Rosado-Vázquez Francisco Javier, Bashbush-Bauza José Luis, López-Ramírez Simón
Departamento de Ingeniería Petrolera, Facultad de Ingeniería, Universidad Nacional Autónoma de México, Ciudad Universitaria, 04510 Mexico City, Mexico.
Departamento de Ingeniería Química/USIP, Facultad de Química, Universidad Nacional Autónoma de México, Ciudad Universitaria, 04510 Mexico City, Mexico.
ACS Omega. 2022 Jul 12;7(29):24982-25002. doi: 10.1021/acsomega.2c00277. eCollection 2022 Jul 26.
Polymer flooding is one of the most used chemical enhanced oil recovery (CEOR) technologies worldwide. Because of its commercial success at the field scale, there has been an increasing interest to expand its applicability to more unfavorable mobility ratio conditions, such as more viscous oil. Therefore, an important requirement of success is to find a set of design parameters that balance material requirements and petroleum recovery benefits in a cost-effective manner. Then, prediction of oil recovery turns out to handle more detailed information and time-consuming field reservoir simulation. Thus, for an effective enhanced oil recovery project management, a quick and feasible tool is needed to identify projects for polymer flooding applications, without giving up key physical and chemical phenomena related to the recovery process and avoiding activities or projects that have no hope of achieving adequate profitability. A detailed one-dimensional mathematical model for multiphase compositional polymer flooding is presented. The mathematical formulation is based on fractional flow theory, and as a function of fluid saturation and chemical compositions, it considers phenomena such as rheology behavior (shear thinning and shear thickening), salinity variations, permeability reduction, and polymer adsorption. Moreover, by setting proper boundary and initial conditions, the formulation can model different polymer injection strategies such as slug or continuous injection. A numerical model based on finite-difference formulation with a fully implicit scheme was derived to solve the system of nonlinear equations. The validation of the numerical algorithm is verified through analytical solutions, coreflood laboratory experiments, and a CMG-STARS numerical model for waterflooding and polymer flooding. In this work, key aspects to be considered for optimum strategies that would help increase polymer flooding effectiveness are also investigated. For that purpose, the simulation tool developed is used to analyze the effects of polymer and salinity concentrations, the dependence of apparent aqueous viscosity on the shear rate, permeability reduction, reversible-irreversible polymer adsorption, polymer injection strategies on petroleum recovery, and the flow dynamics along porous media. The practical tool and analysis help connect math with physics, facilitating the upscaling from laboratory observations to field application with a better-fitted numerical simulation model, that contributes to determine favorable scenarios, and thus, it could assist engineers to understand how key parameters affect oil recovery without performing time-consuming CEOR simulations.
聚合物驱油是全球应用最广泛的化学强化采油(CEOR)技术之一。由于其在油田规模上取得了商业成功,人们越来越有兴趣将其适用性扩展到更不利的流度比条件,例如针对更稠的原油。因此,成功的一个重要要求是找到一组设计参数,以经济有效的方式平衡材料需求和石油采收效益。那么,预测原油采收率就需要处理更详细的信息并且要进行耗时的油藏数值模拟。因此,为了进行有效的强化采油项目管理,需要一个快速且可行的工具来确定聚合物驱油应用的项目,同时不放弃与采收过程相关的关键物理和化学现象,并避免那些没有希望实现足够盈利能力的活动或项目。本文提出了一个用于多相组成聚合物驱油的详细一维数学模型。该数学公式基于分流理论,并且作为流体饱和度和化学成分的函数,它考虑了诸如流变行为(剪切变稀和剪切增稠)、盐度变化、渗透率降低以及聚合物吸附等现象。此外,通过设置适当的边界条件和初始条件,该公式可以模拟不同的聚合物注入策略,例如段塞注入或连续注入。推导了一个基于有限差分公式和全隐式格式的数值模型来求解非线性方程组。通过解析解、岩心驱替实验室实验以及用于水驱和聚合物驱的CMG-STARS数值模型对数值算法进行了验证。在这项工作中,还研究了有助于提高聚合物驱油效果的最优策略应考虑的关键因素。为此,所开发的模拟工具用于分析聚合物和盐度浓度的影响、表观水粘度对剪切速率的依赖性、渗透率降低、可逆 - 不可逆聚合物吸附、聚合物注入策略对石油采收的影响以及沿多孔介质的流动动力学。这个实用工具和分析有助于将数学与物理联系起来,通过一个拟合效果更好的数值模拟模型促进从实验室观测到现场应用的尺度提升,这有助于确定有利的情况,从而可以帮助工程师理解关键参数如何影响原油采收,而无需进行耗时的化学强化采油模拟。