Application of Data Mining in Well Control Management for Well Repair Operations

DOI

10.2991/978-94-6239-689-0_22How to use a DOI?

Keywords

well control; data mining; well repair operations; anomaly detection; risk early warning

Abstract

Well control in well repair operations is essential to safe and stable oilfield production, because failures in pressure control may lead to blowouts, environmental pollution, equipment damage, and even casualties. Traditional well control management mainly depends on manual inspection, experience-based judgment, and fixed emergency procedures, which makes it difficult to identify early abnormal signals in a timely and accurate manner. To improve the effectiveness of well control management, this paper discusses the application of data mining techniques in well repair operations. Time-series analysis and anomaly detection can be used to monitor the operating status of key well control equipment, while data-driven early warning models can support the identification of kick and blowout risks. By integrating equipment-state data, pressure-related signals, and operational information, data mining provides a more objective and timely basis for risk assessment and emergency response. This study shows that the introduction of data mining can strengthen process supervision, improve abnormal situation warning capability, and support the intelligent development of well control management in well repair operations.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Miao Miao
PY  - 2026
DA  - 2026/05/28
TI  - Application of Data Mining in Well Control Management for Well Repair Operations
BT  - Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026)
PB  - Atlantis Press
SP  - 224
EP  - 231
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-689-0_22
DO  - 10.2991/978-94-6239-689-0_22
ID  - Miao2026
ER  -