Research on Optimization of Drilling Investment Estimation Based on Parameter Extraction and Simulation

doi:10.12388/j.issn.1673-2677.2025.02.009

Abstract

Abstract:

The investment estimation of a systematic drilling engineering project is an important step for oilfield enterprises to strengthen investment control and enhance operation management. The quality of investment estimation does not only decide the feasibility and profitability of the development plan，but also has an important instruction influence on the implementation and operation performance of the approved engineering plan. This paper proposed a method for extracting engineering parameters of drilling investment estimation based on the natural language processing algorithm and the Monte Carlo simulation investment prediction model. These two techniques were introduced into the petroleum engineering estimation，and it was demonstrated via modelling and case studies that all selected control factors were significant and thus effective. Based on the above，the investment estimation was carried out. Natural language processing algorithms were required for parameter extraction and processing，with an accuracy of over 90%. Meanwhile，the Monte Carlo simulation investment prediction model was used for calculation to ensure that the error between the extreme investment and the existing economic evaluation results was less than 5%. This developed method has been successfully applied to 29 production capacity building projects in 2024，identifying and warning 8 projects with excessive investment. It improves the accuracy and efficiency of engineering parameter extraction，enhances the percent of pass for the internal rate of return of petroleum drilling engineering investment estimation，and is of great help in improving the digitalization level of the petroleum engineering estimation.

Key words:

"> petroleum drilling engineering, engineering plan, investment estimation, engineering parameter, natural language processing, Monte Carlo

摘要：

钻井系统工程投资估算是油田企业加强投资管控、强化经营管理的重要环节，投资测算工作质量不仅决定着开发方案的可行性和效益性，而且对已批复工程方案的实施和运行效果有着重要指导性影响。提出一种基于自然语言处理算法的钻井投资估算工程参数提取方法和蒙特卡洛模拟投资预测模型，将上述两种技术引入石油工程估算形成中，通过模型构建、实证分析得到的所有控制因子均显著证实了研究选择的控制因子有效。基于上述思路，开展相关工作，要求运用自然语言处理算法进行参数提取和处理，准确率需达到90%以上；同时利用蒙特卡洛模拟投资预测模型进行计算，确保极限投资与现有经济评价结果的误差小于 5%。研究成果已成功应用于2024年29项产建项目，预警超额投资项目8项，提高了工程参数提取的准确性和效率，提升了石油钻井工程投资估算内部收益达标率，对于提升石油工程估算形成的数字化程度有较大帮助。

关键词:

石油钻井工程, 工程方案, 投资估算, 工程参数, 自然语言处理, 蒙特卡洛

CLC Number:

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LIU Mingyan , ZHANG Zhunxi , WANG Xintong , ZHAO Haiyan , WU Yuanyue , LIU Yongjie.

Research on Optimization of Drilling Investment Estimation Based on Parameter Extraction and Simulation

[J]. Xinjiang Oil & Gas, 2025, 21(2): 82-.

刘明艳 , 张准玺 , 王欣桐 , 赵海燕 , 邬元月 , 刘永杰.

基于参数提取和模拟的钻井投资估算优化方法

[J]. 新疆石油天然气, 2025, 21(2): 82-.

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