The underlying unity of distinct processing algorithms for: (1) the removal of free surface and internal multiples, (2) Q compensation (without Q), (3) depth imaging, and (4) nonlinear AVO, that derive from the inverse scattering series

Abstract

Listen

Translate article

Pressing seismic exploration challenges are frequently caused by the inability to satisfy the requirements for sub-surface information required by many seismic processing methods. Since the inverse scattering series promises to achieve all processing objectives without the need for subsurface information, it is a natural path to explore for addressing that type of challenge. This paper reports further understanding, perspective and progress towards achieving our processing goals by developing and mining that promise. The items reported here include: (1) new ways to understand both the broad perspective and promise of the inverse scattering series (ISS), as well as the similarities and differences between the distinct methods that derive from the inverse scattering series, and that address, for example, the removal of free surface multiples, the removal of internal multiples, Q compensation (without Q) and depth imaging and AVO, (2) how the directness of the methods derived from the ISS is often under-appreciated, since the directness not only provides the tremendous benefit of direct methods for achieving a specific processing goal, but it also provides a unique and clear and unavoidable message and framework for defining, for the very first time, the precise data required to achieve processing objectives, e.g., for AVO analysis or on-shore or ocean bottom data processing; it is entirely direct, and unique, both in terms of the solutions it provides as well as how it explicitly communicates the types of data needed to achieve its goals, and (3) that for the modelling and generation of synthetic data, e.g., modelling primaries and multiples, that scattering theory actually agrees with everyone else in the area of seismic modelling, that is, the need in modelling for precise subsurface information, and (4) we exemplify recent progress with highlights from the projects within the M-OSRP research program, and discuss open issues and plans.