A Weighted Metric for Semi-blind Seismic Data Quality Assessment

Hilal Nuha, Bo Liu, M. Mohandes*, Ali Al-Shaikhi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Seismic data may undergo many types of distortions. However, the effect of distortion on raw data may not be apparent until the end of the standard processing of seismic reflection data. This paper presents a semi-blind metric for seismic data quality assessment, namely weighted normalized mean squared error (wNMSE). A weighting scheme is utilized on the data to shift more emphasis on the samples that are received later. Compared with conventional metrics, the proposed metric exhibits a higher correlation to the signal quality after standard processing steps for all tested noise types. This high correlation indicates that our proposed metric is suitable to quantify stacked seismic trace distortion level.

Original languageEnglish
Title of host publicationAdvances in Geophysics, Tectonics and Petroleum Geosciences - Proceedings of the 2nd Springer Conference of the Arabian Journal of Geosciences CAJG-2, Tunisia 2019
EditorsMustapha Meghraoui, Narasimman Sundararajan, Santanu Banerjee, Klaus-G. Hinzen, Mehdi Eshagh, François Roure, Helder I. Chaminé, Said Maouche, André Michard
PublisherSpringer Nature
Pages265-268
Number of pages4
ISBN (Print)9783030730253
DOIs
StatePublished - 2022

Publication series

NameAdvances in Science, Technology and Innovation
ISSN (Print)2522-8714
ISSN (Electronic)2522-8722

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Mean squared error
  • Quality assessment
  • Seismic data

ASJC Scopus subject areas

  • Architecture
  • Renewable Energy, Sustainability and the Environment
  • Environmental Chemistry

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