Comparative analysis of several formation identification methods based on parameters while drilling

doi:10.12143/j.ztgc.2024.S1.007

Home > Archive>Volume 51, Issue S1, 2024 >10-15. DOI:10.12143/j.ztgc.2024.S1.007

Comparative analysis of several formation identification methods based on parameters while drilling
DOI:
                        10.12143/j.ztgc.2024.S1.007
                    
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                        ZHANG Hangsheng1,2,3ZHANG Hangsheng
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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SUN Pinghe1,2,3SUN Pinghe
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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ZHU Jianjun4ZHU Jianjun
Sunward Intelligent Equipment Co., Ltd., Changsha Hunan 410100, China
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DENG Yingying1,2,3DENG Yingying
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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CAO Han1,2,3CAO Han
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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ZHANG Chen1,2,3ZHANG Chen
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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ZHANG Xinxin1,2,3ZHANG Xinxin
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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PU Yingjie1,2,3PU Yingjie
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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Affiliation:1.Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;2.Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;3.School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China;4.Sunward Intelligent Equipment Co., Ltd., Changsha Hunan 410100, China
Clc Number:P634
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Abstract:

Real-time recognition of formation lithology is critical for promptly adjusting drilling parameters， effectively controlling wellbore trajectory， and identifying subsurface reservoirs. Compared to traditional methods of identifying lithology， real-time recognition through monitoring parameters while drilling offers advantages such as convenience， efficiency， real-time accuracy， environmental compatibility， and energy efficiency. In this paper， around the lithology identification technology based on real-time parameters while drilling， the parameters according to different applications such as coal exploration and oil and gas reservoir exploitation are classified. Through the analysis of the current research status of drilling measurement and control technology and equipment， the technology for collecting and transmitting real-time parameters while drilling is introduced. Additionally， the characteristics and applications of machine learning algorithms， multivariate statistical analysis， grey relational analysis， and cross-plotting methods are also discussed. Through application cases， it compares and analyzes four types of lithology identification methods based on real-time parameters while drilling. Ultimately， the key technical issues in real-time lithology identification research is summarized， the deficiencies and challenges in development and engineering applications are analyzed， and the recommendations are provided.

Key words:lithology recognition;parameters while drilling;data acquisition;machine learning algorithms;multivariate statistical analysis;grey relational analysis;cross-plotting methods

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Received:July 30,2024
Revised:July 30,2024
Adopted:August 13,2024
Online: November 08,2024
Published:

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