Fast 3D velocity updates using the pre-stack exploding reflector model |

A typical way of decreasing the cost of wavefield extrapolation is to reduce the amount of input data by linearly combining the wavefields using plane-wave phase encoding (Liu et al., 2006; Whitmore, 1995) and random phase encoding (Sun et al., 2002; Romero et al., 2000). Combination of wavefields is exploited by the prestack-exploding reflector model (PERM) (Biondi, 2006) to significantly reduce the data size while keeping the migrated image crosstalk-free. This is achieved by selecting subsurface-offset common-image gathers (SODCIGs) separated by a decorrelation distance such that the wavefields from different SODCIGs in the same modeling experiment do not correlate during migration. Guerra et al. (2009) show that further reduction can be achieved by randomly phase encoding the modeling experiments, significantly decreasing the cost of migration velocity analysis iterations.

An interesting feature of PERM is that, because the wavefields are upward propagated, data can be collected at any depth level. In migration velocity analysis, PERM wavefields can be propagated only in the region with velocity inaccuracies. As a result the velocity update can be performed in a target-oriented way, which contributes to an additional cost reduction of migration velocity analysis.

In 3D, reduction of the data size can be considerable if the initial image used to model PERM wavefields has only in-line subsurface offsets, as in the common-azimuth approximation. We show that, in this case, 3D-PERM data size can be potentially up to two orders of magnitude smaller than 3D-plane wave data. The usefulness of PERM data to migration-velocity analysis with wavefield extrapolation is illustrated using a North Sea 3D dataset.

Fast 3D velocity updates using the pre-stack exploding reflector model |

2010-05-19