基于沉积微相特征挖掘的随机森林岩石相测井识别方法——以新场地区须家河组二段致密砂岩为例

doi:10.11720/wtyht.2024.0180

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Abstract

Tight sandstones serve as significant oil and gas reservoirs.Their lithofacies identification can assist in further understanding the developmental characteristics of reservoirs.Combining core observations with log data processing,this study analyzed the lithofacies and sedimentary microfacies characteristics of tight sandstones in the Xinchang area and the internal relationships between lithofacies and sedimentary microfacies.Moreover,it constructed a random forest classification model with geological implications through data mining of sedimentary microfacies characteristics.The results show that:(1)Tight sandstones in the Xinchang area can be classified into seven typical lithofacies,including mudstone,siltstone with ripple lamination,massive fine sandstone,fine sandstone with parallel bedding,massive medium- to coarse-grained sandstone,and medium- to coarse-grained sandstone with parallel/cross bedding;(2)The sedimentary microfacies in the Xinchang area consist primarily of subaqueous distributary channel,subaqueous distributary bay,river-mouth bar,and prodeltaic mud,which are closely associated with the sedimentation of lithofacies;(3)In the classification model,the relative centroid(RM),root mean square deviation(GS),average median(AM),and average slope(M) of the gamma ray(GR) curve can be used as the characteristic parameters of sedimentary microfacies to increase the number of characteristics in the dataset;(4)Considering the characteristics of sedimentary microfacies,especially the energy and turbulence of water bodies,can significantly enhance the performance of the random forest classification model.Overall,the results of this study provide a novel approach for lithofacies identification using machine learning methods and a significant reference for oil and gas exploration in tight sandstones.

Key words： sedimentary microfacies random forest lithofacies Xujiahe Formation tight sandstone

Received: 25 April 2024 Published: 21 October 2024

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	Articles by authors
	Xiao-Long HE
	Bing ZHANG
	Kai YANG
	Yi-Fan HE
	Zhuo LI

Cite this article:

Xiao-Long HE,Bing ZHANG,Kai YANG, et al. A log-based lithofacies identification method based on random forest and sedimentary microfacies characteristics:A case study of tight sandstones in the second member of the Xujiahe Formation in the Xinchang area[J]. Geophysical and Geochemical Exploration, 2024, 48(5): 1337-1347.

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https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2024.0180 OR https://www.wutanyuhuatan.com/EN/Y2024/V48/I5/1337

Map of structural position(a) and comprehensive columnar section(b) of the Xujiahe Formation in the Xinchang area,Western Sichuan Basin

Typical sandstone sedimentary structure of the second member of Xujiahe Formation in the Western Sichuan depression

Main sedimentary microfacies of the Xujiahe Formation in the Xinchang area

Decision tree classification diagram

Matrix plot of petrophysical logging parameters associated with rock facies

Setting of hyperparameter grid search space

Distribution of F₁ scores from grid search and hyperparameter optimization

Random forest classification report(including sedimentary microfacies related parameters)

Confusion matrix of classification results

SHAP model importance analysis(a) and CL562 well lithofacies prediction results(b)

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