石油与天然气地质 ›› 2017, Vol. 38 ›› Issue (5): 983-992.doi: 10.11743/ogg20170517

• 技术方法 • 上一篇    下一篇

区带勘探中的油气资源评价方法

盛秀杰1, 金之钧1, 肖晔2   

  1. 1. 中国石化 石油勘探开发研究院, 北京 100083;
    2. 清华大学 理学院 数学科学系, 北京 100084
  • 收稿日期:2016-03-03 修回日期:2011-03-21 出版日期:2017-10-28 发布日期:2017-11-10
  • 第一作者简介:盛秀杰:(1973-),男,博士,石油工程。E-mail:shengxj.syky@sinopec.com。
  • 基金项目:
    中国科学院战略性先导科技专项(A类)(XDA14010101)的软件成果。

Petroleum resources assessment methodology in play exploration stages

Sheng Xiujie1, Jin Zhijun1, Xiao Ye2   

  1. 1. Petroleum Exploration and Production Research Institute, SINOPEC, Beijing 100083, China;
    2. Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China
  • Received:2016-03-03 Revised:2011-03-21 Online:2017-10-28 Published:2017-11-10

摘要: 国内外主流统计方法的预测结果,作为区带高效勘探部署的有效决策依据还有一段距离,评价方法研究与应用仍有提升空间。立足于提升区带商业发现效益以及解决区带勘探部署规划中的实际问题,分别提出:①区分边际概率、条件概率与空间概率模型的地质模型内涵与适用条件,揭示特定地质条件约束下的地质风险,辅助提升低勘探程度区带的预探目标或风险井的勘探成功率;②遵循油气成藏体系理论划分高勘探程度区带范围,按最早探井发现时间整理、归并储量计算单元为经历了相同地质作用过程的油气藏(样本)数据,为求解油气藏规模总体分布模型提供较为客观的样本数据;③充分考虑不同勘探投入对油气藏发现的影响,推导期望最大化算法并基于勘探效率图版求解地质帕莱托概率分布参数,更加客观地预测区带油气资源潜力及油气藏规模结构;④分别采用体现地质和市场不确定性的情景树,以及勘探目标地质相关性或战略相关性的贝叶斯网络,可有效将投资组合技术与公司战略规划部署有机结合起来。

关键词: 地质帕莱托, 勘探效率图版, 投资组合, 地质风险评价, 区带定量评价, 油气资源评价

Abstract: The assessment results of prevailing statistical methods used in the petroleum industry are,to some extent,ina-dequate in helping the formulation of effective exploration strategies.There are still plenty of rooms of improvement in terms of assessment methods.Aiming at enhancing the economy of commercial discoveries and dealing with challenges faced during exploration deployment planning,we proposed that:(1) Differentiating the applicable scope and conditions of marginal,conditional and spatial probability mathematical assessment models and providing information concerning geological-constraint risk so as to improve success rate of exploratory drilling in less-explored areas;(2) Providing more objective data samples for solving general reservoir scale distribution models by delineating highly-explored areas with the guidance of petroleum accumulation theories and sorting and merging reserve assessment units into oil and gas reservoirs (samples) that went through the same geologic processes according to the time order of first discovery well;(3) Taking into consideration the effect of different exploratory investments upon oil and gas discoveries and eliciting expectation maximization algorithm to work out the Pareto distribution parameters based on exploration efficiency plates,so as to predict more objectively the resource potential of oil and gas and the structure of reservoir scales;(4) Using scenario trees representing respectively geological and market uncertainties and geology-or strategy-related Bayesian networks to combine effectively and organically investment portfolios and exploration strategies.

Key words: geological Pareto, exploration efficiency plate, investment portfolio, geological risk assessment, quantitative assessment of play, assessment of oil and gas resources

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