased least-squares method. The Radon transforms separate primary reflection and multiple reflection events in the (-q) domain based on move-out differences between primary and multiple events, which are characterized as events with slower velocity. Reflection events relating to parabolas with a higher curvature are counted as multiples, whereas events with smaller are counted as primary events. The RAMUR algorithms subtract the model of multiples from the input gathers. The workflow effectively attenuates reflection-based generated multiples events, which improves the overall seismic response after imaging, and enhances correlation with well information.