[1] 戴金星,倪云燕,刘全有,等. 四川超级气盆地[J]. 石油勘探与开发,2021,48（6）：1081-1088.

Dai Jinxing, Ni Yunyan, Liu Quanyou, et al. Sichuan super gas basin in southwest China[J]. Petroleum Exploration and Development, 2021, 48(6): 1081-1088.
[2] 马新华,杨雨,文龙,等. 四川盆地海相碳酸盐岩大中型气田分布规律及勘探方向[J]. 石油勘探与开发,2019,46（1）：1-13.

Ma Xinhua, Yang Yu, Wen Long, et al. Distribution and exploration direction of medium-and large-sized marine carbonate gas fields in Sichuan Basin, SW China[J]. Petroleum Exploration and Development, 2019, 46(1): 1-13.
[3] 刘景东,刘光祥,韦庆亮,等. 四川盆地元坝地区飞仙关组二段滩相储层孔隙演化特征[J]. 中国石油大学学报（自然科学版）,2016,40（1）：10-17.

Liu Jingdong, Liu Guangxiang, Wei Qingliang, et al. Pore evolution characteristics of beach facies reservoir of Feixianguan Ⅱ member in Yuanba area, Sichuan Basin[J]. Journal of China University of Petroleum (Edition of Natural Science), 2016, 40(1): 10-17.
[4] 陈辉,郭海洋,徐祥恺,等. 四川盆地剑阁—九龙山地区长兴期与飞仙关期古地貌演化特征及其对礁滩体的控制[J]. 石油与天然气地质,2016,37（6）：854-861.

Chen Hui, Guo Haiyang, Xu Xiangkai, et al. Features of paleogeomorphological evolution and its control on reef flat composite in Changxing-Feixianguan Formation in Jiange-Jiulongshan region, the Sichuan Basin[J]. Oil & Gas Ge-ology, 2016, 37(6): 854-861.
[5] 蒋裕强,邓虹兵,易娟子,等. 开江—梁平海槽西侧飞仙关组不同类型鲕滩储层特征及其控制因素研究[J]. 特种油气藏,2020,27（1）：17-24.

Jiang Yuqiang, Deng Hongbing, Yi Juanzi, et al. Properties of different oolitic beach reservoirs in the Feixianguan Formation of Kaijiang-Liangping trough[J]. Special Oil & Gas Reservoirs, 2020, 27(1): 17-24.
[6] 胡忠贵,董庆民,李世临,等. 川东—渝北地区长兴组—飞仙关组礁滩组合规律及控制因素[J]. 中国石油大学学报（自然科学版）,2019,43（3）：25-35.

Hu Zhonggui, Dong Qingmin, Li Shilin, et al. Combination regularities of reef-beach and main controlling factors in Changxing-Feixianguan Formation of eastern Sichuan-northern Chongqing area[J]. Journal of China University of Petroleum, 2019, 43(3): 25-35.
[7] 赫云兰,付孝悦,刘波,等. 川东北飞仙关组鲕滩沉积与成岩对储集层的控制[J]. 石油勘探与开发,2012,39（4）：434-443.

He Yunlan, Fu Xiaoyue, Liu Bo, et al. Control of oolitic beaches sedimentation and diagenesis on reservoirs in Feixianguan Formation, northeastern Sichuan Basin[J]. Petroleum Exploration and Development, 2012, 39(4): 434-443.
[8] 赵文智,沈安江,胡素云,等. 中国碳酸盐岩储集层大型化发育的地质条件与分布特征[J]. 石油勘探与开发,2012,39（1）：1-12.

Zhao Wenzhi, Shen Anjiang, Hu Suyun, et al. Geological conditions and distributional features of large-scale carbonate reservoirs onshore China[J]. Petroleum Exploration and Development, 2012, 39(1): 1-12.
[9] 蒋裕强,周亚东,陈智雍,等. 川东地区台内洼地二叠系生物礁、滩沉积格局及勘探意义[J]. 天然气地球科学,2019,30（11）：1539-1550.

Jiang Yuqiang, Zhou Yadong, Chen Zhiyong, et al. Sedimentary pattern and exploration significance of Permian reefs and shoals in intra-platform depressions, eastern Sichuan Basin[J]. Natural Gas Geoscience, 2019, 30(11): 1539-1550.
[10] 刘建强,罗冰,谭秀成,等. 川东北地区飞仙关组台缘带鲕滩分布规律[J]. 地球科学：中国地质大学学报,2012,37（4）：805-814.

Liu Jianqiang, Luo Bing, Tan Xiucheng, et al. Distribution of marginal-platform oolitic shoal in Feixianguan Formation, northeast Sichuan, China[J]. Earth Science: Journal of China University of Geosciences, 2012, 37(4): 805-814.
[11] 郭彤楼. 川东北元坝地区长兴组—飞仙关组台地边缘层序地层及其对储层的控制[J]. 石油学报,2011,32（3）：387-394.

Guo Tonglou. Sequence strata of the platform edge in the Changxing and Feixianguan Formations in the Yuanba area, northeastern Sichuan Basin and their control on reservoirs[J]. Acta Petrolei Sinica, 2011, 32(3): 387-394.
[12] 谢增业,田世澄,单秀琴,等.川东北飞仙关组鲕滩天然气富集成藏特征及勘探前景[J].石油勘探与开发,2005,32(2)：31-34.

Xie Zengye, Tian Shicheng, Shan Xiuqin, et al. Features of gas accumulation and exploration foreground in oolitic reservoir of Feixianguan Formation in Sichuan Basin [J]. Petroleum Exploration and Development, 2005,32(2): 31-34.
[13] 邹才能,徐春春,汪泽成,等. 四川盆地台缘带礁滩大气区地质特征与形成条件[J]. 石油勘探与开发,2011,38（6）：641-651.

Zou Caineng, Xu Chunchun, Wang Zecheng, et al. Geological characteristics and forming conditions of the large platform margin reef-shoal gas province in the Sichuan Basin[J]. Petroleum Exploration and Development, 2011, 38(6): 641-651.
[14] 邹娟,杨迅,尹宏,等. 九龙山—剑阁地区长兴组、飞仙关组礁、滩储层特征及控制因素研究[J]. 天然气勘探与开发,2014,37（4）：1-7.

Zou Juan, Yang Xun, Yin Hong, et al. Characteristics of bioreef and shoal reservoirs in Changxing and Feixianguan Formations of Jiulongshan-Jiange area and their controlling factors[J]. Natural Gas Exploration and Development, 2014, 37(4): 1-7.
[15] 冯林杰,蒋裕强,刘菲,等. 川东地区开江—梁平海槽南段飞仙关组鲕滩储层特征及主控因素[J]. 石油学报,2021,42（10）：1287-1298.[

Feng Linjie, Jiang Yuqiang, Liu Fei, et al. Reservoir characteristics and main controlling factors of oolitic shoal reservoir in Feixianguan Formation in the southern part of Kaijiang-Liangping trough, eastern Sichuan Basin[J]. Acta Petrolei Sinica, 2021, 42(10): 1287-1298.
[16] 朱怡翔,石广仁. 火山岩岩性的支持向量机识别[J]. 石油学报,2013,34（2）：312-322.

Zhu Yixiang, Shi Guangren. Identification of lithologic characteristics of volcanic rocks by support vector machine[J]. Acta Petrolei Sinica, 2013, 34(2): 312-322.
[17]

Rosenblatt F. The perceptron: A probabilistic model for information storage and organization in the brain[J]. Psychological Review,1958, 65(6): 386-408.
[18] 赵彦超,吴春萍,吴东平. 致密砂岩气层的测井评价：以鄂尔多斯盆地大牛地山西组一段气田为例[J]. 地质科技情报,2003,22（4）：65-70.[

Zhao Yanchao, Wu Chunping, Wu Dongping. Logging evaluation to tight gas sandstone: A case study from the First member of Shanxi Formation in Daniudi gas pool, Ordos Basin, China[J]. Geological Science and Technology Information, 2003, 22(4): 65-70.
[19]

Ghiasi M M, Zendehboudi S, Mohsenipour A A. Decision tree-based diagnosis of coronary artery disease: CART model[J]. Computer Methods and Programs in Biomedicine, 2020, 192: 105400.
[20] 张俊玉,胡家豪,黄嵩. CART决策树方法在煤电厂节能降耗中的应用[J]. 控制与决策,2021,36（5）：1232-1238.

Zhang Junyu, Hu Jiahao, Huang Song. Application of CART decision tree model in reducing coal consumption in coal power plant[J]. Control and Decision, 2021, 36(5): 1232-1238.
[21] 陈平,徐星. 基于CART算法的带钢抗拉强度影响因素研究[J]. 控制工程,2015,22（2）：276-281.

Chen Ping, Xu Xing. Research of tensile strength of strip steel based on CART[J]. Control Engineering of China, 2015, 22(2): 276-281.
[22] 魏合理,陈秀红,戴聪明. 通用大气辐射传输软件（CART）及其应用[J]. 红外与激光工程,2012,41（12）：3360-3366.

Wei Heli, Chen Xiuhong, Dai Congming. Combined atmospheric radiative transfer (CART) model and its applications[J]. Infrared and Laser Engineering, 2012, 41(12): 3360-3366.
[23] 刘玉茹,赵成萍,臧军,等. CART分析及其在故障趋势预测中的应用[J]. 计算机应用,2017,37（增刊2）：57-59,73.

Liu Yuru, Zhao Chengping, Zang Jun, et al. Analysis of CART regression tree and its application in fault trend forecasting[J]. Journal of Computer Applications, 2017, 37(Suppl.2): 57-59, 73.
[24] 吴冠朋,黄伟,刘毅慧. CART算法在原发性肝癌放疗后HBV再激活的应用[J]. 生物信息学,2017,15（3）：164-170.

Wu Guanpeng, Huang Wei, Liu Yihui. Application of HBV reactivation in primary liver carcinoma after radiotherapy based on CART algorithm[J]. Chinese Journal of Bioinformatics, 2017, 15(3): 164-170.
[25] 王晓畅,张军,李军,等. 基于交会图决策树的缝洞体类型常规测井识别方法：以塔河油田奥陶系为例[J]. 石油与天然气地质,2017,38（4）：805-812.

Wang Xiaochang, Zhang Jun, Li Jun, et al. Conventional logging identification of fracture-vug complex types data based on crossplots-decision tree: A case study from the Ordovician in Tahe oilfield, Tarim Basin[J]. Oil & Gas Geology, 2017, 38(4): 805-812.
[26] 孙予舒,黄芸,梁婷,等. 基于XGBoost算法的复杂碳酸盐岩岩性测井识别[J]. 岩性油气藏,2020,32（4）：98-106.

Sun Yushu, Huang Yun, Liang Ting, et al. Identification of complex carbonate lithology by logging based on XGBoost algorithm[J]. Lithologic Reservoirs, 2020, 32(4): 98-106.
[27] 李洪奇,谭锋奇,许长福,等. 基于决策树方法的砾岩油藏岩性识别[J]. 测井技术,2010,34（1）：16-21.

Li Hongqi, Tan Fengqi, Xu Changfu, et al. Lithology identification of conglomerate reservoir based on decision tree method[J]. Well Logging Technology, 2010, 34(1): 16-21.
[28] Han J W, Kamber M. Data mining concepts and techniques[M]. 2nd ed. San Francisco: Morgan Kaufmann Publishers, 2006.
[29] Witten I H, Frank E. 数据挖掘：实用机器学习技术[M]. 董琳,邱泉,于晓峰,等译. 2版. 北京：机械工业出版社,2006.

Witten I H, Frank E. Data mining: practical machine learning tools and techniques[M]. Dong Lin, Qiu Quan, Yu Xiaofeng, et al, trans. 2nd ed. Beijing: China Machine Press, 2006.
[30] 李雄炎,周金昱,李洪奇,等. 复杂岩性及多相流体智能识别方法[J]. 石油勘探与开发,2012,39（2）：243-248.

Li Xiongyan, Zhou Jinyu, Li Hongqi, et al. Computational intelligent methods for predicting complex lithologies and multiphase fluids[J]. Petroleum Exploration and Development, 2012, 39(2): 243-248.
[31] Kohonen T. Self-organization and associative memory[M]. 3rd ed. Heidelberg: Springer, 1989.
[32]

Kohonen T. The self-organizing map[J]. Proceedings of the IEEE, 1990, 78(9): 1464-1480.
[33]

Shi G R, Zhou X X, Zhang G Y, et al. The use of artificial neural network analysis and multiple regression for trap quality evaluation: A case study of the northern Kuqa Depression of Tarim Basin in western China[J]. Marine and Petroleum Geology, 2004, 21(3): 411-420.
[34] 王俊,曹俊兴,尤加春. 基于GRU神经网络的测井曲线重构[J]. 石油地球物理勘探,2020,55（3）：510-520.

Wang Jun, Cao Junxing, You Jiachun. Reconstruction of logging traces based on GRU neural network[J]. Oil Geophysical Prospecting, 2020, 55(3): 510-520.
[35] 李霞,范宜仁,邓少贵,等. 自动划分层序单元的测井多尺度数据融合方法[J]. 石油勘探与开发,2009,36(2)：221-227.

Li Xia, Fan Yiren, Deng Shaogui, et al. Automatic demarcation of sequence stratigraphy using the method of well logging multiscale data fusion[J]. Petroleum Exploration and Development, 2009, 36(2): 221-227.
[36] 肖小玲,靳秀菊,张翔,等. 基于常规测井与电成像测井多信息融合的裂缝识别[J]. 石油地球物理勘探,2015,50（3）：542-547.

Xiao Xiaoling, Jin Xiuju, Zhang Xiang, et al. Fracture identification based on information fusion of conventional logging and electrical imaging logging[J]. Oil Geophysical Prospecting, 2015, 50(3): 542-547.
[37] 马陇飞,萧汉敏,陶敬伟,等. 基于梯度提升决策树算法的岩性智能分类方法[J]. 油气地质与采收率,2022,29（1）：21-29.

Ma Longfei, Xiao Hanmin, Tao Jingwei, et al. Intelligent lithology classification method based on GBDT algorithm[J]. Petroleum Geology and Recovery Efficiency, 2022, 29(1): 21-29.
[38]

Friedman J H. Greedy function approximation: A gradient boosting machine[J]. The Annals of Statistics, 2001, 29(5): 1189-1232.
[39] 王瑞妮. 基于流形学习和GBDT的异常流量检测方法[D]. 哈尔滨：哈尔滨工程大学,2020.

Wang Ruini. Anomaly traffic detection based on manifold learning and GBDT[D]. Harbin: Harbin Engineering University, 2020.
[40] 王焱. 基于随机梯度提升决策树的行人检测算法设计与实现[D]. 杭州：浙江大学,2017.

Wang Yan. Design and implementation of a pedestrian detection algorithm using s-GBDT[D]. Hangzhou: Zhejiang University, 2017.
[41] Nassif A B. Short term power demand prediction using stochastic gradient boosting[C]//5th international conference on electronic devices, systems and applications (ICEDSA). Ras Al Khaimah: IEEE, 2016: 1-4.
[42] 谢振平,孙桃. 自组织决策树的联想记忆在线学习模型[J]. 模式识别与人工智能,2017,30(1)：21-31.

Xie Zhenping, Sun Tao. Online associative memory model based on self-organizing decision tree[J]. Pattern Recognition and Artificial Intelligence, 2017, 30(1): 21-31.
[43]

Sakkari M, Hamdi M, Elmannai H, et al. Feature extraction-based deep self-organizing map[J]. Circuits, Systems, and Signal Processing, 2022, 41(5): 2802-2824.