Zhao Ling, Sun Xianda, Zhang Huili, Xu Chengwu, Sui Xin, Qin Xudong, Zeng Maokun
College of Computer and Information Technology, Northeast Petroleum University, Daqing 163318, China.
State Key Laboratory of Continental Shale Oil, Northeast Petroleum University, Daqing 163318, China.
Polymers (Basel). 2024 Sep 29;16(19):2757. doi: 10.3390/polym16192757.
As a non-renewable resource, oil faces increasing demand, and the remaining oil recovery rates in existing oil fields still require improvement. The primary objective of this study is to investigate the impact of pore structure parameters on the distribution and recovery of residual oil after polymer flooding by constructing a digital pore network model. Using this model, the study visualizes the post-flooding state of the model with 3DMAX-9.0 software and employs a range of simulation methods, including a detailed analysis of the pore size, coordination number, pore-throat ratio, and wettability, to quantitatively assess how these parameters affect the residual oil distribution and recovery. The research shows that the change in the distribution of pore sizes leads to a decrease in cluster-shaped residual oil and an increase in columnar residual oil. An increase in the coordination number increases the core permeability and reduces the residual oil; for example, when the coordination number increases from 4.3 to 6, the polymer flooding recovery rate increases from 24.57% to 30.44%. An increase in the pore-throat ratio reduces the permeability and causes more residual oil to remain in the throat; for example, when the pore-throat ratio increases from 3.2 to 6.3, the total recovery rate decreases from 74.34% to 63.72%. When the wettability changes from oil-wet to water-wet, the type of residual oil gradually changes from the difficult-to-drive-out columnar and film-shaped to the more easily recoverable cluster-shaped; for example, when the proportion of water-wet throats increases from 0.1:0.9 to 0.6:0.4, the water flooding recovery rate increases from 35.63% to 51.35%. Both qualitative and quantitative results suggest that the digital pore network model developed in this study effectively predicts the residual oil distribution under different pore structures and provides a crucial basis for optimizing residual oil recovery strategies.
作为一种不可再生资源，石油面临着不断增长的需求，而现有油田的剩余油采收率仍有待提高。本研究的主要目的是通过构建数字孔隙网络模型，研究孔隙结构参数对聚合物驱后剩余油分布和采收率的影响。利用该模型，本研究使用3DMAX - 9.0软件对模型的驱替后状态进行可视化，并采用一系列模拟方法，包括对孔径、配位数、孔喉比和润湿性的详细分析，以定量评估这些参数如何影响剩余油分布和采收率。研究表明，孔径分布的变化导致簇状剩余油减少，柱状剩余油增加。配位数的增加会提高岩心渗透率并降低剩余油；例如，当配位数从4.3增加到6时，聚合物驱采收率从24.57%提高到30.44%。孔喉比的增加会降低渗透率，并导致更多的剩余油滞留在喉道中；例如，当孔喉比从3.2增加到6.3时，总采收率从74.34%降至63.72%。当润湿性从油湿变为水湿时，剩余油类型逐渐从难以驱出的柱状和膜状变为更容易采收的簇状；例如，当水湿喉道比例从0.1:0.9增加到0.6:0.4时，水驱采收率从35.63%提高到51.35%。定性和定量结果均表明，本研究开发的数字孔隙网络模型能够有效预测不同孔隙结构下的剩余油分布，为优化剩余油采收策略提供了关键依据。
