地质通报2025，Vol.44Issue(5)：935-948,14.DOI:10.12097/gbc.2024.06.016
基于SSMO-SSA-LGBM算法的致密砂岩储层岩性识别
Lithology identification of tight sandstone reservoirs based on SSMO-SSA-LGBM algorithm
摘要
Abstract
[Objective]Existing lithology logging identification methods face challenges of imbalanced lithology class processing and insufficient sensitivity when applied to tight sandstone reservoirs.[Methods]This study proposes the SSMO-SSA-LGBM model.First,the SVM-SMOTE oversampling algorithm(abbreviated as SSMO)is used to balance samples with fewer lithology data in the training set by generating synthetic samples.These synthetic samples are combined with the original training set to form a new training dataset for constructing the LightGBM(LGBM)model.Given the numerous hyperparameters in LGBM,the Sparrow Search Algorithm(SSA)is employed to optimize hyperparameters and obtain the optimal combination.The model is trained using logging data from the Yan 10 tight sandstone reservoir in the Huachi S Block,and compared with KNN,Adaboost,Random Forest,and other models.[Results]After SSMO balancing,the LGBM model exhibits enhanced recognition performance for minority lithology classes.The SSA algorithm achieves global optimization with fewer iterations,obtaining the optimal hyperparameters for LGBM.The SSMO-SSA-LGBM model demonstrates superior predictive performance,with lithology identification results on validation wells showing high consistency with core data.[Conclusions]The SSMO algorithm effectively mitigates the adverse effects of lithology class imbalance on prediction accuracy.The SSA algorithm efficiently identifies the optimal hyperparameter combination for LGBM through limited iterations,maximizing model performance.The proposed model achieves satisfactory application results in the Huachi S Block.关键词
SSMO-SSA-LGBM算法/非均衡数据/岩性识别/致密砂岩储层/甘肃华池Key words
SSMO-SSA-LGBM algorithm/imbalanced data/lithology recognition/tight sandstone reservoir/Huachi,Gansu分类
天文与地球科学引用本文复制引用
孙婧,赵军龙,张雨辰,金利睿,崔文洁,陈家鑫..基于SSMO-SSA-LGBM算法的致密砂岩储层岩性识别[J].地质通报,2025,44(5):935-948,14.基金项目
国家自然科学基金《压力-应力耦合对前陆冲断带深层—超深层碎屑岩储层异常高原生孔隙的保存机制研究》(批准号:42172164) （批准号:42172164）
