John Oluwadamilola Olutoki , Jian-guo Zhao , Numair Ahmed Siddiqui , Mohamed Elsaadany , AKM Eahsanul Haque , Oluwaseun Daniel Akinyemi , Amany H. Said , Zhaoyang Zhao
{"title":"Shear wave velocity prediction: A review of recent progress and future opportunities","authors":"John Oluwadamilola Olutoki , Jian-guo Zhao , Numair Ahmed Siddiqui , Mohamed Elsaadany , AKM Eahsanul Haque , Oluwaseun Daniel Akinyemi , Amany H. Said , Zhaoyang Zhao","doi":"10.1016/j.engeos.2024.100338","DOIUrl":null,"url":null,"abstract":"<div><p>Shear logs, also known as shear velocity logs, are used for various types of seismic analysis, such as determining the relationship between amplitude variation with offset (AVO) and interpreting multiple types of seismic data. This log is an important tool for analyzing the properties of rocks and interpreting seismic data to identify potential areas of oil and gas reserves. However, these logs are often not collected due to cost constraints or poor borehole conditions possibly leading to poor data quality, though there are various approaches in practice for estimating shear wave velocity. In this study, a detailed review of the recent advances in the various techniques used to measure shear wave (S-wave) velocity is carried out. These techniques include direct and indirect measurement, determination of empirical relationships between S-wave velocity and other parameters, machine learning, and rock physics models. Therefore, this study creates a collection of employed techniques, enhancing the existing knowledge of this significant topic and offering a progressive approach for practical implementation in the field.</p></div>","PeriodicalId":100469,"journal":{"name":"Energy Geoscience","volume":"5 4","pages":"Article 100338"},"PeriodicalIF":3.6000,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666759224000532/pdfft?md5=2c2cd98daeb3201a53158d6709e7981b&pid=1-s2.0-S2666759224000532-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Geoscience","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666759224000532","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
Shear logs, also known as shear velocity logs, are used for various types of seismic analysis, such as determining the relationship between amplitude variation with offset (AVO) and interpreting multiple types of seismic data. This log is an important tool for analyzing the properties of rocks and interpreting seismic data to identify potential areas of oil and gas reserves. However, these logs are often not collected due to cost constraints or poor borehole conditions possibly leading to poor data quality, though there are various approaches in practice for estimating shear wave velocity. In this study, a detailed review of the recent advances in the various techniques used to measure shear wave (S-wave) velocity is carried out. These techniques include direct and indirect measurement, determination of empirical relationships between S-wave velocity and other parameters, machine learning, and rock physics models. Therefore, this study creates a collection of employed techniques, enhancing the existing knowledge of this significant topic and offering a progressive approach for practical implementation in the field.
剪切测井又称剪切速度测井,用于各种类型的地震分析,如确定振幅变化与偏移(AVO)之间的关系以及解释多种类型的地震数据。这种测井仪是分析岩石性质和解释地震数据的重要工具,可用于确定潜在的油气储藏区域。然而,由于成本限制或井眼条件差,可能导致数据质量不高,尽管在实践中有各种估计剪切波速度的方法,但这些测井仪往往无法收集。本研究详细回顾了用于测量剪切波(S 波)速度的各种技术的最新进展。这些技术包括直接和间接测量、确定 S 波速度与其他参数之间的经验关系、机器学习和岩石物理模型。因此,本研究汇集了所使用的各种技术,丰富了这一重要课题的现有知识,并为该领域的实际应用提供了一种渐进的方法。