Development and Practice of Cloud Collaborative Platform for Downhole Measurement Tools
The digital transformation and intelligent development of the petroleum industry have become a consensus. The digital solution for surface equipment is relatively mature， while the digital upgrade of downhole tools is difficult. The measurement tools are mainly single machine version， which is diffi...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of China Petroleum Machinery
2025-06-01
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| Series: | Shiyou jixie |
| Subjects: | |
| Online Access: | http://www.syjxzz.com.cn/en/#/digest?ArticleID=4959 |
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| Summary: | The digital transformation and intelligent development of the petroleum industry have become a consensus. The digital solution for surface equipment is relatively mature， while the digital upgrade of downhole tools is difficult. The measurement tools are mainly single machine version， which is difficult to meet the current requirements for improving drilling quality and efficiency. In the paper， based on the remote operation requirements of coreless magnetic steering tool， a platform architecture of five modules， including simulation rehearsal， virtual training， remote operation， smart tool and intelligent decision， was designed in detail， achieving a whole process digitization from predrilling risk assessment and in-drilling acquisition and processing to post-drilling feedback and optimization， and a visual interface was developed. Moreover， to solve the problem of low far-field ranging accuracy， multiple magnetic steering data mining algorithms such as support vector machine （SVM）， decision tree （DT）， multilayer perceptron （MLP） and convolutional neural network （CNN） were built and compared， indicating that the robustness and generalization of the multilayer perceptron algorithm is the best. The field application in 5 wells shows that the efficiency is improved by 30% and the remote measurement accuracy is increased by 20%. The research results provide a reference for the development of cloud collaborative digital platform of similar tools. |
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| ISSN: | 1001-4578 |