Interpolation performs two valuable roles. Firstly it allows holes to be filled, fully or partially depending on their extent. The gaps are often related to acquisition layout or issues. Secondly it allows us to increase spatial sampling density which has beneficial implications for aliasing and stack fold. Regularization places the seismic data onto a regular grid, which helps when merging multiple surveys and can be beneficial or even vital for subsequent migration.
The CGG REVIVE5D algorithm is of particular benefit to land, seabed and wide-azimuth surveys. A global multidimensional interpolator fills gaps in coverage and increases spatial sampling density, while preserving original recorded data.
Up to five interpolation dimensions can be used to infill gaps, increase fold and improve offset-azimuth distribution, especially in areas of complex structure. More dimensions make the model of the data more accurate and the interpolation more effective. This results in improved images as geometry-related migration artefacts are minimized. It also gives cleaner, regularly populated pre-stack gathers with preserved AVO and AVAZ characteristics for reservoir and fracture characterization.
Plots of shot (red) and receiver (blue) locations for a land dataset with irregular acquisition. Note the river running north-south through the center of the survey area. After interpolation of additional shot and receiver locations the gaps have been filled and the fold has been boosted and equalized. This will result in more uniform amplitudes after migration and allow a decrease in bin size to improve resolution.
Data courtesy of GDF, SUEZ, ExxonMobil, Wintershall and EWE.
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