海洋地质与第四纪地质2024，Vol.44Issue(6)：25-33,9.DOI:10.16562/j.cnki.0256-1492.2024092401
南海天然气水合物智能识别方法与应用
Intelligent identification and application of gas hydrate in South China Sea
摘要
Abstract
Gas hydrate is an important ideal energy source,with advantages of high energy,large reserves,wide distribution,and shallow burial.Accurate identification of gas hydrate reservoirs and estimation of hydrate saturation are the prerequisite for the application of gas hydrate resources.This study focuses on the difficult issues of hydrate identification,combining the interdisciplinary technologies of oceanology,geology,and artificial intelligence.Effective methods of hydrate-bearing strata identification were proposed based on the geophysical attributes,and verified in the Dongsha area of South China Sea.Machine-learning algorithms were used to analyze whether the sediment contains gas hydrates.Several commonly used machine-learning algorithms were selected,including random forest,Bagging,AdaBoost,and KNN;and data were analyzed based on the P-wave velocity and density attributes that are more sensitive to hydrate existence.The parameters of different algorithms were trained and optimized,and the effects of different algorithms on the identification and classification were compared.All these algorithms could do good on whether there is hydrate in the sediment,of which KNN algorithm was shown the best.Therefore,machine-learning-based methods could improve the identification accuracy of gas hydrate.关键词
水合物/识别/机器学习/地震属性/南海Key words
hydrate/identification/machine learning/seismic attributes/South China Sea分类
海洋科学引用本文复制引用
田冬梅,杨胜雄,刘鑫,李沅衡,胡广,曹荆亚,周军明,邓雨恬..南海天然气水合物智能识别方法与应用[J].海洋地质与第四纪地质,2024,44(6):25-33,9.基金项目
国家自然科学基金国家重大科研仪器研制项目"海底地震与电磁同步探测系统关键技术及验证样机"(42327901) （42327901）
国家自然科学基金项目"南海北部高富集天然气水合物储层特征与成藏控制机理研究"(U2244224) （U2244224）
广州市基础与应用基础研究项目"基于地震属性海域天然气水合物识别方法研究"(2023A04J0916) （2023A04J0916）
