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• W84872090 abstract "The recording and storage capacity of modern seismic acquisition systems is continuously growing, enabling denser sampling and the acquisition of better-quality data. One big hurdle is survey time, since the duration of a survey is directly proportional to the number of sources fired. The proposed way forward is to deploy nearly simultaneous sources. Then, the acquired data are blended, i.e., the response to multiple sources is recorded in a single shot record. The objective of this thesis is to provide a method for the separation of blended data with a specific focus on the marine case. The result of this method will contain the response to only one source in every shot record, hence, the subsequent processing steps will not suffer from the interference noise caused by blending. In order to address this challenge, a firm mathematical formulation is required. Based on this formulation, the problem of separating blended data can be cast as a constrained optimisation problem. A constraint reflects the prior knowledge about the solution, in this case the separated data. The fundamental property of coherency is chosen as constraint and the problem can be solved with the aid of an iterative algorithm. A comparison of this algorithm with similar algorithms currently developed in the industry reveals that there are small but important theoretical and implementational differences. The leakage subspace, a mathematical notion inspired by the convergence analysis of this iterative algorithm, contains data that cannot be separated uniquely. This subspace can be computed prior to the acquisition of the data and establishes the link between acquisition parameters and separation efficiency. The separation method has been successfully applied to one of the few real 3D blended datasets currently available. Moreover, numerically blended datasets have been created based on unblended field data and then have been efficiently separated. Numerical blending gives us the freedom to utilize and study the method under different blending conditions. A well-known challenge in the processing of marine seismic data is the presence of strong surface-related multiples, i.e., up going energy from the subsurface that has been reflected at the surface and travels back into the subsurface. A field-data example showed that the separation algorithm, equipped with a surface-multiple prediction term, is able to suppress the surface-multiples while separating the blended data. Another approach is the use of a sparse inversion scheme for the same objective. This algorithm utilizes prior knowledge in terms of travel-time operators and provided excellent results when tested on simple numerical data. This thesis proposes a solution to the challenge of separating blended data. The added business value of such separation algorithms is significant for any exploration company since it can lead to a substantial reduction of the data acquisition cost." @default.
• W84872090 created "2016-06-24" @default.
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• W84872090 date "2013-01-14" @default.
• W84872090 modified "2023-09-23" @default.
• W84872090 title "Inversion methods for the separation of blended data" @default.
• W84872090 doi "https://doi.org/10.4233/uuid:0820cec3-c497-4c53-b680-3b1eaaade0b6" @default.
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