Asphaltene deposition is a common phenomenon during CO₂ flooding in ultralow permeability reservoirs. The deposited asphaltene occupies the pore volume and decreases permeability, resulting in serious formation damage and pore well productivity. It is urgent to investigate the asphaltene deposition mechanisms, adverse effects, and preventive measures. However, few asphaltene deposition investigations have been systematically conducted by now. In this research, the asphaltene precipitation mechanisms and adverse effects were comprehensively investigated by using experimental and numerical methods. To study the effects of pressure, asphaltene content, and temperature on asphaltene precipitation qualitatively and quantitatively, the microscope visible detection experiment and the PVT cell static experiment were firstly conducted. The adverse effects on porosity and permeability resulted from asphaltene deposition were also studied by the core flooding experiment. Secondly, simulation models of asphaltene precipitation and deposition were developed and validated by experimental data. Finally, a case study from Changqing oil field was presented to analyze the asphaltene deposition characteristic and preventive measures. The experimental results showed that the asphaltene precipitation increases with the increased pressure before reaching the minimum miscible pressure (MMP) and gets the peak value around the MMP, while decreases slowly. The asphaltene precipitation increases with the increased temperature and asphaltene content. The variation trend of adverse effects on porosity and permeability resulted from asphaltene deposition is similar to that of asphaltene precipitation under the influence of pressure, asphaltene content, and temperature. The case study shows that the water-altering-gas (WAG) with high injection rate suffers more serious asphaltene deposition compared with the WAG with low injection rate, for the asphaltene precipitation increases as the increased pressure before reaching the MMP. The CO₂ continuous injection with high injection rate is the worst choice, for low sweep efficiency and the most severe formation damage. Thus, the WAG with optimal injection rate was proposed to maintain well productivity and to reduce formation damage resulted from asphaltene deposition during developing ultralow permeability reservoirs.

The CO₂ flooding with superior displacement efficiency and high injectivity is an efficient enhanced oil recovery method. However, due to the unfavorable sweep efficiency particularly for strong heterogeneous reservoirs and immiscible flooding, the oil recovery on site is not all favorable. Multi-well rates optimization is one of common measures improving sweep efficiency with easy implement and low cost There are many rates optimization methods have been proposed by now. In this research, we first introduced the multi-agent deep deterministic policy gradient (MADDPG) algorithm to the multi-well rates optimization of CO₂ flooding, and the new rates optimization method was built. The MADDPG adopts the centralized training and decentralized execution algorithm framework, and overcomes the defect that the single-agent reinforcement learning cannot deal the multi-well rates optimization well and also avoids the dimensional disaster problems. We treated each well as an agent, and each agent has its own reward, state and action. We chose the net present value (NPV) as the reward, the injection-production rate change range as the action element, and the production time, the bottom hole pressure, the oil production rate, and the gas-oil ratio as the state elements. The simulation results show that the optimal case obviously improves the NPV compared with the base case, and the simulation case with strong heterogeneity and immiscible flooding can also converge to the optimal target, which prove the effectiveness and robustness of the rates optimization method respectively. This research provides recommendations that improving the oil recovery by increasing the sweep efficiency to increase the income, and reducing the invalid CO₂ injection to decrease the cost can achieve the optimal NPV. Reservoir heterogeneity seriously impairs the rates optimization performance, and rates optimization makes little difference to extreme strong interlayer heterogeneity for serious interlayer influence.

The CO₂ huff-n-puff is an effective substitute technology to further improve oil recovery of natural fractured tight oil reservoirs after water flooding, for its high displacement efficiency and superior injectivity. The CO₂ huff-n-puff process is influenced by many factors, such as miscible degree, complex fracture networks, and production schemes. What is worse, those influence facts affect each other making the process more complex. Many researchers concentrated on mechanisms and single sensitivity analysis of CO₂ huff-n-puff process, whereas few optimized this process with the consideration of all influence factors and multiobjective to get favorable performance. We built multiobjective consisted of miscible degree, oil recovery, and gas replacing oil rate considering the aspects of CO₂ flooding special characteristic, technical effectiveness, and economic feasibility, respectively. We have taken Yuan 284 tight oil block as a case, firstly investigated sensitivity analysis, and then optimized CO₂ huff-n-puff process using orthogonal experiment design with multifactors and multiobjectives. The optimization results show CO₂ huff-n-puff can significantly improve oil recovery by 8.87 original oil in place (OOIP) compared with water flooding, which offers guidelines for field operations.