Seismic data processing reveals that internal multiples exhibit highly complex formation mechanisms,making their accurate identification and effective suppression a persistent challenge in geophysical exploration.Traditional methods for internal multiple suppression frequently require manual identification of subsurface reflection interfaces,making them difficult to apply to complex underground medium structures.Moreover,these methods are not only computationally cumbersome but also typically ensure only temporal and positional consistency when predicting internal multiples.The amplitude often deviates from observed values,requiring adaptive matching subtraction algorithms for effective suppression.This study developed an internal multiple suppression method based on Marchenko theory.Specifically,the wavefield relationships between the focusing function and Green’s function were constructed using the convolution and correlation reciprocity theorem of the Green’s function during data processing.The Green’s function was then solved using the focusing function,yielding either multiples or primaries constructed from the Green’s function.This method requires only the background velocity or the original data as operators during the iterative multidimensional correlation and convolution process,rendering it simple and computationally efficient. This study constructed an expression for the primary wave field using the Green’s function and the Marchenko equation.The tests using the SMAART model and actual data from the Gulf of Mexico demonstrate that the Marchenko method can effectively suppress internal multiples under the conditions of complex subsurface media.The iterative process requires no velocity information,providing significant advantages over conventional methods and great potential for application in complex underground environments where layers are difficult to distinguish.