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Illumination, resolution, and image quality of PP- and PS-waves for survey planning

PGS Geophysical, Oslo, Norway

Corresponding author: jurgen.hoffmann@pgs.com

The first 20% of the full text of this article appears below.

In the past, survey planning was based mainly on analysis of the acquisition geometry at the surface assuming a symmetric raypath between source and receiver. CMP fold and offset distribution maps were used to compare alternate acquisition geometries. When sources and receivers are at different depths (e.g., for OBS surveys) or when converted waves are considered, this assumption no longer holds, even in a horizontally layered subsurface.

Thus, more advanced methods are required to plan PP- and PS-surveys and to determine their effectiveness by predicting illumination, resolution, and image quality. This article will discuss three more sophisticated techniques: reflection point coverage, common focus point (CFP) resolution analysis, and finite difference (FD) modeling and migration.

	Illumination using reflection point coverage

 
This technique extends the well-known CMP fold analysis. CMP fold calculation is based on only lateral shot and receiver coordinates, but reflection point coverage also includes source and receiver levels and subsurface effects.

The technique simulates the illumination of a target horizon for a given acquisition geometry by a selected raypath or wave mode (e.g., PP- and PS-reflections). Dynamic raytracing is performed in a representative subsurface model and the "successful" rays, those connecting each shot point via the target horizon to the receiver, are recorded. In this context, successful indicates physically meaningful rays obeying Snell's reflection and refraction laws. The attributes of these rays (e.g., offset, amplitude) are then regrouped according to their reflection point position on the target horizon. For each bin cell on the target horizon, a set of attributes is calculated and projected onto the target structure so that target structure and attribute distribution can be correlated. Typical attributes are number of hits, minimum offset, maximum offset, offset distribution, azimuth distribution, or sum of reflection amplitudes.

As an example (Figures 1–3), we use a salt pillow as . . . [Full Text of this Article]