Permeability is one of the most important parameters of reservoir rocks, it illustrates the capacity of rock to transmit fluids (oil, gas, water) in pore spaces. Permeability data can be obtained from routine core analysis in laboratory on 1.5 in plugs and sidewall core. However, coring is limited due to cost issue, so permeability prediction in uncored sections play a significantly important role. The variety of methods developed to estimate permeability using pore scale such as Kozeny-Carman, Swanson and Pittman. In fact, those equations are applied individually to estimate permeability. In this research, permeability estimation methods will be used on the same rock (sandstone or carbonate rock) to detect the suitable method for each rock type. Porosity, permeability data from routine core analysis and pore throat size from mercury injection capillary pressure on sandstone and carbonate rocks from Cuu Long and Song Hong basins in Vietnam will be gathered and permeability estimation conducted by using Hydraulic Flow Unit (HFU), Mercury Injection Capillary Pressure (MICP) and Pittman methods based on that data. Estimated permeability obtained from each methods will be compared with core permeability, the method with the highest R-squared be selected. The research shows that Hydraulic Flow Unit is the most suitable methods for permeability prediction on sandstone with R-squared > 0.9. On the other hand, mercury injection capillary pressure is the most accurate method to estimate permeability on carbonate rocks related to heterogeneity and complicated pore system. That results will help engineers have a fast and accurate decision for permeability prediction methods selection on sandstone and carbonate rocks. In addition, the empirical equations were derived to predict permeability on sandstone and carbonate rocks with the highest coefficient of correlation in multiple regression analysis and based on the relationship between porosity, permeability and pore throat size.

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The Proportional Navigation (PN) is one of the most successful and widely applied conductive rules in the field of guidance since from the innitial days of its proposal. The success of PN comes from very early by the simplicity and ease of actualization and the especially important reason that leads to the success of the PN is permanent or poor maneuverability target. However, with the development in aerospace science, the maneuverability of flying vehicles is constantly improving. This causes PN to reveal its disadvantages, reduce its accuracy when sticking and attacking mobile targets. The paper presents a guidance rule based on fuzzy logic on basis of Particle Swarm Optimization (PSO) algorithm. The proposed guidance rule (FPSOG) is simulated according to PN to exploit the advantages of PN but still ensure the optimal and flexible design by fuzzy logic and PSO algorithm. The results of the completion process of FPSOG were investigated and compared with PN and pure Fuzzy Proportional Navigation (FPN) rule MATLAB software.