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Map-based uncertainty analysis for exploration using basin modeling and machine learning techniques applied to the Levant Basin petroleum systems, Eastern Mediterranean
Marine and Petroleum Geology ( IF 3.7 ) Pub Date : 2020-10-01 , DOI: 10.1016/j.marpetgeo.2020.104560
Mathieu Ducros , Fadi Henri Nader

Abstract The Levant Basin of the East-Mediterranean region contains a biogenic petroleum system and possibly an underlying thermogenic system. The application of a new map-based uncertainty and sensitivity analysis that integrates a large set of geological parameters demonstrates that a connection between an Upper Cretaceous thermogenic petroleum system and the shallower Oligo-Miocene reservoirs is highly possible in the southern part of the basin (offshore Israel and southern Lebanon) where hydrocarbon fluids are generated from the Campanian source rock and charge the overlying Oligo-Miocene reservoir interval through faults. Estimates of volumes of expelled hydrocarbons combined with regional analysis of the Eocene top seal integrity indicates that the most prospective zones correspond to the southern offshore Lebanon and offshore Israel. In the northern part of the Levant Basin (offshore central and northern Lebanon), petroleum fluids potentially generated by the Campanian source rocks remain trapped under the Eocene seal or they migrate towards the margins of the basin. Our approach is based on applications of machine learning techniques and robust statistical analyses to petroleum systems modeling, focusing on spatial uncertainty analysis. It may be used on similar frontier or emerging hydrocarbon provinces to help de-risking the petroleum systems.

中文翻译:

使用应用于地中海东部黎凡特盆地石油系统的盆地建模和机器学习技术进行基于地图的不确定性分析

摘要 东地中海地区的黎凡特盆地包含一个生物成因石油系统,可能还有一个潜在的热成因系统。新的基于地图的不确定性和敏感性分析的应用,该分析整合了大量地质参数,表明在盆地南部(近海)上白垩统热成因石油系统与较浅的渐新世油藏之间很有可能存在联系。以色列和黎巴嫩南部),其中烃类流体从坎帕阶烃源岩中产生,并通过断层向上覆的渐新世储层层段充注。对排出的碳氢化合物量的估计以及对始新世顶部密封完整性的区域分析表明,最有前景的区域对应于黎巴嫩南部近海和以色列近海。在黎凡特盆地的北部(黎巴嫩中部和北部近海),坎帕阶烃源岩可能产生的石油流体仍被困在始新世密封之下或向盆地边缘迁移。我们的方法基于机器学习技术和稳健统计分析对石油系统建模的应用,重点是空间不确定性分析。它可用于类似的前沿或新兴的碳氢化合物省份,以帮助降低石油系统的风险。我们的方法基于机器学习技术和稳健统计分析对石油系统建模的应用,重点是空间不确定性分析。它可用于类似的前沿或新兴的碳氢化合物省份,以帮助降低石油系统的风险。我们的方法基于机器学习技术和稳健统计分析对石油系统建模的应用,重点是空间不确定性分析。它可用于类似的前沿或新兴的碳氢化合物省份,以帮助降低石油系统的风险。
更新日期:2020-10-01
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