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CORRECTION article
Front. Earth Sci. , 26 January 2024
Sec. Geoinformatics
Volume 12 - 2024 | https://doi.org/10.3389/feart.2024.1366700
This article is a correction to:
Research on neural network prediction method for upgrading scale of natural gas reserves
A Corrigendum on
Research on neural network prediction method for upgrading scale of natural gas reserves
by Zhan W, Li H, Wu X, Zhang J, Liu C and Zhang D (2023). Front. Earth Sci. 11:1253495. doi: 10.3389/feart.2023.1253495
In the published article, there was an error in Figure 1 Natural gas exploration results in the Sichuan Basin. After communicating with Southwest Oil Company, it was found that there was an error in the distribution of proven reserves in Figure 1, and the actual distribution of proven reserves cannot be presented to readers, which may affect their reading experience. The preliminary confirmed reserves and confirmed reserves in yellow and green have been removed from the figure. The corrected Figure 1 and its caption appear below.
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by Sthe publisher.
Keywords: natural gas in sichuan basin, reserve upgrade, cluster analysis, analytic hierarchy process, neural network prediction
Citation: Zhan W, Li H, Wu X, Zhang J, Liu C and Zhang D (2024) Corrigendum: Research on neural network prediction method for upgrading scale of natural gas reserves. Front. Earth Sci. 12:1366700. doi: 10.3389/feart.2024.1366700
Received: 07 January 2024; Accepted: 15 January 2024;
Published: 26 January 2024.
Edited and reviewed by:
Yubing Liu, China University of Mining and Technology, ChinaCopyright © 2024 Zhan, Li, Wu, Zhang, Liu and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Chenxi Liu, MjAyMjIwMDIxMDMzQHN0dS5jcXUuZWR1LmNu
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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