In practical applications, the chemical and physical adsorption of a polymer solution greatly affects its action mode and effect. Understanding the adsorption mechanism and its influencing factors can help to optimize the application mode and ensure application efficiency. Three types of polymer solutions—partially hydrolyzed polyacrylamide (HPAM), hydrophobically associating polymer (AP-P4), and dendrimer hydrophobically associating polymer (DHAP), which are viscoelastic liquids—were used as sorbates to study their adsorption by a sorbent such as quartz sand. The effects of the solution concentration, contact time, particle size of quartz sand, solid–liquid ratio, and fluid movement on the adsorption capacity of the polymer solutions were examined. The results showed that HPAM presents a typical Langmuir monolayer adsorption characteristic, and its adsorption capacity (per unit area) is 1.17–1.62 μg/cm². The association enhances the interactions of the AP-P4 and DHAP solutions, and they present multilayer characteristics of first-order chemical adsorption and secondary physical molecule adsorption. Moreover, the dendrite structure further increases the adsorption thickness of DHAP. Hence, the adsorption thicknesses of AP-P4 and DHAP are four and six times that of HPAM, respectively. The adsorption of the three polymers is consistent with the influence of fluid motion and decreases with increasing fluid velocity. However, the larger the thickness of the adsorption layer, the clearer the influence of the flow, and the higher the decrease in adsorption capacity. Optimizing the injection rate is an effective method to control the applications of a polymer in porous media.

Polymer flooding has been proven to effectively improve oil recovery in the Bohai Oil Field. However, due to high oil viscosity and significant formation heterogeneity, it is necessary to further improve the displacement effectiveness of polymer flooding in heavy oil reservoirs in the service life of offshore platforms. In this paper, the effects of the water/oil mobility ratio in heavy oil reservoirs and the dimensionless oil productivity index on polymer flooding effectiveness were studied utilizing relative permeability curves. The results showed that when the water saturation was less than the value, where the water/oil mobility ratio was equal to 1, polymer flooding could effectively control the increase of fractional water flow, which meant that the upper limit of water/oil ratio suitable for polymer flooding should be the value when the water/oil mobility ratio was equal to 1. Mean while, by injecting a certain volume of water to create water channels in the reservoir, the polymer flooding would be the most effective in improving sweep efficiency, and lower the fractional flow of water to the value corresponding to \( \Delta \,J_{\hbox{max} } \) . Considering the service life of the platform and the polymer mobility control capacity, the best polymer injection timing for heavy oil reservoirs was optimized. It has been tested for reservoirs with crude oil viscosity of 123 and 70 mPa s, the optimum polymer flooding effectiveness could be obtained when the polymer floods were initiated at the time when the fractional flow of water were 10 % and 25 %, respectively. The injection timing range for polymer flooding was also theoretically analyzed for the Bohai Oil Field utilizing relative permeability curves, which provided methods for improving polymer flooding effectiveness.

Polymer flooding is one of the techniques used to enhance oil recovery from depleted hydrocarbon reservoirs. Although this technology is popular for this application, the shearing effect in the injection process causes poor performance, which is an obstacle to meeting the needs of the formation. An experimental evaluation of the rheological properties, viscoelasticity, hydrodynamic size, static adsorption, and seepage characteristics of the associated polymer solution before and after shearing was conducted to determine the influence of shearing on the polymer solution. The results show that the effect of shear on the polymer was irreversible, and the properties of the polymer solution damaged by shear were attenuated. After the critical associating concentration, the associated polymer can recover its solution properties through hydrophobic association, which can improve the shear resistance of the polymer solution and make its own rheological law and reduce the viscoelastic change. Although the hydrodynamic size, viscoelasticity, and adsorption capacity of the polymer solution after shear failure decreased, strong flow resistance during porous media seepage and mobility control was achieved. Improving the shear resistance of the polymer solution by increasing the intermolecular force is proposed to develop new polymer systems for subsequent oil displacement.

The polymer solution for oil displacement is subjected to strong shear action in practical application, and this action will affect its percolation characteristics in porous media. The effects of mechanical shearing on the solution properties and seepage characteristics of modified hydrophobically associated polymers and dendrimers with two different aggregation behaviours were studied. The results showed that mechanical shearing did not affect hydrophobic microzones. Polymers can re-associate to restore part of the network structure, thereby improving shear resistance (dendritic hydrophobically associating polymers > hydrophobically modified partially hydrolysed polyacrylamide). Polymers with ‘cluster’ aggregation behaviour enhanced solution performance, enabling them to establish higher resistance coefficient (RF) and residual resistance factor (RRF) in porous media but also bringing about injection difficulties. Increasing the injection rate would increase the injection pressure, but the established RF and RRF showed a downward trend. Mechanical shear pretreatment effectively improved the injectability of the polymer. To achieve polymer injection and flow control, pre-shearing polymer solution and low-speed injection can be used in field applications.

To predict the natural gas hydrate formation conditions quickly and accurately, a novel hybrid genetic algorithm–support vector machine (GA-SVM) model was developed. The input variables of the model are the relative molecular weight of the natural gas (M) and the hydrate formation pressure (P). The output variable is the hydrate formation temperature (T). Among 10 gas samples, 457 of 688 data points were used for training to identify the optimal support vector machine (SVM) model structure. The remaining 231 data points were used to evaluate the generalisation capability of the best trained SVM model. Comparisons with nine other models and analysis of the outlier detection revealed that the GA-SVM model had the smallest average absolute relative deviation (0.04%). Additionally, the proposed GA-SVM model had the smallest amount of outlier data and the best stability in predicting the gas hydrate formation conditions in the gas relative molecular weight range of 15.64–28.97 g/mol and the natural gas pressure range of 367.65–33,948.90 kPa. The present study provides a new approach for accurately predicting the gas hydrate formation conditions.