Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Dec 16, 2025

Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging
04:54

Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging

Published on: June 16, 2023

3.5K

Tutorial: unified 1D inversion of the acoustic reflection response.

Evert Slob1, Kees Wapenaar1, Sven Treitel2

  • 1Department of Geoscience and Engineering Delft University of Technology P.O. Box 5048 Delft GA 2600 The Netherlands.

Geophysical Prospecting
|July 3, 2020
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

Impulse Response01:17

Impulse Response

621
The impulse response is the system's reaction to an input impulse. In an RC circuit, the voltage source is the input, and the capacitor's voltage is the output. The system's state and output response before and after input excitation are distinctly defined.
Kirchhoff's law forms an input signal equation, with the capacitor's current and voltage providing the output. Substituting the current and dividing by RC yields a differential equation. The output for an impulse input is the impulse...
621
Deconvolution01:20

Deconvolution

469
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
469
Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

582
Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
Spin decoupling is usually achieved by...
582
Echo01:06

Echo

813
The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case,...
813
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

729
In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
729
Standing Waves in a Cavity01:28

Standing Waves in a Cavity

1.3K
A household microwave and lasers are examples of standing electromagnetic waves in a cavity. When two conducting metal plates are placed parallel at the nodal planes, it creates a cavity where standing waves are formed. The cavity between the two planes is analogous to a stretched string held at the points x = 0 and x = L. Here, the distance 'L' between the two planes must be an integer multiple of half of the wavelength. The wavelengths that satisfy this condition are given by:
1.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

On the relation between time-reversed acoustics and Green's function retrieval in space-variant and in time-variant materials.

The Journal of the Acoustical Society of America·2026
Same author

Erratum: Wave-field representations with Green's functions, propagator matrices, and Marchenko-type focusing functions [J. Acoust. Soc. Am. 151, 587-608 (2022)].

The Journal of the Acoustical Society of America·2023
Same authorSame journal

Data-driven retrieval of primary plane-wave responses.

Geophysical prospecting·2020
Same authorSame journal

Three-dimensional Marchenko internal multiple attenuation on narrow azimuth streamer data of the Santos Basin, Brazil.

Geophysical prospecting·2020
Same author

Marchenko-Based Target Replacement, Accounting for All Orders of Multiple Reflections.

Journal of geophysical research. Solid earth·2018
Same author

Virtual acoustics in inhomogeneous media with single-sided access.

Scientific reports·2018

This study combines recursive and Marchenko-type acoustic inversion methods for 1D layered media. The integrated approach enables non-recursive, target-oriented seismic inversion, even with noisy data.

Area of Science:

  • Geophysics
  • Seismic Exploration
  • Acoustic Inversion

Background:

  • One-dimensional acoustic inversion determines impedance from travel time.
  • Inverting reflection response is a linear problem, with known recursive methods.
  • Marchenko-based methods offer non-recursive impedance retrieval but need zero-frequency reflection data.

Purpose of the Study:

  • To develop a non-recursive, target-oriented seismic inversion scheme.
  • To combine recursive and Marchenko-type methods for improved inversion.
  • To accurately determine layer properties in horizontally layered media.

Main Methods:

  • Utilizing a fundamental wave field computed from reflection response.
  • Integrating recursive (top-down/bottom-up) and Marchenko-type inversion techniques.
Keywords:
acousticinversionnumerical study

More Related Videos

Evanescent Field Based Photoacoustics: Optical Property Evaluation at Surfaces
10:21

Evanescent Field Based Photoacoustics: Optical Property Evaluation at Surfaces

Published on: July 26, 2016

12.0K
Hemi-laryngeal Setup for Studying Vocal Fold Vibration in Three Dimensions
10:13

Hemi-laryngeal Setup for Studying Vocal Fold Vibration in Three Dimensions

Published on: November 25, 2017

11.3K

Related Experiment Videos

Last Updated: Dec 16, 2025

Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging
04:54

Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging

Published on: June 16, 2023

3.5K
Evanescent Field Based Photoacoustics: Optical Property Evaluation at Surfaces
10:21

Evanescent Field Based Photoacoustics: Optical Property Evaluation at Surfaces

Published on: July 26, 2016

12.0K
Hemi-laryngeal Setup for Studying Vocal Fold Vibration in Three Dimensions
10:13

Hemi-laryngeal Setup for Studying Vocal Fold Vibration in Three Dimensions

Published on: November 25, 2017

11.3K
  • Applying an integral over the Marchenko equation solution for impedance retrieval.
  • Main Results:

    • A novel non-recursive inversion scheme effective with finite-frequency bandwidth was developed.
    • The combined method accurately retrieves layer thickness, wave velocity, and density ratios.
    • Statistical analysis confirmed robust performance on noisy synthetic data.

    Conclusions:

    • The combined inversion method provides a powerful tool for target-oriented seismic analysis.
    • This approach enhances the accuracy of geophysical parameter estimation in layered media.
    • The method demonstrates resilience and effectiveness even with the presence of noise.