Data-driven internal multiple elimination applications using imperfectly sampled reflection data

We consider reflection data that have been subsampled by 70% and use Point-Spread-Functions to reconstruct the original data. The subsampled, original and reconstructed reflection data are used to image the medium of interest with the Marchenko method. The image obtained using the subsampled data shows artifacts caused by internal multiples,...

Obtaining angle-dependent reflectivity using the Marchenko redatuming method

When reflection images are studied, often only the zero-offset reflectivity is considered, however, taking into account the angle-dependent reflectivity can add additional information about the subsurface. This additional information can be used to extract the properties of the subsurface using amplitude variation with offset (AVO) analysis....

An overview of Marchenko methods

Since the introduction of the Marchenko method in geophysics, many variants have been developed. Using a compact unified notation, we review redatuming by multidimensional deconvolution and by double focusing, virtual seismology, double dereverberation and transmission-compensated Marchenko multiple elimination, and discuss the underlying...

Green's theorem in time-reversal acoustics, back propagation and source-receiver redatuming: A tutorial

Time-reversal acoustics, seismic interferometry, back propagation, source-receiver redatuming and imaging by double focusing are all based in some way or another on Green's theorem. An implicit assumption for all these methods is that data are available on a closed boundary, a condition that is never met in geophysical practice. As a...

Monitoring induced distributed double-couple sources using Marchenko-based virtual receivers

Forecasting induced seismicity responses for field data is difficult if no detailed model of the subsurface is available, which generally is the case. As an alternative, reflection data of the subsurface and a non-detailed background model can be used in the Marchenko method to obtain virtual receivers in the subsurface. By employing homogeneous...

A single-sided representation for the homogeneous Green's function, accounting for all multiples

Marchenko imaging is a novel imaging technique that is capable to retrieve images from single-sided reflection measurements free of artefacts related to internal multiples (e.g. Behura et al., 2014; Broggini et al., 2012). An essential ingredient of Marchenko imaging is the so-called focusing function which can<br/>be retrieved from reflection...

Marchenko method for monitoring induced seismicity with virtual receivers

The Marchenko method can be used to retrieve Green’s functions (including multiple scattering) between virtual sources in the subsurface and physical receivers at the surface or virtual receivers in the subsurface. Here we discuss a variant of the Marchenko method which retrieves the response between physical sources and virtual receivers in the...

Virtual seismology: from hydrocarbon reservoir imaging to induced earthquake monitoring

Recent developments in exploration seismology have enabled the creation of virtual sources and/or virtual receivers in the subsurface from reflection measurements at the earth's surface. Unlike in seismic interferometry, no physical instrument (receiver or source) is needed at the position of the virtual source or receiver. Moreover, no detailed...

Q‐factor Estimation and Redatuming in a Lossy Medium Using the Marchenko Equation

Marchenko Imaging is a new technology in geophysics, which enables us to retrieve Green's functions at any point in the subsurface having only reflection data. One of the assumptions of the Marchenko method is that the medium is lossless. One way to circumvent this assumption is to find a compensation parameter for the lossy reflection series so...

Decomposition of the Green's function using the Marchenko equation

The Marchenko equation can be used to retrieve the Green’s function at depth as a full function or decomposed into its upand downgoing parts. We show that the equation can be rewritten to create a decomposition scheme that can decompose a full wavefield, that was recorded at depth, into its up- and downgoing parts. We show that this can be done...