We targeted high-temperature and highly saline old oil fields, whose environmental conditions could be attributed to the significantly high heterogeneity cause by long-term water flooding. The Huabei Oilfield was chosen as the research object. We developed a hydrophobic functional monomer–polymer with temperature and salt resistance by introducing the temperature-resistant and salt-resistant monomer NVP and a hydrophobic functional monomer into the main chain for copolymerization. We used a crosslinking agent with phenolic resin to prepare a weak gel system that showed temperature and salt resistance and investigated its temperature and salt resistance, infective property, plugging performance, liquid flow ability, micropore throat migration, and plugging characteristics. The results obtained using the infrared spectroscopy technique revealed the successful preparation of the phenolic resin crosslinker. The weak gel exhibited good temperature and salt resistance when the polymer concentration was 2000 mg/L, the cohesion ratio was 1:1.5, the additive concentration was 2000 mg/L, the reservoir temperature was 120 °C, and the injected water salinity was 40,300.86 mg/L. The average viscosity retention rate of the 90-day weak gel reached more than 80% and its microstructure was examined. The coreflow experiment results revealed that the weak gel system was characterized by good infectivity. After plugging the weak gel, the effect on the direction of the liquid flow was evident and the flow rate of the low permeability layer increased to a maximum of 48.63% under conditions of varying permeability levels. A significant improvement in the water absorption profile was achieved. The plugging was carried out through a sand-filling pipe under varying permeability conditions and the pressure measuring points in the sand-filling pipe were sucessfully pressurized. The migration ability of the weak gel was good and the blocking rate was >85%.

This study analyzes the water invasion characteristics and water encroachment of the deep sea bottom-water gas reservoir (LS17 field) in the South China Sea for the purpose of developing horizontal wells. Gas-producing profile tests and a three-dimensional (3D) water invasion simulation are used to produce a quantitative analysis of the bottom-water cresting influence factors. On this basis, we establish a suitable risk identification method for the water influx of a deep bottom-water reservoir. The results show that: (1) During the development of a bottom-water gas reservoir, the water ridging is affected by reservoir heterogeneity, production system and heel–toe effect of a horizontal wellbore, and reservoir heterogeneity is the main influencing factor; (2) the horizontal–vertical ratio of the well area determines whether the gas well productivity will be affected by the risk of water invasion. The stronger the reservoir heterogeneity, the smaller the safety limit value of the horizontal–vertical ratio; (3) when the permeability differential increases gradually, the safety limit value of the transverse longitudinal ratio decreases in turn; (4) based on the relationship curve between permeability level difference and the safety limit value of the horizontal–vertical ratio in the well area, the horizontal–vertical ratio of the N1H well is far greater than the safety limit value. The well is at high risk of water invasion and should be developed by water control. In order to improve deep seabed water and gas reservoirs, water control development should be carried out in well areas with sufficient water energy and high water invasion risk. The water invasion characteristics of bottom-water gas reservoirs under different water control technologies (such as variable density screen technology, filling water blocking, breathable coated gravel technology, etc.) and production systems (periodic gas production technology) should be studied. The research results can not only judge the water invasion risk of deep seabed water and gas reservoirs under different permeability levels and gas production rates but also provide a reference for water control development of offshore and onshore bottom-water and gas reservoirs.

Accurately predicting oilfield development indicators (such as oil production, liquid production, current formation pressure, water cut, oil production rate, recovery rate, cost, profit, etc.) is to realize the rational and scientific development of oilfields, which is an important basis to ensure the stable production of the oilfield. Due to existing oilfield development index prediction methods being difficult to accurately reflect the complex nonlinear problem in the oil field development process, using the artificial neural network, which can predict the oilfield development index with the function of infinitely close to any non-linear function, will be the most ideal prediction method at present. This article summarizes four commonly used artificial neural networks: the BP neural network, the radial basis neural network, the generalized regression neural network, and the wavelet neural network, and mainly introduces their network structure, function types, calculation process and prediction results. Four kinds of artificial neural networks are optimized through various intelligent algorithms, and the principle and essence of optimization are analyzed. Furthermore, the advantages and disadvantages of the four artificial neural networks are summarized and compared. Finally, based on the application of artificial neural networks in other fields and on existing problems, a future development direction is proposed which can serve as a reference and guide for the research on accurate prediction of oilfield development indicators.

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A heavy oil activator is an amphiphilic polymer solution that contains hydrophilic and oleophobic groups. It can enhance heavy oil recovery efficiency. This paper studied the changes in the distribution of the remaining oil after activator flooding and the performance of heavy oil’s active agent. Nuclear magnetic resonance spectroscopy, laser confocal microscopy, microscopic visualization, and CT scanning techniques were used to analyze crude oil utilization, and the distribution characteristics of the remaining oil during activator flooding of heavy oil. The results showed that the heavy oil activator solution presented a dense spatial network and good viscosification ability. The activator could reduce the interfacial tension of oil and water, disassemble the heavy components of dispersed heavy oil and reduce the viscosity of heavy oil. The utilization degree of the remaining oil in small and middle pores increased significantly after activator flooding, the remaining oil associated with membranous-like and clusterlike structures was utilized to a high degree, and the decline of light/heavy fraction in heavy oil slowed down. Heavy oil activator improved the swept volume and displacement efficiency of heavy oil, playing a significant role in improving the extent of recovery of heavy oil reservoirs.