利用石油指纹技术进行墨西哥湾深水生产优化的时移产量分配

L. Xing, S. Teerman, F. Descant
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引用次数: 0

摘要

在地下成像、油藏动态建模和油气生产监测方面,上游技术的多样性和复杂性正在迅速发展。然而,对已开采的储层流体进行彻底取样和分析仍然是一项基本需求。储层流体分析是了解所产油气性质的关键,也是优化生产的关键。为了从分析中获得最大的价值,油藏流体取样方案需要精心设计,并将其整合到试井和油藏监测方案中,而不是在此之后再开发。在雪佛龙墨西哥湾深水(DWGOM)的一个盐下油田,一项强大的地球化学采样计划和生产监测计划从最初的生产开始就已经到位,以估计单个堆叠储层的层间贡献。在10年的时间里,这项监测工作一直在对9口混合井进行监测。本文介绍了随时间推移生产地球化学分配的准确性,以及结果如何实质性地影响和改善储层表征和解决完井问题
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Time Lapse Production Allocation Using Oil Fingerprinting for Production Optimization in Deepwater Gulf Mexico
The variety and sophistication of upstream technologies have been growing fast for imaging the subsurface, modeling reservoir performance and monitoring oil and gas production. Yet there remains a fundamental need to thoroughly sample and analyze the produced reservoir fluids. Reservoir fluid analysis is critical for understanding the nature of produced hydrocarbons and is the key for production optimization. To gain the maximum value from this analysis, reservoir fluid sampling programs need to be well designed and integrated into well testing and reservoir surveillance programs, and not to be developed after. In one of Chevron's deep-water Gulf of Mexico (DWGOM) sub-salt fields, a robust geochemical sampling plan and production monitoring program has been in place since initial production to estimate the zonal contribution from individually stacked reservoirs. This surveillance work has been ongoing for 9 commingled wells over a period of 10 years. This paper presents the accuracy of time lapsed production geochemistry allocation and how the results can substantially impact and improve reservoir characterization and trouble shoot completion issues
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