Velocity-independent Marchenko focusing in time- and depth-imaging domains for media with mild lateral heterogeneity

Sripanich, Yanadet; Vasconcelos, Ivan; Wapenaar, Kees

doi:10.1190/geo2019-0059.1

Cited by 4 publications

(3 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hence, we can effectively retrieve Green's functions at a desired (intercept) time, even in absence of velocity information [2]. A velocity model is only required to convert intercept times into depths, akin to acoustic Marchenko imaging [37]. An important observation in this context is that the construction of a virtual P-wave source is intrinsically decoupled from the construction of a virtual S-wave source in our formalism and both tasks may even be processed independently.…”

Section: Discussionmentioning

confidence: 99%

Marchenko Green's Function Retrieval in Layered Elastic Media from Two-Sided Reflection and Transmission Data

Neut¹,

Brackenhoff²,

Meles³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

By solving a Marchenko equation, Green's functions at an arbitrary (inner) depth level inside an unknown elastic layered medium can be retrieved from single-sided reflection data, which are to be collected at the top of the medium. So far, an exact solution could only be obtained if the medium obeys stringent monotonicity conditions and if all forward-scattered (non-converted and converted) transmissions between the acquisition level and the inner depth level are known a-priori. We introduce an alternative Marchenko equation by revising the window operators that are applied in its derivation. We also introduce an auxiliary equation for transmission data, which are to be collected at the bottom of the medium, and a coupled equation, which is based on both reflection and transmission data. We show that the joint system of the Marchenko equation, the auxiliary equation and the coupled equation can be succesfully inverted when broadband reflection and transmission data are available. This results in a novel methodology for elastodynamic Green's function retrieval from two-sided data. Apart from these data, our approach requires P- and S-wave transmission times between the inner depth level and the top of the medium, as well as two angle-dependent amplitude scaling factors, which can be estimated from the data by enforcing energy conservation.

show abstract

Section: Discussionmentioning

confidence: 99%

Marchenko Green's Function Retrieval in Layered Elastic Media from Two-Sided Reflection and Transmission Data

Neut¹,

Brackenhoff²,

Meles³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Hence, we can effectively retrieve Green's functions at a desired (intercept) time, even in the absence of velocity information [2]. A velocity model is only required to convert intercept times into depths, akin to acoustic Marchenko imaging [45]. An important observation in this context is that the construction of a virtual P-wave source is intrinsically decoupled from the construction of a virtual S-wave source in our formalism and both tasks may even be processed independently.…”

Section: Discussionmentioning

confidence: 99%

Marchenko Green’s Function Retrieval in Layered Elastic Media from Two-Sided Reflection and Transmission Data

et al. 2022

Self Cite

View full text Add to dashboard Cite

By solving a Marchenko equation, Green’s functions at an arbitrary (inner) depth level inside an unknown elastic layered medium can be retrieved from single-sided reflection data, which are collected at the top of the medium. To date, it has only been possible to obtain an exact solution if the medium obeyed stringent monotonicity conditions and if all forward-scattered (non-converted and converted) transmissions between the acquisition level and the inner depth level were known a priori. We introduce an alternative Marchenko equation by revising the window operators that are applied in its derivation. We also introduce an auxiliary equation for transmission data, which are collected at the bottom of the medium, and a coupled equation, which is based on both reflection and transmission data. We show that the joint system of the Marchenko equation, the auxiliary equation and the coupled equation can be succesfully inverted when broadband reflection and transmission data are available. This results in a novel methodology for elastodynamic Green’s function retrieval from two-sided data. Apart from these data, our approach requires P- and S-wave transmission times between the inner depth level and the top of the medium, as well as two angle-dependent amplitude scaling factors, which can be estimated from the data by enforcing energy conservation.

show abstract

“…Ravasi et al (2016), Jia et al (2018), Staring et al (2018), Pereira et al (2019), andMildner et al (2019) apply the Marchenko method successfully on field data. Sripanich et al (2019) derive a method that can estimate initial focusing functions from data and does not rely on a velocity model for mildly varying media. Mildner et al (2019) develop a method to estimate a source wavelet from the Marchenko focusing functions that enables more precise Marchenko redatuming.…”

Section: Introductionmentioning

confidence: 99%

Implementation of the Marchenko multiple elimination algorithm

et al. 2021

Self Cite

View full text Add to dashboard Cite

The Marchenko multiple elimination and transmission compensation schemes retrieve primary reflections in the two-way traveltime domain without model information or using adaptive subtraction. Both schemes are derived from projected Marchenko equations and similar to each other, but use different time-domain truncation operators. The Marchenko multiple elimination scheme retrieves a new dataset without internal multiple reflections. The transmission compensated Marchenko multiple elimination scheme does the same and additionally compensates for transmission losses in the primary reflections. Both schemes can be solved with an iterative algorithm based on a Neumann series. At each iteration, a convolution or correlation between the projected focusing function and the measured reflection response are performed and after each convolution or correlation, a truncation in the time domain is applied. After convergence, the resulting projected focusing function is used for retrieving the transmission compensated primary reflections and the projected Green’s function is used for the physical primary reflections. We demonstrate that internal multiples are removed by using time-windowed input data that only contain primary reflections. We evaluate both schemes in detail and develop an iterative implementation that reproduces the presented numerical examples. The software is part of our open-source suite of programs and fits into the Seismic Unix software suite of the Colorado School of Mines.

show abstract

Velocity-independent Marchenko focusing in time- and depth-imaging domains for media with mild lateral heterogeneity

Cited by 4 publications

References 52 publications

Marchenko Green's Function Retrieval in Layered Elastic Media from Two-Sided Reflection and Transmission Data

Marchenko Green's Function Retrieval in Layered Elastic Media from Two-Sided Reflection and Transmission Data

Marchenko Green’s Function Retrieval in Layered Elastic Media from Two-Sided Reflection and Transmission Data

Implementation of the Marchenko multiple elimination algorithm

Contact Info

Product

Resources

About