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Low primary recovery factor and rapid production decline necessitates the proposal of enhanced oil recovery methods to mobilize the remaining oil resource of tight reservoirs, especially for oil-wet ones, and wettability alteration by injecting a chemical agent such as a surfactant is a promising option. A discrete-fracture-network-based mathematical model is developed with consideration of the displacement mechanisms and complicated physical-chemical phenomena during EOR by wettability alteration, and this model numerically solved by the fully implicit method. Simulation cases are conducted to investigate the production performance and key factors of cyclic injection of a surfactant. Cyclic injection can significantly improve the production of oil-wet tight reservoirs, and the ultimate recovery factor can be increased by 10 percent. The reason is that a surfactant can alter the wettability of a reservoir from oil wet to medium or even water wet, which triggers spontaneous imbibition and favors oil movement from a matrix into a fracture. Better EOR results can be achieved with decreasing oil viscosity, increasing matrix permeability, or decreasing fracture spacing. Cyclic surfactant injection is applicable to reservoirs with an oil viscosity of less than 7 mPa·s, a matrix permeability bigger than 0.01 mD, or a fracture spacing smaller than 150 m. It is favorable for the wettability alteration method by maintaining capillary pressure and reducing residual oil saturation as much as possible.

Water injectors and polymer injectors coexist after well pattern infilling in some offshore oilfields, which exerts a deep impact on oil exploitation. In order to quantitatively characterize the injected water-polymer perturbation degree and analyze perturbation laws, water-polymer perturbation coefficient is proposed and established by comparing the displacement process of water-polymer coflooding and pure polymer flooding, which quantifies the dynamic change of displacement volume of injected water and polymer, and controlling strategy is discussed correspondingly to improve the development effect of water-polymer coflooding. Finally, a field case is used to demonstrate this new evaluation method. The results show that water-polymer perturbation coefficient has a good correlation with oil increasing, and water-polymer coflooding process can be divided into five stages according polymer perturbation coefficient. In addition, water-polymer coflooding has a better oil increasing effect than pure polymer flooding at the initial stage, but for a long period, development effect of pure polymer flooding is much better. The result has a great significance to quantitatively characterize water-polymer perturbation degree and make adjustment measurements.

Clinical pathways are widely used around the world for providing quality medical treatment and controlling healthcare cost. However, the expert-designed clinical pathways can hardly deal with the variances among hospitals and patients. It calls for more dynamic and adaptive process, which is derived from various clinical data. Topic-based clinical pathway mining is an effective approach to discover a concise process model. Through this approach, the latent topics found by latent Dirichlet allocation (LDA) represent the clinical goals. And process mining methods are used to extract the temporal relations between these topics. However, the topic quality is usually not desirable due to the low performance of the LDA in clinical data. In this paper, we incorporate topic assignment constraint and topic correlation limitation into the LDA to enhance the ability of discovering high-quality topics. Two real-world datasets are used to evaluate the proposed method. The results show that the topics discovered by our method are with higher coherence, informativeness, and coverage than the original LDA. These quality topics are suitable to represent the clinical goals. Also, we illustrate that our method is effective in generating a comprehensive topic-based clinical pathway model.