Experimental simulation study on influencing factors of liquid production capacity in heterogeneous water drive reservoirs

Abstract

Oilfield development involves a complex, dynamic flow process of oil and water, with reservoir characteristics and environmental conditions continually evolving as the field evolves. Particularly when a waterflooding reservoir reaches a stage of ultra-high water cut, prolonged waterflooding intensifies challenges in reservoir development: the exacerbation of reservoir heterogeneity and development behaviors disrupts the initial understanding of the reservoir's liquid production capacity from current development conditions. Thus, it becomes imperative to adjust the productivity prediction methods for oil wells in heterogeneous waterflooding reservoirs. Leveraging the flow simulation of reservoir micro channel networks, and integrating features such as the geometric characteristics of the reservoir percolation field, micro channel characteristics, interlayer differences of mixed layers, degree of plane heterogeneity, production pressure differentials, and fluid properties, a visual sand filling experimental model is established that adheres to specific similarity criteria. Using this sand filling experimental model, we simulate the percolation characteristics of oil–water two-phase flow during the waterflooding process, and uncover the diverse influencing factors and their varying degrees of impact on the oil-phase flow during this waterflooding phase. Qualitative and semi-quantitative percolation simulation experiments are employed to intuitively demonstrate the interlayer interference, degree of plane heterogeneity, and oil–water distribution in heterogeneous reservoirs, which influence the change in oil well productivity during waterflooding. This lays bare the microscopic percolation mechanisms behind the productivity changes in heterogeneous waterflooding reservoirs. The simulation experiment results show that the higher the permeability, the stronger the micro-heterogeneity, and the smaller the overall mobility increase after flooding, the smaller the JLDmax obtained by testing or calculation. At the same permeability, the greater the driving pressure difference, the greater the microscopic sweep coefficient within the pore network, and the greater the mobility increase after flooding, the greater the JLDmax. There is interlayer interference in commingled mining, and the higher the permeability of the high-permeability layer (the greater the interlayer difference), the higher the initial productivity of the commingled well. However, due to the high permeability layer being prone to flooding, resulting in ineffective water circulation, the low-permeability tube is difficult to completely flood, resulting in a small increase in overall mobility, and therefore, JLDmax is small. Water drive preferentially breaks through the high permeability zone on the plane, and the shape of the water drive sweep zone is controlled by the planar permeability gradient, the width of the high permeability zone, and the displacement pressure difference.

Experimental Study on Factors Affecting Oil Recovery in Sandstone-Buried Hill Superimposed Reservoirs

“…Due to their unique geological characteristics and relatively high oil reserves, these types of reservoirs have increasingly attracted attention. − The connectivity between reservoirs, the heterogeneity, and the strategy of development are the critical factors affecting the efficacy of reservoir exploitation. − Reservoir connectivity can be determined by comparing the differences in well logging curves across various strata between adjacent oil and water wells . It can also be assessed by introducing tracers and detecting their production within the same well group unit to understand the connectivity between injection and production wells. − Additionally, it can be conducted using data inversion methods. − Studies on the impact of interlayer heterogeneity and development methods on development effectiveness can utilize numerical simulations, physical simulations, and mechanistic research, among other strategies. − …”

“… 18 − 20 Studies on the impact of interlayer heterogeneity and development methods on development effectiveness can utilize numerical simulations, physical simulations, and mechanistic research, among other strategies. 21 − 25 …”