蒙特卡洛模拟法在也门马里卜—夏布瓦盆地中的应用

高济稷; 白国平; 秦养珍; 周志龙

doi:10.11781/sysydz201003305

蒙特卡洛模拟法在也门马里卜—夏布瓦盆地中的应用

doi: 10.11781/sysydz201003305

高济稷^1,2,
白国平^1,2,
秦养珍^1,2,
周志龙^1,2

1.
中国石油大学, 油气资源与探测国家重点实验室, 北京, 102249
2. 中国石油大学, 盆地与油藏研究中心, 北京, 102249

基金项目: 国家油气专项项目(2008ZX05031-001-006);国土资源部油气资源战略研究中心全球选区项目(GT-YQ-QQ-2008-3-09)”联合资助

详细信息

作者简介:
高济稷(1986- ),男,硕士研究生,主要从事油气资源评价研究.E-mail:entermoon@gmail.com.

中图分类号: TE155
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出版历程
- 收稿日期: 2010-01-25
- 修回日期: 2010-05-07
- 刊出日期: 2010-06-28

MONTE CARLO SIMULATION-A CASE STUDY OF MARIB-SHABWA BASIN IN YEMEN

1.
State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China
2. Basin and Reservoir Research Center, China University of Petroleum, Beijing 102249, China

摘要

摘要: 美国地质调查局在2000年全球油气资源评价项目中,对待发现可采资源量的计算采用了概率相乘,即蒙特卡洛模拟法。文中将此方法应用于也门马里卜—夏布瓦盆地的资源评价工作,计算结果表明该盆地待发现可采资源量为1.02×10⁸t油当量。认为研究区内同裂谷系成藏组合已接近成熟,而基底裂缝型成藏组合可能具有较大的勘探潜力。
- 蒙特卡洛模拟法 /
- 资源评价 /
- 勘探潜力 /
- 马里卜—夏布瓦盆地 /
- 也门
Abstract: In the World Petroleum Assessment 2000 project,U.S.Geologic Survey(USGS) adopted the method of probabilistic multiplying,namely Monte Carlo simulation to obtain the forecast for undisco-vered petroleum resources.This method is applied to the resources assessment of the Marib-Shabwa Basin in Yemen,and the results show the undiscovered resources will be 102 million tons of oil equivalents(TOE).In the study area,the syn-rift play is considered to be mature,while the fractured basement play is supposed to be highly promising.
- Monte Carlo simulation /
- resources assessment /
- exploration potential /
- Marib-Shabwa Basin /
- Yemen

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参考文献(9)

[1]	USGS.U.S.Geological Survey World Petroleum Assessment2000:Description and results by World Energy Assessment Team[DB].USGS Digital Data Series DDS-60,4 CD-ROM set,2000.
[2]	SCHMOKER J W,KLETT T R.U.S.Geological Survey assessment model for undiscovered conventional oil,gas,and NGL resources:The seventh approximation[CD]//U.S.Geological Survey World Petroleum Assessment Team,eds.U.S.Geological Survey World Petroleum Assessment 2000:Geological Survey Digital Data Series DDS-60,4 CD-ROMs,2000.
[3]	CHARPENTIER R R,KLETT T R.Monte Carlo simulation model[CD]//U.S.Geological Survey Assessment Methodology Team,eds.U.S.Geological Survey World Petroleum Assessment 2000:U.S.Geological Survey Digital Data Series DDS-60,4 CD-ROMs,2000.
[4]	METROPOLIS N,ULAM S.The Monte Carlo Method[J].Journal of the American Statistical Association,1949,44(247):335-341.
[5]	JOEY MECHELLE DAWES.EC Approves Project Methodology[J].AAPG Explorer,1999 May Issue.
[6]	周总瑛,白森舒,何宏.成因法与统计法油气资源评价对比分析[J].石油实验地质,2005,27(1):67-73.
[7]	KLETT T R,CHARPENTIER R R,SCHMOKER J W.Assessment operational procedures[CD]//U.S.Geological Survey World Petroleum Assessment Team,eds.U.S.Geological Survey World Petroleum Assessment 2000:U.S.Geological Survey Digital Data Series DDS-60,4 CD-ROMs,2000.
[8]	AHLBRANDT T S,CARPENTIER R R,KLETT T R.et al.Global Resources Estimates from Total Petroleum Systems,AAPG Memoir 86[M].Tulsa:AAPG,2005:1-323.
[9]	AHLBRANDT THOMAS S.Chapter Introduction[CD]//U.S.Geological Survey Assessment Methodology Team,eds.U.S.Geological Survey World Petroleum Assessment2000:U.S.Geological Survey Digital Data Series DDS-60,4 CD-ROMs,2000.