Dynamic Numerical Simulation and Transfer Learning-Based Rapid Rock Identification during Measurement While Drilling (MWD)
文献类型：期刊论文
| 作者 | Fang, Yuwei1,2,3,4; Wu, Zhenjun3,4; Jiang, Lianghua1,2; Tang, Hua3,4; Fu, Xiaodong3,4; Shen, Junxin1,2 |
| 刊名 | PROCESSES
 |
| 出版日期 | 2024-06-01 |
| 卷号 | 12期号:6页码:34 |
| 关键词 | measurement while drilling (MWD) numerical simulation rock classification transfer learning neural network drilling parameters granite limestone sandstone |
| DOI | 10.3390/pr12061260 |
| 英文摘要 | In constructing rapid rock identification models for measurement while drilling (MWD) via neural network methods, collecting actual drilling data to train the model is extremely time-consuming and labor-intensive. This requires extensive drilling experiments in various rock types, resulting in limited neural network training data for rock identification that covers a limited range of rock types. To suitably address this issue, a dynamic numerical simulation model for rock drilling is established that generates extensive drilling data. The input parameters for the simulations include torque, drill bit rotation speed, and drilling speed. A neural network model is then developed for rock classification using large datasets from dynamic numerical simulations, specifically those of granite, limestone, and sandstone. Building upon this model, transfer learning is appropriately applied to store the knowledge obtained in the rock identification based on the neural network model. Further training through transfer learning is conducted with smaller datasets obtained during actual drilling, making the model suitable for practical rock identification and prediction in the drilling processes. The neural network rock classification model, incorporating dynamic numerical simulation and transfer learning, achieves a prediction accuracy of 99.36% for granite, 99.53% for sandstone, and 99.82% for limestone. This reveals an enhancement in prediction accuracy of up to 22.94% compared to the models without transfer learning. |
| 资助项目 | Science and Technology innovation demonstration project of Yunnan Transportation Department[2022(24-2)] ; Key R&D Program of Yunnan Province[202303AA080010] ; Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences[SKLGME022014] |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001256710500001 |
| 出版者 | MDPI |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/41797]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Wu, Zhenjun |
| 作者单位 | 1.Yunnan Key Lab Digital Commun, Kunming 650103, Peoples R China 2.Yunnan Inst Transport Planning & Design Co Ltd, Kunming 650200, Peoples R China 3.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fang, Yuwei,Wu, Zhenjun,Jiang, Lianghua,et al. Dynamic Numerical Simulation and Transfer Learning-Based Rapid Rock Identification during Measurement While Drilling (MWD)[J]. PROCESSES,2024,12(6):34. |
| APA | Fang, Yuwei,Wu, Zhenjun,Jiang, Lianghua,Tang, Hua,Fu, Xiaodong,&Shen, Junxin.(2024).Dynamic Numerical Simulation and Transfer Learning-Based Rapid Rock Identification during Measurement While Drilling (MWD).PROCESSES,12(6),34. |
| MLA | Fang, Yuwei,et al."Dynamic Numerical Simulation and Transfer Learning-Based Rapid Rock Identification during Measurement While Drilling (MWD)".PROCESSES 12.6(2024):34. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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