A precise and refined identification method for carbonate bioreefs and prograding bodies guided by knowledge graph.

Cun Yang, Xiang-Ye Zhang, He Meng, Yue-Ming Ye, Xiang-Yu Guo, Yue Dong, Xingmiao Yao
{"title":"A precise and refined identification method for carbonate bioreefs and prograding bodies guided by knowledge graph.","authors":"Cun Yang, Xiang-Ye Zhang, He Meng, Yue-Ming Ye, Xiang-Yu Guo, Yue Dong, Xingmiao Yao","doi":"10.1190/int-2023-0032.1","DOIUrl":null,"url":null,"abstract":"Carbonate bioreefs formations serve as crucial hydrocarbon reservoirs, and their accurate identification bears significant implications for oil and gas exploration. Moreover, the precise and refined delineation of prograding body structures aids in the comprehensive analysis of stratigraphic geological configurations. We propose the Knowledge Graph and Geological Strata Interpolation Constraints (KGGSIC) model for the intricate identification of carbonate bioreefs and prograding bodies structures. Furthermore, we assess the KGGSIC-Unet architecture we propose on Dengying Formation Sections 3-4 carbonate bioreefs and prograding bodies in the Moxi area of the Sichuan Basin. Experimental results indicate that the KGGSIC enhances the predictive performance of the U-Net and realizes the precise and refined segmentation of carbonate bioreefs and prograding bodies structures. Additionally, through a meticulous geological study of the area, we synthesize the two-dimensional profile identification results to achieve the precise and refined identification of carbonate bioreefs and prograding bodies.","PeriodicalId":502519,"journal":{"name":"Interpretation","volume":"2008 12","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Interpretation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1190/int-2023-0032.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Carbonate bioreefs formations serve as crucial hydrocarbon reservoirs, and their accurate identification bears significant implications for oil and gas exploration. Moreover, the precise and refined delineation of prograding body structures aids in the comprehensive analysis of stratigraphic geological configurations. We propose the Knowledge Graph and Geological Strata Interpolation Constraints (KGGSIC) model for the intricate identification of carbonate bioreefs and prograding bodies structures. Furthermore, we assess the KGGSIC-Unet architecture we propose on Dengying Formation Sections 3-4 carbonate bioreefs and prograding bodies in the Moxi area of the Sichuan Basin. Experimental results indicate that the KGGSIC enhances the predictive performance of the U-Net and realizes the precise and refined segmentation of carbonate bioreefs and prograding bodies structures. Additionally, through a meticulous geological study of the area, we synthesize the two-dimensional profile identification results to achieve the precise and refined identification of carbonate bioreefs and prograding bodies.
以知识图谱为指导的碳酸盐生物礁和原生体精确精细识别方法。
碳酸盐岩生物礁地层是重要的碳氢化合物储层,准确识别它们对油气勘探具有重要意义。此外,精确、精细地划分渐变体结构有助于全面分析地层地质构造。我们提出了知识图谱和地层插值约束(KGGSIC)模型,用于复杂识别碳酸盐岩生物礁和原生体结构。此外,我们还在四川盆地巫溪地区的登瀛组 3-4 段碳酸盐岩生物礁和原生体上评估了我们提出的 KGGSIC-Unet 结构。实验结果表明,KGGSIC提高了U-Net的预测性能,实现了对碳酸盐岩生物礁和原生体结构的精确和精细划分。此外,通过对该地区细致的地质研究,我们综合了二维剖面识别结果,实现了碳酸盐岩生物礁和原生体的精确精细识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信