节点文献

我国油气勘探项目投资决策研究

The Study on Investment Decision-making of the Petroleum Exploration Project in China

【作者】 殷爱贞

【导师】 周泓; 张在旭;

【作者基本信息】 中国石油大学 , 石油工程管理, 2010, 博士

【摘要】 在勘探难度逐年加大,勘探资金紧缺的情况下,应做好油气勘探项目投资决策工作,使有限勘探资金得到有效利用,提高勘探投资效益。本文主要研究工作有:(1)油气勘探开发投资优化研究。勘探投资规模及勘探开发投资比例直接影响油田企业勘探投资总的效果,但长期以来对此进行定量研究的专家学者很少。本文研究的思路是:首先根据油田企业历年的勘探开发数据资料,总结勘探开发规律,预测吨可采储量投资和单位产能建设投资等参数;其次,估算当年勘探投资可能发现的可采储量;再次,估测将这些可采储量开采所需开发投资、开采成本及相关税费;最后构建勘探开发投资优化模型,测算油田企业合适的勘探投资、开发投资及勘探开发投资比例,为决策者提供参考。(2)油气勘探项目多属性评价研究。包括以下几个方面的工作:①明确油气勘探项目经济评价的对象是勘探开发整体;②根据油气勘探项目特点,完善现有的评价指标体系,形成一套能反映项目间差异、易于操作的评价指标体系;③各指标从不同的角度反映油气勘探项目特征,因此将多属性决策引入油气勘探项目经济评价。(3)油气勘探项目投资组合优化研究。油气勘探项目的最大特点是风险高、收益大,勘探项目投资组合优化的目标是风险和收益的均衡,因此首先确定油气勘探项目投资组合风险和收益的衡量指标。综合评价值能综合反映各项目风险和收益的排序情况,但综合评价值没有实质意义,因此可用将其做为项目投资组合的综合目标之一,但不宜做为惟一目标;本文选取净年值指标来衡量项目和项目组合的收益,净年值的方差来衡量项目和项目组合的风险,综合评价值来衡量项目及项目组合的综合评价结果,项目组合的收益是入选项目净年值之和,项目组合的方差用夏普的单指数模型计算,项目组合的综合评价值以入选项目综合评价值与投资加权之和,最后建立油气勘探项目投资组合多目标混合规划模型,运用遗传算法求解。

【Abstract】 With the scare exploration funds and increasing difficulty of exploration, the oil-gas exploration investment decision-making should be studied, so as to use the limited exploration funds effectively and increase the exploration investment benefit. The author’s main research work and achievements are summarized as follows:(1) Study on the oil-gas exploration and development investment optimization. The scale of exploration investment and proportion of exploration and development investment directly influence the overall effect of exploration investment, which has been studied quantificationally by very few experts for a long time. The idea of this paper is summarized as follows: Firstly,to summarize the law of exploration and development, to forecast the parameters of tons of recoverable reserves investment and unit capacity investment, etc. according to the data of exploration and development of oil companies over the years. Secondly,to estimate the recoverable reserves that may be found in exploration investment in a year. Thirdly,to estimate the development investment,exploitation cost and related taxes for the recoverable reserves. Finally,to construct the optimization model of exploration and development investment, to estimate the appropriate oilfield exploration, development investment and investment ratio to provide reference for decision makers.(2)Study on multi-attribute evaluation of oil-gas exploration project, which includes the following aspects of work:①To ensure that the evaluation object is the whole process of exploration and development.②To perfect the existing evaluation index system existing,form a set of evaluation index system which can reflect difference among projects and easy to operate.③To introduce the multi-attribute decision making in economic evaluation of oil and gas exploration project, because the indicators reflect different aspects of oil and gas exploration project characteristics. (3) Study on the portfolio optimization of oil-gas exploration project. The main characteristic of oil-gas exploration project is high-risk and high-profit. The objective of portfolio optimization is the balance of risks and profits,so the measurement indicators of risks and profits should be determined firstly. The comprehensive evaluation value can comprehensively reflect the sort of each project’s risks and benefits,but the comprehensive evaluation value has no real significance. It can be integrated as one of the project portfolio objectives, but not as the only objective. The net annual value is selected to measure the profits, the variance of the net annual value is selected to measure the risks and the comprehensive evaluation value is selected to measure the comprehensive evaluation results. Portfolio income is the summation of the net annual value of the selected projects. The portfolio variance can be calculated with Sharpe’s single-index model. The comprehensive evaluation value of the project portfolio is the summation of comprehensive evaluation value of the selected projects. Finally, the oil and gas exploration project portfolio multi-objective mixed programming model is established, which is solved with genetic algorithm.

  • 【分类号】F224;F426.22
  • 【被引频次】4
  • 【下载频次】771
  • 攻读期成果
节点文献中: