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石油钻井机械钻速预测研究进展
Research Progress on Prediction of Penetration Rate of Oil Drilling Machinery

DOI: 10.12677/me.2024.123055, PP. 449-453

Keywords: 机械钻速预测,研究进展,机器学习
ROP Prediction
, Research Progress, Machine Learning

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Abstract:

钻井机械钻速的精确预测对钻井作业降本增效具有非常重要的意义。总结了国内外钻井机械钻速预测研究进展,大致经历了以下三个阶段:基于物理建模的机械钻速预测模型、基于统计回归的机械钻速预测模型、基于机器学习的机械钻速预测模型。最后分析了目前钻井机械钻速预测模型面临的挑战,并指出在当前人工智能技术与大数据飞速发展的时代背景下,增强钻井机械钻速预测模型的跨区域迁移性一定是未来的发展趋势。
Accurate prediction of drilling machine penetration rate is of great significance to reducing costs and increasing efficiency in drilling operations. This paper summarizes the research progress of drilling ROP prediction at home and abroad, which has roughly gone through the following three stages: ROP prediction model based on physical modeling, ROP prediction model based on statistical regression, and ROP prediction model based on machine learning. Finally, the challenges faced by current drilling machinery penetration rate prediction models are analyzed, and it is pointed out that in the current era of rapid development of artificial intelligence technology and big data, enhancing the cross-regional portability of drilling machinery penetration rate prediction models must be a future development trend.

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