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Stratigraphic lithology identification based on no-dig Logging While Drilling system and random forest

Authors :
Han Xu
Kongxuan Yao
Danyi Cheng
Qiangyin Song
Zhiming Ma
Xuming Zhu
Xiaoming Wu
Guanhui Zhao
Xiaochun Cai
Source :
地质科技通报, Vol 40, Iss 5, Pp 272-280 (2021)
Publication Year :
2021
Publisher :
Editorial Department of Bulletin of Geological Science and Technology, 2021.

Abstract

Through the self-developed and designed no-dig Logging While Drilling(LWD) system, it can collect the parameters of no-dig drilling, identify the real-time formation lithology of no-dig drilling, and provide safety information guarantee for no-dig construction.In view of the lack of prospecting data in no-dig engineering, it is difficult to determine the lithology of the excavation stratum.A real-time data acquisition system based on the no-dig LWD system is proposed.The random forest algorithm is used to establish the stratum identification model, and identify the unknown strata.The identification results are displayed visually.Through the practical application of the detection while drilling system in the engineering field, the drilling sensitive parameters including Rate of Penetration(ROP), torque, rotation speed, pulling force, pump pressure and pump volume are obtained as training samples.The random forest algorithm is used to train the collected drilling parameters, and the decision tree and random forest are constructed to classify the drilling parameters.A classification model aiming at the classification of typical no-dig strata is established, and the classification labels of miscellaneous fill, clay, silty fine sand, gravel and silt are determined respectively.Furthermore, based on the classification results of machine learning, PCA principal component analysis is used to reduce the dimension of strata recognition features to three-dimensional, and realize the three-dimensional display of formation lithology identification results.The prediction model is applied to practical engineering to verify its effectiveness.The results show that the method can quickly identify the drilling formation under the condition of no-dig real-time drilling, and the recognition accuracy is as high as 92%.The research results provide important information for the selection of no-dig mud and no-dig reaming stage.

Details

Language :
Chinese
ISSN :
20968523
Volume :
40
Issue :
5
Database :
Directory of Open Access Journals
Journal :
地质科技通报
Publication Type :
Academic Journal
Accession number :
edsdoj.fe79f0fc73354b60874344d0b0d40bed
Document Type :
article
Full Text :
https://doi.org/10.19509/j.cnki.dzkq.2021.0039