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An improved method for internal multiple elimination using the theory of virtual events

Petroleum Science 2022年第6期19卷 2663-2674页

作者： Pei-Nan Bao Ying Shi Wei-Hong Wang Wei Zhang Zhe-Jun Pan Key Laboratory of Continental Shale Hydrocarbon Accumulation and Efficient Development Ministry of EducationNortheast Petroleum UniversityDaqingHeilongjiang163318China School of Earth Sciences Northeast Petroleum UniversityDaqingHeilongjiang163318China School of Information and Communication Engineering Faculty of Electronic and Information EngineeringXi'an Jiaotong UniversityXi’anShaanxi710049China National Engineering Laboratory for Offshore Oil Exploration Xi'an Jiaotong UniversityXi’anShaanxi710049China

Compared with first-order surface-related multiples from marine data,the onshore internal multiples are weaker and are always combined with a hazy and occasionally strong interference pattern.It is usually difficult to discriminate these events from complex targets and highly scattering overburdens,especially when the primary energy from deep layers is weaker than that from shallow layers.The internal multiple elimination is even more challenging due to the fact that the velocity and energy difference between primary reflections and internal multiples is tiny.In this study,we propose an improved method which formulates the elimination of the internal multiples as an optimization problem and develops a Convolution factor T.The generated internal multiples at all interfaces are obtained using the Convolution factor T through iterative inversion of the initial multiple model.The predicted internal multiples are removed from seismic data through subtraction.Finally,several synthetic experiments are conducted to validate the effectiveness of our approach.The results of our study indicate that compared with the traditional virtual events method,the improved method simplifies the multiple prediction process in which internal multiples generated from each interface are built through iterative inversion,thus reducing the calculation cost,improving the accuracy,and enhancing the adaptability of field data.

关键词： Internal multiple Convolution factor Elimination Virtual events

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