English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Marchenko algorithms retrieve the wavefields excited by virtual sources inthe subsurface, these are the Green's functions consisting of the primary andmultiple reflected waves. The requirements for these algorithms are the same asfor conventional imaging algorithms; they need an estimate of the velocitymodel and the recorded reflected waves. We investigate the dependence of theretrieved Green's functions using the Marchenko equation on the backgroundvelocity model and address the question: ``How well do we need to know thevelocity model for accurate Marchenko focusing?". We present three differentbackground velocity models and compare the Green's functions retrieved usingthese models. We show that these retrieved Green's functions using theMarchenko equation give correlation coefficients with the exact Green'sfunction larger than 90% on average except near the edges of the receiveraperture. We also examine the presence of refracted waves in the retrievedGreen's function. We show with a numerical example that the Marchenko focusingalgorithm produces refracted waves only if the initial velocity model used forthe iterative scheme is sufficiently detailed to model the refracted waves.

The role of the background velocity model for the Marchenko focusing of reflected and refracted waves