{"title":"开源碳酸盐岩储层模型的设计","authors":"J. Costa Gomes, S. Geiger, D. Arnold","doi":"10.1144/petgeo2021-067","DOIUrl":null,"url":null,"abstract":"This work presents a new open-source carbonate reservoir case study, the COSTA model, that uniquely considers significant uncertainties inherent to carbonate reservoirs, providing a far more challenging and realistic benchmarking test for a range of geo-energy applications. The COSTA field is large, with many wells and large associated volumes. The dataset embeds many interacting geological and petrophysical uncertainties in an ensemble of model concepts with realistic geological and model complexity levels and varying production profiles. The resulting number of different models and long run times creates a more demanding computational challenge than current benchmarking models.The COSTA model takes inspiration from the shelf-to-basin geological setting of the Upper Kharaib Member (Early Cretaceous), one of the most prolific aggradational parasequence carbonate formations sets in the world. The dataset is based on 43 wells and the corresponding fully anonymised data from the north-eastern part of the Rub Al Khali basin, a sub-basin of the wider Arabian Basin. Our model encapsulates the large-scale geological setting and reservoir heterogeneities found across the shelf-to-basin profile, into one single model, for geological modelling and reservoir simulation studies.The result of this research is a semi-synthetic but geologically realistic suite of carbonate reservoir models that capture a wide range of geological, petrophysical, and geomodelling uncertainties and that can be history-matched against an undisclosed, synthetic 'truth case'. 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引用次数: 2
摘要
这项工作提出了一种新的开源碳酸盐岩储层案例研究,即COSTA模型,该模型独特地考虑了碳酸盐岩储层固有的重大不确定性,为一系列地能源应用提供了更具挑战性和更现实的基准测试。COSTA油田面积大,井多,伴生体积大。该数据集将许多相互作用的地质和岩石物理不确定性嵌入到具有实际地质和模型复杂性水平以及不同生产剖面的模型概念集合中。与当前的基准测试模型相比,由此产生的不同模型的数量和较长的运行时间产生了更苛刻的计算挑战。COSTA模型的灵感来自上Kharaib段(早白垩世)的陆架-盆地地质背景,这是世界上最多产的沉积准层序碳酸盐岩地层之一。该数据集基于Rub Al Khali盆地东北部的43口井和相应的完全匿名数据,该盆地是阿拉伯盆地的一个子盆地。我们的模型将大陆架-盆地剖面的大规模地质背景和储层非均质性封装到一个模型中,用于地质建模和储层模拟研究。这项研究的结果是一套半合成但地质上真实的碳酸盐岩储层模型,它捕获了广泛的地质、岩石物理和地质建模的不确定性,并且可以与未公开的合成“真实案例”进行历史匹配。模型和数据集作为开源提供,用于分析与测试地质建模,不确定性量化,油藏模拟,历史匹配,优化和机器学习的新数值算法相关的几个问题。辅料:https://doi.org/10.6084/m9.figshare.c.5823571
The design of an open-source carbonate reservoir model
This work presents a new open-source carbonate reservoir case study, the COSTA model, that uniquely considers significant uncertainties inherent to carbonate reservoirs, providing a far more challenging and realistic benchmarking test for a range of geo-energy applications. The COSTA field is large, with many wells and large associated volumes. The dataset embeds many interacting geological and petrophysical uncertainties in an ensemble of model concepts with realistic geological and model complexity levels and varying production profiles. The resulting number of different models and long run times creates a more demanding computational challenge than current benchmarking models.The COSTA model takes inspiration from the shelf-to-basin geological setting of the Upper Kharaib Member (Early Cretaceous), one of the most prolific aggradational parasequence carbonate formations sets in the world. The dataset is based on 43 wells and the corresponding fully anonymised data from the north-eastern part of the Rub Al Khali basin, a sub-basin of the wider Arabian Basin. Our model encapsulates the large-scale geological setting and reservoir heterogeneities found across the shelf-to-basin profile, into one single model, for geological modelling and reservoir simulation studies.The result of this research is a semi-synthetic but geologically realistic suite of carbonate reservoir models that capture a wide range of geological, petrophysical, and geomodelling uncertainties and that can be history-matched against an undisclosed, synthetic 'truth case'. The models and dataset are made available as open-source to analyse several issues related to testing new numerical algorithms for geological modelling, uncertainty quantification, reservoir simulation, history matching, optimisation and machine learning.Supplementary material:https://doi.org/10.6084/m9.figshare.c.5823571
期刊介绍:
Petroleum Geoscience is the international journal of geoenergy and applied earth science, and is co-owned by the Geological Society of London and the European Association of Geoscientists and Engineers (EAGE).
Petroleum Geoscience transcends disciplinary boundaries and publishes a balanced mix of articles covering exploration, exploitation, appraisal, development and enhancement of sub-surface hydrocarbon resources and carbon repositories. The integration of disciplines in an applied context, whether for fluid production, carbon storage or related geoenergy applications, is a particular strength of the journal. Articles on enhancing exploration efficiency, lowering technological and environmental risk, and improving hydrocarbon recovery communicate the latest developments in sub-surface geoscience to a wide readership.
Petroleum Geoscience provides a multidisciplinary forum for those engaged in the science and technology of the rock-related sub-surface disciplines. The journal reaches some 8000 individual subscribers, and a further 1100 institutional subscriptions provide global access to readers including geologists, geophysicists, petroleum and reservoir engineers, petrophysicists and geochemists in both academia and industry. The journal aims to share knowledge of reservoir geoscience and to reflect the international nature of its development.