蒙特卡洛法在油气勘探项目决策中的应用

doi:10.3969/j.issn.1002-302x.2017.04.009

摘要/Abstract

摘要：

现代投资组合优化计算中，基于勘探项目确定性经济评价结果的遗传算法已经得到广泛应用。然而在实际勘探项目评价中，经济评价的部分参数可能在评价周期内发生较大变化，这些不确定因素会影响到投资组合分析结果的准确性。因此在油气勘探项目投资组合分析中引入蒙特卡洛法，充分考虑到经济评价中油气产量、油气价格及地质风险等评价参数发生变化时经济评价结果的变化情况，在此基础上进行最优投资组合分析。蒙特卡洛法计算过程主要包括构造概率过程、随机抽样、建立各种估计量等步骤，通过渤海湾盆地14 个勘探项目投资组合优化实例应用，表明基于蒙特卡洛法的投资组合分析方法能够很好地处理多个勘探目标的组合优化问题，投资组合分析结果也较为合理。

关键词: 油气勘探, 投资组合优化, 遗传算法, 蒙特卡洛模拟, 效益前缘

Abstract: Genetic algorithm, based on deterministic economic evaluation of exploration project, has been widely adopted in modern portfolio optimization, with its advantages actually recognized. However, some economic evaluation parameters of the project may be varied vastly during the evaluation, especially for those exploration projects with long-life cycle. Obviously, These uncertain factors can affect the accuracy of the portfolio analysis. In view of this situation, the author introduced the Monte Carlo method in the portfolio calculation, which is based on uncertain economic evaluation. Fully considering the variety situation of the parameters change, such as oil and gas production, oil and gas prices and geologic risk, the method carries on optimized portfolio analysis by massive Monte Carlo simulation with possible economic evaluation results. The application of portfolio optimization of 14 exploration projects in Bohai Bay Basin shows that this method, considering the uncertain economic evaluation results, can deal with portfolio optimization of multi-objects well, and the analysis results are more objective and reasonable.

中图分类号:

王义刚　徐忠美　曹　晋　李治昊. 蒙特卡洛法在油气勘探项目决策中的应用[J]. 石油科技论坛, 2017, 36(4): 44-48.

Wang Yigang, Xu Zhongmei, Cao Jin, Li Zhihao. Application of Monte Carlo in Oil and Gas Exploration Project Decision Making[J]. Petroleum Science and Technology Forum, 2017, 36(4): 44-48.

参考文献

[1] 金之钧, 石兴春, 韩保庆. 勘探开发一体化经济评价模型的建立及其应用[J]. 石油学报, 2002,23(2):1-5. Jin Zhijun, Shi Xingchun, Han Baoqing. The foundation and application of the integrated model of economic evaluation in exploration and development[J]. Acta Petrolei Sinica,2002,23(2):1-5.
[2] 周总瑛, 唐跃刚. 我国油气资源评价的现状与存在问题[J]. 新疆石油地质,2004,25(5):554-556. Zhou Zongying, Tang Yuegang. Current situation and problems in China's oil and gas resources assessment[J]. Xinjiang Petroleum Geology,2004,25(5):554-556.
[3] 罗凯升, 贾希玉, 翁宁. 圈闭评价与油气勘探决策[J]. 新疆石油地质,1997,18(1):24-29. Luo Kaisheng, Jia Xiyu, Wen Ning. Trap evaluation and oil and gas exploration decision[J]. Xinjiang Petroleum Geology,1997,18(1):24-29.
[4] 郭秋麟, 米石云, 谢红兵, 等. 勘探目标投资组合的优化模型及其应用[J]. 中国石油勘探,2005,10(2):53-57。 Guo Qiulin, Mi Shiyun, Xie Hongbing, et al. The portfolio optimization model of exploration objects and it’s application[J].China Petrleum Exploration,2005,10(2): 53-57.
[5] 郭秋麟. 考虑地质风险的勘探项目投资组合优化模型[J]. 石油勘探与开发,2007,34(6):760-764. Guo Qiulin. A portfolio optimization model for petroleum exploration projects with consideration of geological risk[J].Petroleum Exploration and Development,2007, 34(6):760-764.
[6] 蔡利学, 闫相宾, 李娜, 等. 钻探目标评价优选决策系统[J]. 石油与天然气地质,2014,35(5):720-728. Cai Lixue, Yan Xiangbin, Li Na, et al. Evaluation optimization and decision system for prospects to drill[J]. Oil and Gas Geology,2014,35(5):720-728.
[7] 米立军, 张厚和, 陈蓉, 等. 中海油勘探投资组合系统开发与应用[J]. 中国石油勘探,2008,13(5):54-60. Mi Lijun, Zhang Houhe, Chen Rong, et al. Development and application of exploration portfolio systems of CNOOC[J].China Petroleum Exploration,2008,13(5): 54-60.
[8] 米立军, 张厚和, 高剑波. 中海油勘探投资组合管理理念与实践[J]. 中国石油勘探,2011,16(1):70-74. Mi Lijun, Zhang Houhe, Gao Jianbo. Management idea and practice of exploration portfolio of CNOOC[J].China Petroleum Exploration,2011,16(1): 70-74.
[9] 陈科燕. 基于遗传算法的最优证券组合投资模型研究[D]. 南京: 南京气象学院,2004. Chen Keyan. The research of the optimal models for portfolio investment bases on genetic algorithm[D].Nanjing: Nanjing Institute of Meteorology,2004.
[10] 黄文华, 王仁明, 刘芬. 混合遗传算法在电厂机组负荷分配中的应用[J]. 三峡大学学报( 自然科学版), 2006,28(4):400-403. Huang Wenhua, Wang Renming, Liu Fen. Application of hybrid genetic algorithm to load allocation among power generating[J].Units Journal of China Three Gorges University(Natural Sciences),2006,28(4):400-403.
[11] 王小平, 曹立明. 遗传算法――理论、应用与软件实现[M]. 西安: 西安交通大学出版社,2002:234-236. Wang Xiaoping, Cao Liming. Genetic algorithm:Theory, application and software implementation[M]. Xi’an: Xi’an Jiaotong University Press,2002：234-236.
[12] 王永兰, 陈光海. 油气勘探项目投资组合优化方法[J]. 河南石油,2005,19(2):87-89. Wang Yonglan, Chen Guanghai. Optimization of portfolio of petroleum exploration projects[J].Henan Petroleum, 2005,19(2):87-89.
[13] 赵鹏. 基于Copula 理论的投资组合风险测度[J]. 统计与决策,2011,327(3):37-40. Zhao Peng. Portfolio risk measure based on copula theory[J].Statistics and Decision,2011,327(3):37-40.
[14] 吴海龙, 方兆本, 朱俊鹏. 基于R-vineCopula 方法的投资组合风险分析[J]. 投资研究,2013,32(10):98-107. Wu Hailong, Fang Zhaoben, Zhu Junpeng. Portfolio risk analysis baised on R-vineCopula[J].Investment Research,2013,32(10):98-107.
[15] 王丹丹, 李明. 基于VaR 模型的证券投资组合风险分析[J]. 合作经济与科技,2011,27(3):62-63. Wang Dandan, Li Ming. Portfolio risk analysis based on VaR-model[J].Cooperative economy and science,2011,27(3): 62-63.
[16] 杨祺, 曹阳. 油气勘探项目投资决策的风险分析[J]. 石油科技论坛,2009,28(5):46-49. Yang Qi, Cao Yang. Risk analysis on investment decision-making of oil and gas exploration projects[J]. Oil Forum,2009,28(5):46-49.