1. State Key Lab of Petroleum Resources and Prospecting, Beijing 102249, China;
2. CNPC Key Lab of Geophysical Exploration, China University of Petroleum (Beijing), Beijing 102249, China
Abstract：2D SRME algorithm is quite efficient, but it brings some errors in 3D multiple prediction when underground layers have a dip angle in the cross lines direction, and the adaptive subtraction is unable to compensate these errors. Therefore we develop a 3D SRME algorithm. Due to data acquisition limitation, source and receiver intervals in cross line directions are too sparse, and 2D algorithm cannot predict the exact multiples for 3D data. Assuming that a multiple contribution gather relative to a seismic trace has a shape of hyperbolas, we can conduct a sparse inversion to this corresponding multiple contribution gather to predict multiples of the trace. 3D model data tests verify the feasibility and validity of the proposed SRME algorithm.
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