解决油藏规模模拟EOR和CO2封存项目的挑战:准确估计圈闭气饱和度

S. Aghabozorgi, M. Sohrabi
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引用次数: 0

摘要

地质二氧化碳储存项目可行性分析和选址的首要步骤之一是估计指定含水层或枯竭水库的储存能力。已经确定,由于毛细管捕获而储存的CO2体积明显高于其他活性机制。因此,需要一种准确的方法来确定系统中被困气体的饱和度。由于相对渗透率的滞后是圈闭气饱和度的直接函数,因此该方法对于模拟涉及地下储层循环注入流体的任何其他过程也具有重要意义。地下储层工程中循环过程的例子是储气项目和进行提高采收率(EOR)注入的储层。在这项研究中,我们使用商业软件对储层规模模拟结果进行了详细研究,并讨论了在计算圈闭气饱和度时观察到的挑战。第一个挑战是,Land的公式将吸胀循环中测量的初始和剩余非润湿饱和度联系起来。然而,在许多油藏区块,驱替流体的体积和速率不足以确保达到剩余值。准确确定各个储层网格块的饱和度历史也具有挑战性,因为小的振荡使得难以识别流动逆转点。当圈闭气饱和度的组成进入传质计算时,圈闭气再次溶解在油相中,在成分模拟中引入了相当大的误差。而在物理上,它应该被水相隔离和屏蔽。最后,饱和度相关函数的不准确定义会增加使用捕获气饱和度计算相对渗透率数据的误差。在这项研究中,我们提出了一种新的计算捕获气饱和度的工作流程,解决了上述所有问题。该工作流的主干是一种有效的算法,它可以消除任何被误认为是流反转点的振荡。本文讨论的结果表明,应谨慎部署文献中可用的公式(考虑系统中的主动机制)以减少不确定性。因此,提高采收率方法的可行性、二氧化碳封存项目的选址和决策过程可以基于更可靠的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Addressing the Challenges of Simulating EOR and CO2 Storage Projects at Reservoir Scale: Accurate Estimation of Trapped Gas Saturation
One of the first and foremost steps in the feasibility analysis and site selection of geological CO2 storage projects is estimating the storage capacity of the appointed aquifer or depleted reservoir. It has been established that the volume of CO2 stored due to capillary trapping is significantly higher than other active mechanisms. Therefore, an accurate method is required to determine the trapped gas saturation in the system. This method is also of significant importance for simulating any other process involving cyclic injection of fluids in subsurface reservoirs as the hysteresis in relative permeability is a direct function of trapped gas saturation. Examples of the cyclic process in subsurface reservoir engineering are gas storage projects and reservoirs undergoing Enhanced Oil Recovery (EOR) injections. In this study, we present a detailed study of the reservoir scale simulation results using commercial software, and we discuss the challenges observed in calculating the trapped gas saturation. The first challenge is that Land's formulation relates the initial and residual non-wetting saturations measured during an imbibition cycle. However, in many reservoir blocks, the volume and rate of displacing fluid are insufficient to ensure reaching the residual values. Accurate determination of saturation histories in various reservoir grid blocks is also challenging as small oscillations make it hard to identify the flow reversal points. A significant amount of error is introduced in compositional simulations when the composition of trapped gas saturation enters mass transfer calculations, and the trapped gas is dissolved again in the oil phase. Whereas physically, it should be isolated and shielded by the water phase. Finally, an inaccurate definition of saturation-dependent functions can increase the error associated with calculating relative permeability data using trapped gas saturation. In this study, we present a new workflow for calculating the trapped gas saturation, addressing all the abovementioned issues. The backbone of this workflow is an efficient algorithm which removes any oscillation misidentified as a flow reversal point. The results discussed in this paper indicate that the available formulation in the literature should be deployed carefully (considering the active mechanism in the system) to decrease the uncertainties. As a result, the feasibility of EOR methods, the site selection for CO2 storage projects and the decision-making process can be based on more reliable data.
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