An Inverse Scattering Series (ISS) Data Comprehensive Internal Multiple Attenuation Algorithm That Accommodates Primaries and Internal Multiples in the Input Data

The first part of this dissertation contributes to the removal of internal multiples using the Inverse Scattering Series (ISS). The ISS internal multiple attenuator (of a given specific order), inputs the recorded primaries and internal multiples. The primaries in the input data predict internal multiples of that order from all reflectors at once with accurate time and approximate amplitude and without subsurface information. When the internal multiples in the input data enter the ISS attenuator of a given order, they (1) contribute to higher-order internal multiples removal and (2) under certain circumstances, cause false or spurious events to be predicted. Terms in the ISS, which are of higher order than the attenuator, have the purpose and capability of addressing a shortcoming of its lower-order and less-accommodating relative. The new internal multiple algorithm within this dissertation combines the original lower-order attenuation algorithm with the inclusion and assist of the higher-order terms, providing a comprehensive internal multiple attenuator that can accommodate primaries and internal multiples in the input data. That new higher-order algorithm provides all the benefits of the original ISS internal multiple attenuation algorithms without its deficits and shortcomings.

In principle, only primaries are called for to determine structure and to identify subsurface properties. However, when the collection of primaries is incomplete, then the predicted multiples can, at times, be used to provide an approximate image of unrecorded primaries. The latter can supplement the subsurface structural image from recorded primaries. The second part of this dissertation contributes to (1) studying the procedure of using multiples to enhance subsurface structural imaging, and (2) examining and illustrating the added-value from that procedure.

To summarize, this dissertation contributes to two important topics in exploration seismology, (1) identifying and removing multiples and (2) using multiples. This dissertation shows multiples can be used to provide an approximate image of unrecorded primaries to enhance the subsurface structural from recorded primaries. However, multiples need to be first predicted and removed from the data before imaging the recorded primaries for processing goals that seek to effectively locate and invert reflections.