Polymer degradation is critical for polymer flooding because it can significantly influence the viscosity of a polymer solution, which is a dominant property for polymer enhanced oil recovery (EOR). In this work, physical experiments and numerical simulations were both used to study partially hydrolyzed polyacrylamide (HPAM) degradation and its effect on polymer flooding in heterogeneous reservoirs. First, physical experiments were conducted to determine basic physicochemical properties of the polymer, including viscosity and degradation. Notably, a novel polymer dynamic degradation experiment was recommended in the evaluation process. Then, a new mathematical model was proposed and an in-house three-dimensional (3D) two-phase polymer flooding simulator was designed to examine both polymer static and dynamic degradation. The designed simulator was validated by comparison with the simulation results obtained from commercial software and the results from the polymer flooding experiments. This simulator further investigated and validated polymer degradation and its effect. The results of the physical experiments showed that the viscosity of a polymer solution increases with an increase in polymer concentration, demonstrating their underlying power law relationship. Moreover, the viscosity of a polymer solution with the same polymer concentration decreases with an increase in the shear rate, demonstrating shear thinning. Furthermore, the viscosity of a polymer solution decreased with an increase in time due to polymer degradation, exhibiting an exponential relationship. The first-order dynamic degradation rate constant of 0.0022 day⁻¹ was greater than the first-order static degradation rate constant of 0.0017 day⁻¹. According to the simulation results for the designed simulator, a 7.7% decrease in oil recovery, after a cumulative injection volume of 1.67 pore volume (PV) was observed between the first-order dynamic degradation rate constants of 0 and 0.1 day⁻¹, which indicates that polymer degradation has a detrimental effect on polymer flooding efficiency.

Polymer flooding (PF) in heterogeneous heavy oil reservoirs is not only closely related to polymer degradation, but also to non-Newtonian flow. In this paper, both experimental and simulation methods are combined to investigate this type of flooding. Through experiments, the degradation of polymer, rheological properties of fluids, and flow of fluids in porous media were determined. Based on the experimental results, a novel mathematical model was established, and a new PF simulator was designed, validated, and further applied to study the effects of polymer degradation, polymer solution shear thinning, and non-Newtonian flow on PF in heterogeneous heavy oil reservoirs. These experimental results demonstrated that the polymer first-order static degradation rate constant was lower than the polymer first-order dynamic degradation rate constant; the polymer solution and heavy oil were non-Newtonian fluids, with shear thinning and Bingham fluid properties, respectively; and the heavy oil threshold pressure gradient (TPG) in low-permeability porous media was higher than that in high-permeability porous media. All comparison results showed that the designed simulator was highly accurate and reliable, and could well describe both polymer degradation and non-Newtonian flow, with special emphasis on the distinction between polymer static and dynamic degradation and heavy oil TPG. Furthermore, the simulation results verified that polymer degradation, polymer solution shear thinning, and heavy oil TPG all had negative effects on the efficiency of PF in heterogeneous heavy oil reservoirs.

In this paper, physical experiments and numerical simulations were applied to systematically investigate the non-Newtonian flow characteristics of heavy oil in porous media. Rheological experiments were carried out to determine the rheology of heavy oil. Threshold pressure gradient (TPG) measurement experiments performed by a new micro-flow method and flow experiments were conducted to study the effect of viscosity, permeability and mobility on the flow characteristics of heavy oil. An in-house developed novel simulator considering the non-Newtonian flow was designed based on the experimental investigations. The results from the physical experiments indicated that heavy oil was a Bingham fluid with non-Newtonian flow characteristics, and its viscosity-temperature relationship conformed to the Arrhenius equation. Its viscosity decreased with an increase in temperature and a decrease in asphaltene content. The TPG measurement experiments was impacted by the flow rate, and its critical flow rate was 0.003 mL/min. The TPG decreased as the viscosity decreased or the permeability increased and had a power-law relationship with mobility. In addition, the critical viscosity had a range of 42–54 mPa∙s, above which the TPG existed for a given permeability. The validation of the designed simulator was positive and acceptable when compared to the simulation results run in ECLIPSE V2013.1 and Computer Modelling Group (CMG) V2012 software as well as when compared to the results obtained during physical experiments. The difference between 0.0005 and 0.0750 MPa/m in the TPG showed a decrease of 11.55% in the oil recovery based on the simulation results, which demonstrated the largely adverse impact the TPG had on heavy oil production.

The flow of polymer solution and heavy oil in porous media is critical for polymer flooding in heavy oil reservoirs because it significantly determines the polymer enhanced oil recovery (EOR) and polymer flooding efficiency in heavy oil reservoirs. In this paper, physical experiments and numerical simulations were both applied to investigate the flow of partially hydrolyzed polyacrylamide (HPAM) solution and heavy oil, and their effects on polymer flooding in heavy oil reservoirs. First, physical experiments determined the rheology of the polymer solution and heavy oil and their flow in porous media. Then, a new mathematical model was proposed, and an in-house three-dimensional (3D) two-phase polymer flooding simulator was designed considering the non-Newtonian flow. The designed simulator was validated by comparing its results with those obtained from commercial software and typical polymer flooding experiments. The developed simulator was further applied to investigate the non-Newtonian flow in polymer flooding. The experimental results demonstrated that the flow behavior index of the polymer solution is 0.3655, showing a shear thinning; and heavy oil is a type of Bingham fluid that overcomes a threshold pressure gradient (TPG) to flow in porous media. Furthermore, the validation of the designed simulator was confirmed to possess high accuracy and reliability. According to its simulation results, the decreases of 1.66% and 2.49% in oil recovery are caused by the difference between 0.18 and 1 in the polymer solution flow behavior indexes of the pure polymer flooding (PPF) and typical polymer flooding (TPF), respectively. Moreover, for heavy oil, considering a TPG of 20 times greater than its original value, the oil recoveries of PPF and TPF are reduced by 0.01% and 5.77%, respectively. Furthermore, the combined effect of shear thinning and a threshold pressure gradient results in a greater decrease in oil recovery, with 1.74% and 8.35% for PPF and TPF, respectively. Thus, the non-Newtonian flow has a hugely adverse impact on the performance of polymer flooding in heavy oil reservoirs.

As global energy demand grows, the oil and gas industry faces increasing challenges in optimizing production while achieving sustainability. Accurate oil well production forecasting is essential for effective resource management and operational decision-making. However, traditional mathematical models struggle with the nonlinear and dynamic characteristics of production data, while existing hybrid neural networks often lack sensitivity to operational changes and suffer from overcomplexity due to numerous parameters. This study proposes a novel hybrid model, TCN–KAN, combining temporal convolutional networks (TCN) and Kolmogorov–Arnold networks (KAN), to address these challenges. By integrating feature selection informed by reservoir engineering expertise and Spearman correlation analysis, the model effectively reduces input dimensionality while ensuring physically meaningful feature representation. Experimental results demonstrate the TCN–KAN model’s superior ability to capture nonlinear interactions and long-term temporal dependencies, achieving the highest predictive accuracy among tested models. Additionally, a modified whale optimization algorithm (WOA) is employed for hyperparameter tuning, further enhancing the model’s robustness. Validation on Volvo oil field data (2008–2016) highlights the model’s operational sensitivity and practical value, providing actionable insights for optimizing oilfield management strategies.

Fracture-vuggy carbonate reservoirs commonly exhibit sufficient bottom water energy and are characterized by fractures or other interconnected channels with bottom water, which can easily cause high water cut in oil wells during production. The main reasons are as follows: firstly, bottom water coning leads to water flooding. Secondly, artificial water injection flooding fails and shows high water cut in oil production. This paper further clarifies the causes of high water cut in fractured-vuggy carbonate reservoirs and explores rational and feasible management strategies to improve the current water flooding situation and reduce the comprehensive water cut in oil wells. In this paper, numerical simulation technology is used to establish a mechanism model based on the actual reservoir conditions. By comparing the development effects of four bottom water suppression measures, including the adjustment of flow channel, artificial barriers, adjustment of flow potential and gas injection, the optimal measure is selected and the relevant parameters are optimized. Building upon this, further optimization of water injection methods is conducted to explore comprehensive management strategies for enhancing the water flooding effect during high water cut periods. The research demonstrates that bottom water can be effectively inhibited by artificial barriers, leading to an expansion of the swept volume of water injection and achieving the goal of improving the high water cut condition in carbonate reservoirs. Optimal implementation of artificial barriers occurs when the water cut reaches around 80%. Specifically, positioning barriers at the bottom of perforations and setting the barrier radius at 0.15–0.2 times the well spacing obtain the most favorable results. Additionally, short-term injection with long-term shut-in, identified through cyclic water injection simulations, exhibits superior oil recovery enhancement. Validation conducted in a practical field of a fractured carbonate reservoir over a five-year period has led to a substantial increase in oil production by 5.6 × 10⁴ t and a 12% reduction in water cut. The research approach and methodology presented in this paper can provide valuable insights and serve as a reference for the development of high water cut periods in fractured-vuggy carbonate reservoirs.