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I have proposed a novel iterative deblending approach with multiple constraints: iterative orthogonalization and seislet thresholding. The principle of the proposed approach is to iteratively retrieve the leakage energy in the blending noise section after seislet thresholding during the iterations, using local orthogonalization. Because of the iterative orthogonalization, the data misfit during the iterations can be decreased significantly and thus the convergence can be accelerated. The final deblended performance can also be improved using the proposed approach, compared with that of seislet thresholding. Simulated synthetic and field data examples show a successful performance of the proposed approach.