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General theory for accommodating primaries and multiples in internal multiple algorithm: analysis and numerical tests

机译:容纳初学和内部多算法倍数的一般理论:分析和数值测试

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The inverse scattering series (ISS) predicts internal multiples directly and without subsurface information. This is achieved through a task-specific subseries within the overall ISS. The ISS leading-order attenuator of first-order internal multiple is the leading-order term in the subseries, that, contributes to the removal of first-order internal multiples. It has shown stand-alone capabilities for internal multiple prediction/attenuation for both marine and on-shore plays. The basic idea behind the leading-order attenuator is that all the events in the data are treated as subevents and combined nonlinearly (three data sets are involved), and among all the combinations first-order internal multiples can be predicted by the combination that has all subevents correspond to primaries. However, the entire data set, consisting of primaries and internal multiples, enters the algorithm. When internal multiples in the data themselves act as subevents, the leading-order attenuator produces not only first-order internal multiples, but also higher-order internal multiples and, at times, spurious events. The latter have been observed in the tests of Fu et al. (2010) and Luo et al. (2011). Weglein et al. (2011) have noted this and suggest that the resolution of the problem would reside in other terms of the ISS. Ma et al. (2012) describes the initial occurrence of the circumstance under which spurious event arises, and explains how to address that issue. This abstract extends the analysis in Ma et al. (2012) to more complex circumstances, and provide a description of the general arrival of spurious events. In this abstract we show how the ISS anticipates the issue due to spurious events and provides the response.
机译:逆散射系列(ISS)直接预测内部倍数,没有地下信息。这是通过整个ISS中的特定任务特定的子系来实现的。一阶内部多次的ISS领先订购衰减器是子系列中的前导术语,这有助于删除一阶内部倍数。它为海洋和岸上扮演的内部多重预测/衰减显示了独立功能。领导衰减器背后的基本思想是,数据中的所有事件都被视为子宫子,并且非线性地(涉及三种数据集),并且在所有组合中可以通过具有的组合预测一阶内部倍数。所有子子句对应于初选。但是,由Primaries和内部倍数组成的整个数据集进入算法。当数据本身中的内部倍数作为子宫时,前导衰减器不仅产生一阶内部倍数,而且产生高阶内部倍数,并且有时是虚假事件。在Fu等人的测试中已经观察到后者。 (2010)和Luo等人。 (2011)。 Weglein等人。 (2011)已注意到这一点,并建议解决问题的解决方案将纳入其他条款。马等人。 (2012)描述了杂散事件所产生的情况的初始发生,并解释了如何解决该问题。这个摘要在Ma等人延伸了分析。 (2012)以更复杂的情况,并提供对杂散事件的一般到来的描述。在这个摘要中,我们展示了由于虚假事件而预期该问题的问题,并提供了回应。

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