Numerical Investigation of Hybrid Carbonated Smart Water Injection (CSWI) in Carbonate Cores

A. Hassan, E. Al-Shalabi, B. Ghosh, B. N. Tackie-Otoo, M. Ayoub, Imad A. Adel
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Abstract

Carbonated smart water injection (CSWI) is a potential hybrid EOR technology under development. The process involves dissolving CO2 in smart water ripping the benefits of the synergic effect of CO2 injection and smart water. Based on the experimental laboratory data, including core flood experiments, this paper presents numerical investigations of the combined impact of dissolving carbon dioxide (CO2) in smart water (SW) on oil recovery in carbonate cores. An advanced processes reservoir simulator was utilized to build a core-scale model. Both the physics of smart water flooding as well as CO2-gas injection were captured. The generated model was validated against the coreflooding experimental data on hybrid CSWI, including cumulative oil production (cc) and oil recovery factor (%). The Corey's correlation relative permeability model was used for capturing the multiphase flow. The numerical model was used to understand the underlying recovery mechanisms and crude oil-brine-rock interactions during CSWI. The model was further utilized to perform sensitivity analysis of different parameters and to optimize the CSWI design. Based on the numerical results, the experimental coreflooding data were accurately history-matched using the proposed model with a minimal error of 8.79% applying the PSO-based optimization method. Moreover, this history-matched model was further used for sensitivity analysis and optimization of the CSWI process. The objective functions for sensitivity analysis and optimization are based on minimizing the history-matching global error and maximizing oil recovery. The optimized design was achieved by performing a sensitivity analysis of various input parameters such as oil and water saturations (Soi and Swi), DTRAP (i.e., relative permeability interpolation parameter). On the other hand, in terms of maximizing the oil recovery while minimizing the usage of injected CSW solutions during CSWI, the optimal solution via the PSO-based approach achieved a cumulative oil recovery of 55.5%. The main mechanism behind additional oil recovery with CSW is due mainly to wettability alteration and ion exchange between rock and brine. Additionally, CSWI was found to be more efficient in releasing trapped oil compared to waterflooding, indicating the synergic effect of dissolved CO2 in SW solutions. Based on this research, the envelope of CSWI application in carbonates for CO2-storage is expected to expand. This study presents one of the few works on numerical modeling of the CSWI process and capturing its effects on oil recovery. The optimized core-scale model can be further used as a base to build a field-scale model. This promising hybrid CSWI process under optimum conditions is expected to be economical and environmentally acceptable, which promotes future field projects.
碳酸盐岩岩心混合碳酸智能注水(CSWI)数值研究
碳酸智能注水技术(CSWI)是一种潜在的混合提高采收率技术。该过程涉及将二氧化碳溶解在智能水中,从而利用二氧化碳注入和智能水的协同效应。基于岩心驱油实验等室内实验数据,对智能水(SW)溶解二氧化碳(CO2)对碳酸盐岩岩心采收率的综合影响进行了数值研究。利用先进的过程油藏模拟器建立岩心尺度模型。智能水驱和二氧化碳注气的物理特性都被捕获。根据混合CSWI岩心驱油实验数据,包括累积产油量(cc)和采收率(%),对生成的模型进行了验证。采用Corey相关相对渗透率模型捕获多相流。该数值模型用于了解CSWI过程中潜在的采收率机制和原油-盐水-岩石相互作用。利用该模型对不同参数进行灵敏度分析,优化CSWI设计。数值结果表明,采用基于粒子群算法的优化方法,该模型能准确匹配岩心驱油实验数据,误差最小为8.79%。并将该历史匹配模型进一步用于CSWI过程的敏感性分析和优化。灵敏度分析和优化的目标函数是基于最小化历史匹配全局误差和最大化石油采收率。通过对油、水饱和度(Soi和Swi)、DTRAP(即相对渗透率插值参数)等各种输入参数进行敏感性分析,实现了优化设计。另一方面,在最大限度地提高采收率的同时,在CSWI过程中尽量减少注入CSW溶液的使用,通过基于pso方法的最佳解决方案实现了55.5%的累计采收率。CSW提高采收率的主要机制主要是由于岩石与盐水之间的润湿性改变和离子交换。此外,与水驱相比,CSWI在释放困油方面更有效,这表明了SW溶液中溶解的二氧化碳的协同效应。基于该研究,CSWI在碳酸盐中用于二氧化碳储存的应用范围有望扩大。本研究是为数不多的对CSWI过程进行数值模拟并捕捉其对石油采收率影响的工作之一。优化后的核心尺度模型可进一步作为构建场尺度模型的基础。在最佳条件下,这种有前途的混合CSWI工艺有望实现经济和环境可接受,从而促进未来的现场项目。
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