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.
|Title of host publication||Advances in Geophysics, Tectonics and Petroleum Geosciences - Proceedings of the 2nd Springer Conference of the Arabian Journal of Geosciences CAJG-2, Tunisia 2019|
|Editors||Mustapha Meghraoui, Narasimman Sundararajan, Santanu Banerjee, Klaus-G. Hinzen, Mehdi Eshagh, François Roure, Helder I. Chaminé, Said Maouche, André Michard|
|Number of pages||4|
|State||Published - 2022|
|Name||Advances in Science, Technology and Innovation|
Bibliographical noteFunding Information:
Acknowledgements This work is supported by the Center for Energy and Geo Processing (CeGP) at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia, under Project GTEC1801.
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
- Mean squared error
- Quality assessment
- Seismic data
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Environmental Chemistry