关键词 :
permeability, porosity, stoneley wave, nuclear magnetic logging, big data
Abstract:
Permeability is one of the important and difficult to accurately calculate reservoir parameters. At present, the evaluation of permeability logging mainly has four types of methods, namely: permeability evaluation based on porosity-permeability relationship, permeability evaluation based on nuclear magnetic resonance logging, permeability evaluation based on Stoneley wave measurement, and permeability evaluation based on big data and artificial intelligence. Through the analysis of the applicability of the above methods, it was found that the wellbore Stoneley wave is closely related to the fluidity of fluid in the reservoir pore space and has a significant advantage in permeability evaluation. However, at present the permeability logging evaluation faces great challenges due to three reasons: the theoretical and experimental difficulty of determining permeability parameters themselves, the increasing complexity of evaluation objects, and the lack of equipment that can be used for continuous permeability measurement underground. This article points out that promoting the research on the theory, methods, and techniques of Stoneley wave permeability evaluation and constructing a new permeability evaluation technology system centered on Stoneley wave measurement is the development direction of the new generation logging technology.
Key words:
permeability; porosity; stoneley wave; nuclear magnetic logging; big data
收稿日期: 2023-08-30
PACS:
基金资助:中国石油天然气集团公司“十四五”测井基础前沿研究项目(2022DJ3908) 资助
通讯作者:
ln@petrochina.com.cn
引用本文:
李宁, 王克文, 武宏亮, 冯周, 刘鹏, 李雨生. 渗透率测井评价:现状及发展方向. 石油科学通报, 2023, 04: 432-444 LI Ning, WANG Kewen, WU Hongliang, FENG Zhou, LIU Peng, LI Yusheng. Permeability logging evaluation: Current status and development directions. Petroleum Science Bulletin, 2023, 04: 432-444.