地球与行星物理论评（中英文）2024，Vol.55Issue(4)：416-427,12.DOI:10.19975/j.dqyxx.2023-047
岩性预测综合地球物理解释方法综述
Review of lithology prediction and comprehensive geophysical interpretation methods
摘要
Abstract
The primary objective of geophysical research is the exploration of underground structures and to serve as a valuable tool for geological interpretation.The formation structure and properties can be determined by analyzing the physical properties of the underground medium reflected by geophysical data,such as density,velo-city,magnetic susceptibility,resistivity,and more.Given the numerous solutions of a single geophysical method,comprehensive geophysical interpretation is currently a feasible and effective approach.This study explores litho-logy prediction,providing a summary of the basic principles and steps of comprehensive geophysical interpretation methods for lithology prediction.Additionally,it outlines the main technical methods of comprehensive lithology prediction involving two kinds of technical routes:knowledge-driven and data-driven.The knowledge-driven meth-od uses prior information.It is simple,direct,and easy to understand,but has weak adaptability to the complexity and high dimension data.The data-driven method employs a mathematical statistics strategy to explore the relation-ship between data and has a robust capacity to adapt to complex scenarios.In solving practical problems,the super-vised machine learning method,based on sufficient rock physical properties research,not only incorporates prior knowledge but also maximizes its internal data exploration ability.It can enhance the accuracy of lithology predic-tion and interpretation,better establish the corresponding relationship between geophysical and geological informa-tion,and support the exploration needs of resources and energy.关键词
综合地球物理解释/岩性预测/知识驱动与数据驱动/机器学习Key words
comprehensive geophysical interpretation/lithology prediction/knowledge-driven and data-driven/machine learning分类
地球科学引用本文复制引用
路书鹏,徐亚,张倩文,褚伟..岩性预测综合地球物理解释方法综述[J].地球与行星物理论评（中英文）,2024,55(4):416-427,12.基金项目
国家自然科学基金资助项目(92262303,42074092) （92262303,42074092）
中国科学院青年创新促进会资助项目(2016064)Supported by the National Natural Science Foundation of China(Grant Nos.92262303,42074092),and the Youth Innovation Pro-motion Association of Chinese Academy of Sciences(Grant No.2016064) （2016064）
