A study on geological structure prediction based on random forest method
The Xingmeng orogenic belt is located in the eastern section of the Central Asian orogenic belt, which is one of the key areas to study the formation and evolution of the Central Asian orogenic belt. At present, there is a huge controversy over the closure time of the Paleo-Asian Ocean in the Xingme...
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KeAi Communications Co. Ltd.
2022-12-01
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| Series: | Artificial Intelligence in Geosciences |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666544123000047 |
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| author | Zhen Chen Qingsong Wu Sipeng Han Jungui Zhang Peng Yang Xingwu Liu |
| author_facet | Zhen Chen Qingsong Wu Sipeng Han Jungui Zhang Peng Yang Xingwu Liu |
| author_sort | Zhen Chen |
| collection | DOAJ |
| description | The Xingmeng orogenic belt is located in the eastern section of the Central Asian orogenic belt, which is one of the key areas to study the formation and evolution of the Central Asian orogenic belt. At present, there is a huge controversy over the closure time of the Paleo-Asian Ocean in the Xingmeng orogenic belt. One of the reasons is that the genetic tectonic setting of the Carboniferous volcanic rocks is not clear. Due to the diversity of volcanic rock geochemical characteristics and its related interpretations, there are two different views on the tectonic setting of Carboniferous volcanic rocks in the Xingmeng orogenic belt: island arc and continental rift. In recent years, it is one of the important development directions in the application of geological big data technology to analyze geochemical data based on machine learning methods and further infer the tectonic background of basalt. This paper systematically collects Carboniferous basic rock data from Dongwuqi area of Inner Mongolia, Keyouzhongqi area of Inner Mongolia and Beishan area in the southern section of the Central Asian Orogenic Belt. Random forest algorithm is used for training sets of major elements and trace elements in global island arc basalt and rift basalt, and then the trained model is used to predict the tectonic setting of the Carboniferous magmatic rock samples in the Xingmeng orogenic belt. The prediction results shows that the island arc probability of most of the research samples is between 0.65 and 1, which indicates that the island arc tectonic setting is more credible. In this paper, it is concluded that magmatism in the Beishan area of the southern part of the Central Asian Orogenic belt in the Early Carboniferous may have formed in the heyday of subduction, while the Xingmeng orogenic belt in the Late Carboniferous may have been in the late subduction stage to the collision or even the early rifting stage. This temporal and spatial evolution shows that the subduction of the Paleo-Asian Ocean is different from west to east. Therefore, the research results of this paper show that the subduction of the Xingmeng orogenic belt in the Carboniferous has not ended yet. |
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| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-04-10T04:35:11Z |
| publishDate | 2022-12-01 |
| publisher | KeAi Communications Co. Ltd. |
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| series | Artificial Intelligence in Geosciences |
| spelling | doaj.art-6b9259ba1fe34f4b8e4b63b0239930542023-03-10T04:36:33ZengKeAi Communications Co. Ltd.Artificial Intelligence in Geosciences2666-54412022-12-013226236A study on geological structure prediction based on random forest methodZhen Chen0Qingsong Wu1Sipeng Han2Jungui Zhang3Peng Yang4Xingwu Liu5School of Earth Sciences and Resources, China University of Geosciences (Beijing), Beijing, 100083, China; Corresponding author.Applied Geology Research Center, China Geological Survey, Chengdu, 610036, ChinaApplied Geology Research Center, China Geological Survey, Chengdu, 610036, ChinaApplied Geology Research Center, China Geological Survey, Chengdu, 610036, ChinaApplied Geology Research Center, China Geological Survey, Chengdu, 610036, ChinaApplied Geology Research Center, China Geological Survey, Chengdu, 610036, ChinaThe Xingmeng orogenic belt is located in the eastern section of the Central Asian orogenic belt, which is one of the key areas to study the formation and evolution of the Central Asian orogenic belt. At present, there is a huge controversy over the closure time of the Paleo-Asian Ocean in the Xingmeng orogenic belt. One of the reasons is that the genetic tectonic setting of the Carboniferous volcanic rocks is not clear. Due to the diversity of volcanic rock geochemical characteristics and its related interpretations, there are two different views on the tectonic setting of Carboniferous volcanic rocks in the Xingmeng orogenic belt: island arc and continental rift. In recent years, it is one of the important development directions in the application of geological big data technology to analyze geochemical data based on machine learning methods and further infer the tectonic background of basalt. This paper systematically collects Carboniferous basic rock data from Dongwuqi area of Inner Mongolia, Keyouzhongqi area of Inner Mongolia and Beishan area in the southern section of the Central Asian Orogenic Belt. Random forest algorithm is used for training sets of major elements and trace elements in global island arc basalt and rift basalt, and then the trained model is used to predict the tectonic setting of the Carboniferous magmatic rock samples in the Xingmeng orogenic belt. The prediction results shows that the island arc probability of most of the research samples is between 0.65 and 1, which indicates that the island arc tectonic setting is more credible. In this paper, it is concluded that magmatism in the Beishan area of the southern part of the Central Asian Orogenic belt in the Early Carboniferous may have formed in the heyday of subduction, while the Xingmeng orogenic belt in the Late Carboniferous may have been in the late subduction stage to the collision or even the early rifting stage. This temporal and spatial evolution shows that the subduction of the Paleo-Asian Ocean is different from west to east. Therefore, the research results of this paper show that the subduction of the Xingmeng orogenic belt in the Carboniferous has not ended yet.http://www.sciencedirect.com/science/article/pii/S2666544123000047Geological big dataBasic rockTectonic environment discriminationRandom forest |
| spellingShingle | Zhen Chen Qingsong Wu Sipeng Han Jungui Zhang Peng Yang Xingwu Liu A study on geological structure prediction based on random forest method Artificial Intelligence in Geosciences Geological big data Basic rock Tectonic environment discrimination Random forest |
| title | A study on geological structure prediction based on random forest method |
| title_full | A study on geological structure prediction based on random forest method |
| title_fullStr | A study on geological structure prediction based on random forest method |
| title_full_unstemmed | A study on geological structure prediction based on random forest method |
| title_short | A study on geological structure prediction based on random forest method |
| title_sort | study on geological structure prediction based on random forest method |
| topic | Geological big data Basic rock Tectonic environment discrimination Random forest |
| url | http://www.sciencedirect.com/science/article/pii/S2666544123000047 |
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