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 northeastern 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, optimization and machine learning.

Supplementary material: supplementary data associated with this article can be found in the data repository for the COSTA model available at https://doi.org/10.17861/6e36e28d-50d9-4e31-9790-18db4bce6e5d and supplementary material is available at https://doi.org/10.6084/m9.figshare.c.5823571

这项工作提出了一个新的开源碳酸盐储层案例研究，即 COSTA 模型，该模型独特地考虑了碳酸盐储层固有的重大不确定性，为一系列地能应用提供了更具挑战性和现实性的基准测试。COSTA 油田很大，有许多井和大量相关体积。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模型概念的集合中，这些概念具有现实的地质和模型复杂程度以及不同的生产概况。由此产生的不同模型的数量和较长的运行时间产生了比当前基准模型更苛刻的计算挑战。

COSTA 模型的灵感来自上 Kharaib 段（早白垩世）的陆架到盆地地质环境，这是世界上最多产的加积副层序碳酸盐地层之一。该数据集基于 43 口井和来自 Rub Al Khali 盆地东北部的相应完全匿名数据，该盆地是更广泛的阿拉伯盆地的子盆地。我们的模型将在陆架到盆地剖面中发现的大规模地质环境和储层异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现实的碳酸盐储层模型，该模型捕获了广泛的地质、岩石物理和地质建模不确定性，并且可以与未公开的合成“真实案例”进行历史匹配。这些模型和数据集以开源形式提供，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。

补充材料：与本文相关的补充数据可在 https://doi.org/10.17861/6e36e28d-50d9-4e31-9790-18db4bce6e5d 的 COSTA 模型的数据存储库中找到，补充材料可在以下网址获得https://doi.org/10.6084/m9.figshare.c.5823571