摘要
文章分析研究了油气测井中微弱信号识别检测方法,首先回顾了微弱信号检测的传统方法,指出传统方法在处理高噪声环境下的微弱信号时的局限性;其次,详细介绍了非线性系统理论中的混沌理论和随机共振理论;最后,探讨了这些先进理论在油气测井微弱信号检测中的具体应用。该研究对提升油气资源勘探和开发的效率和准确性具有重要的实践意义,为油气测井领域提供了一种新的微弱信号检测策略。
This paper analyzes and studies the weak signal detection methods in oil and gas logging.It begins by reviewing traditional methods of weak signal detection,highlighting their limitations in processing weak signals in high-noise environments.Subsequently,the paper provides a detailed introduction to chaos theory and stochastic resonance within the framework of nonlinear system theory,discussing their specific applications in the detection of weak signals in oil and gas logging.This study is of significant practical importance for enhancing the efficiency and accuracy of oil and gas resource exploration and development,offering a new strategy for weak signal detection in the field of oil and gas logging.
作者
杨进峰
刘凯轩
杨周礼
田怀谷
Yang Jinfeng;Liu Kaixuan;Yang Zhouli;Tian Huaigu(School of Computer Science,Xijing University,Xi’an 710123,China)
出处
《无线互联科技》
2024年第4期126-128,共3页
Wireless Internet Technology
关键词
微弱信号检测
油气测井
混沌理论
随机共振
weak signal detection
oil and gas logging
chaos theory
stochastic resonance
