Approximation of seismic velocities from the spectrum of weighted graphs

Monther Rashed Alfuraidan; Abdullatif Al-Shuhail; Sherif M. Hanafy; Ibrahim O. Sarumi

doi:10.1007/s13137-023-00214-z

Approximation of seismic velocities from the spectrum of weighted graphs

Monther Rashed Alfuraidan, Abdullatif Al-Shuhail, Sherif M. Hanafy, Ibrahim O. Sarumi^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy.

Original language	English
Article number	5
Journal	GEM - International Journal on Geomathematics
Volume	14
Issue number	1
DOIs	https://doi.org/10.1007/s13137-023-00214-z
State	Published - Dec 2023

Bibliographical note

Funding Information:
The authors appreciate funding of this research by the College of Petroleum Engineering and Geosciences in King Fahd University of Petroleum and Minerals through start-up grant number SF 18060.

Publisher Copyright:
© 2023, The Author(s).

Keywords

Graph spectral radius
Seismic migration
Seismic velocity
Weighted graph

ASJC Scopus subject areas

Modeling and Simulation
Earth and Planetary Sciences (all)

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10.1007/s13137-023-00214-z

Cite this

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title = "Approximation of seismic velocities from the spectrum of weighted graphs",

abstract = "Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy.",

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note = "Funding Information: The authors appreciate funding of this research by the College of Petroleum Engineering and Geosciences in King Fahd University of Petroleum and Minerals through start-up grant number SF 18060. Publisher Copyright: {\textcopyright} 2023, The Author(s).",

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AU - Hanafy, Sherif M.

AU - Sarumi, Ibrahim O.

N1 - Funding Information: The authors appreciate funding of this research by the College of Petroleum Engineering and Geosciences in King Fahd University of Petroleum and Minerals through start-up grant number SF 18060. Publisher Copyright: © 2023, The Author(s).

PY - 2023/12

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N2 - Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy.

AB - Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy.

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Approximation of seismic velocities from the spectrum of weighted graphs

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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