Seismic migration of blended shot records with surface-related multiple scattering

This paper focuses on the concept of using blended data and multiple scattering directly in the migration process, meaning that the blended input data for the proposed migration algorithm includes blended surface-related multiples. It also means that both primary and multiple scattering contribute to the seismic image of the subsurface....

Estimation of primaries by sparse inversion from passive seismic data

For passive seismic data, surface multiples are used to obtain an estimate of the subsurface responses, usually by a crosscorrelation process. This crosscorrelation process relies on the assumption that the surface has been uniformly illuminated by subsurface sources in terms of incident angles and strengths. If this is not the case, the...

Estimation of primaries and near-offset reconstruction by sparse inversion: Marine data applications

ost wave-equation-based multiple removal algorithms are based on prediction and subtraction of multiples. Especially for shallow water, the prediction strongly relies on a correct interpolation of the missing near offsets. The subtraction of predicted multiples from the data can easily lead to the distortion of primaries if primaries and...

The concept of double blending: Combining incoherent shooting with incoherent sensing

Seismic surveys are designed so that the time interval between shots is sufficiently large to avoid temporal overlap between records. To economize on survey time, the current compromise is to keep the number of shots to an acceptable minimum. The result is a poorly sampled source domain. We propose to abandon the condition of nonoverlapping shot...

Estimating primaries by sparse inversion and application to near-offset data reconstruction

Accurate removal of surface-related multiples remains a challenge in many cases. To overcome typical inaccuracies in current multiple-removal techniques, we have developed a new primary-estimation method: estimation of primaries by sparse inversion (EPSI). EPSI is based on the same primary-multiple model as surface-related multiple elimination ...

Assessing estimated velocity-depth models: Finding error bars in tomographic inversion

In conventional migration velocity analysis methods, a velocity model is estimated that results in flattened events in common-image gathers. However, after this process, no information is available on the accuracy of this velocity model. A statistical analysis of velocity-model parameters is very difficult because of the integrated nature of the...

Adaptive curvelet-domain primary-multiple separation

In many exploration areas, successful separation of primaries and multiples greatly determines the quality of seismic imaging. Despite major advances made by surface-related multiple elimination (SRME), amplitude errors in the predicted multiples remain a problem. When these errors vary for each type of multiple in different ways (as a function...