hamidreza jahangiri

One of the most important methods of increasing extraction from carbonate reservoirs is to change the wettability of the reservoir rock with the emergence of nanotechnology, which played a significant role in the framework of methods of increasing Oil Recovery. The purpose of this project is to use nanofluids containing inorganic nanoparticles, which are economical and environmentally friendly. For this purpose, first, 3 types of inorganic nanoparticles SiO₂, Al₂O₃ and TiO₂, which were converted into nanometer size powder by mechanical method (Ball mill). Then, 3 nanofluids containing SiO₂, Al₂O₃ and TiO₂ were prepared along with dispersants and stabilizers. By performing the contact angle test, it was found that the contact angle of the oil drop on the oil-wet carbonate rock changed from 132.1° to 87.1° after coating with nanofluid with a concentration of at least 0.01 wt.%. Then the optimal concentration of nano fluid and the optimal time of thin section aging in nano fluid were determined, and the values of these parameters were 0.01% by weight and 7 days, respectively. In the following, it was shown that the stone coated with these nanofluids maintains its wettability well. Based on the interfacial tension test, it was shown that the interfacial tension decreased from 24.029 mN/m (water and oil) to 4 mN/m (nanofluid and oil) at ambient temperature. Finally, by conducting the Core Flooding test on the oil wet plugs, the investigations show that in the flooding test, the volume of extracted oil increased by 42.06% in the case of water injection to 60.09% in the case of nanofluid injection. (Residual oil decreased from 9.64 cm³ to 6.64 cm³ respectively.) In fact, the flooding recovery factor increased by 18% compared to the previous state.

Optimal reservoir management, modeling and production, depend on understanding the connectivity between production wells in an oil reservoir. Using numerical simulation and a reservoir permeability map can clear this feature, however, it is a time-consuming method and the presence of uncertainty in the input data of simulators leads to employ other methods to understand the feature. Having new sensors that are permanently placed in the wellbore, large amounts of production data (production rate and bottom hole pressure) are available. In recent years, intelligent data-driven techniques have been used to work with the large amount of data obtained from production wells. This paper uses a data-driven approach based on detecting important production well events during its production life. Important well events are divided into three categories: (1) increasing, (2) decreasing, and (3) no flow (shut in the well by operator). These events are identified using derivative and slope of the production figures and some limiting factors. Afterwards, the algorithm has to find the related events between the production wells, and based on the importance of the events, the inter-well connectivity among production wells is determined which it is shown as a connectivity map. A synthetic reservoir was first developed in the Eclipse simulation software, and the three high-permeability streaks were considered between three well pairs. Next, its production data were used as the data-driven model’s input, which it is programmed in MATLAB software, in order to identify the three high-permeability streaks via the data-driven model.