物探与化探2024，Vol.48Issue(4)：1025-1036,12.DOI:10.11720/wtyht.2024.1303
基于随机森林的火山岩岩性测井识别
Log-based lithology identification of volcanic rocks using random forest method:A case study of Carboniferous strata in the Dixi area,Junggar Basin
摘要
Abstract
The accurate lithologyidentification of volcanic rocksserves as a significant foundation for the efficient exploration and exploi-tation of volcanic reservoirs.However,volcanic reservoirs exhibit intricate lithologies,longitudinalmultistagesuperimposition,and fast transverse phase transition,which reduce the accuracy of crossplots in lithologyidentification ofvolcanic reservoirs.Based on the optimal parameter combination of the model determined through grid search and orthogonal experiments,this study quantitatively evaluatedthe effects of conventional log curves on the lithologyidentification of volcanic rocks.Withthe natural gamma ray,compensated neutron,sonic interval transit time,and formation resistivity as lithologic indicators,this study builtan intelligent model for the lithology identifi-cation of Carboniferous volcanic rocks in the Dixi area in the Junggar Basin using therandom forest method.This study identified the li-thologies of thecored intervalswith a cumulative thickness of 870 m infive cored wells in the study area,with the coincidence ratesof the identification results with thin section identification results and core description resultsreaching 76.67％and 85.98％,respectively.This suggestssignificant identification effects.Therefore,this studysets the stagefor the fine-scale evaluation of volcanic reservoirs in the study area.关键词
随机森林/岩性识别/火山岩/机器学习Key words
random forest/lithology identification/volcanic rock/machine learning分类
天文与地球科学引用本文复制引用
尚亚洲,张兆辉,许多年,赵雯雯,陈华勇,韩海波..基于随机森林的火山岩岩性测井识别[J].物探与化探,2024,48(4):1025-1036,12.基金项目
新疆维吾尔自治区"天池英才"计划项目(51052300560) （51052300560）
新疆大学博士启动基金项目(620322016) （620322016）
