Journal of Oil, Gas and Petrochemical Technology
سال دهم شماره 1 (Winter and Spring 2023)

To avoid drilling damages, it is very important to determine the field stress. Prediction of elastic parameters such as Poisson's ratio and Young's modulus is of great importance in determining in-situ stress and completing geomechanical modeling. These parameters are calculated statically through laboratory tests on drilling cores or dynamically through log data. However, such data may not be available in the oil field data-bank. Therefore, Daily Drilling Reports (DDR) can be introduced as a suitable alternative for predicting rock’s elastic modulus. In this study, for the first time, an attempt has been made to estimate the Dynamic Young’s modulus using DDR data with the application of a variety of conventional machine learning methods. In this regard, linear, support vector machine (SVM), artificial neural network (ANN), Random Forest (RF) LSBoost, and Baysian have been used. Input data to these algorithms also include depth, string rotary speed (RPM), rate of penetration (ROP), weight on bit (WOB), density (RHOB), porosity (Φ), pump pressure (PP), and tangential velocity (TV). Each of these algorithms was then compared in terms of accuracy using correlation coefficient (R2), mean squared error (MSE), and root mean square error (RMSE) criteria. Finally, using conventional experimental correlations and using core data, the resulting values were converted to static values. The results show that using daily drilling reports, based on the above criteria, a good estimate of the elastic parameters can be achieved. Also, among the methods used, Baysian and LSBoost methods have slightly higher and better accuracy than other methods.

Using Corey model for determining relative permeability in a two-phase flow in porous media has been a remarkable achievement; however, determining the correct exponents for relative permeability to oil and water still remains a challenge. In addition, laboratory obtained relative permeability data is very essential because it is more reliable despite being tedious and expensive. In this work, laboratory relative permeability values were obtained with exponents of 3.39 and 3.22 for Kro and Krw respectively as against the closest Corey exponents of 3.3 and 3.2 for Kro and Krw respectively. These results and the assumed Corey exponents of 3.5 and 3.1 for Kro and Krw respectively selected in error were used to show how seemingly insignificant errors in Corey exponents can be magnified when used for calculations in reservoir studies. Therefore, in this study obtaining laboratory relative permeability data is emphasized since it captures most rock properties that affect relative permeability which Corey models do not consider.

Liquid blockage decreases gas condensate productivity when the reservoir pressure near the wellbore falls below the dew point. Wettability alteration is the most promising method among various techniques to overcome the liquid blockage. In this study, the ability of different chemical solutions to change the wettability of rock types; carbonate and synthetic rocks from liquid-wet to a gas-wetting state was investigated. Contact angle measurement was conducted to evaluate the effect of the treating process. It was found that some of the best solutions containing COUPSYL®WRS nanofluid, PTFE, hydrophobic SiO2 nanoparticles + PDMS, could change the water contact angle from 0° to 130.5°, 142.7°, and 155°, respectively. They could also produce water repellency conditions. In contrast, they were not effective on the synthetic rock surface. Moreover, the contact angle of condensate did not change by using these chemicals and remained at 0°. It was also shown that by increasing SiO2 nanoparticle concentration from 0 to 2 wt%, the water contact angle increased from 117° to 155°, which was the most effective chemical solution in the wettability alteration process.

Asphaltene precipitation and deposition in oil reservoirs, wells, transportation, and refineries pose severe problems. Thus, it is important to evaluate its influence by using cutting-edge techniques such as surface treatment. The purpose of the current investigation is to demonstrate how the alteration of casings composition can influence the threshold at which asphaltene can be dislodged from the well column. This can be accompolished by changing surface energy properties. To evaluate the kinetic changes in the removal velocities of asphaltene particles, the intermolecular asphaltene-oil-casing adhesive forces were calculated using the surface energy characteristics of the casings. A study on the experimental size distribution of asphaltene particles was also conducted as a supplement to the theory of surface energy. The mean size of asphaltene particles decreased from 0.6 to 0.4 microns in live oil while the pressure decreased from 5500-4500 psia at 80°C for 260 minutes, before reaching an asumptote. The results showed that particle rebound has a significant impact on the critical velocity of asphaltene removal from the well column which are profoundly influenced by the casing substrate. This can be considered as a viable physical-based surface treatment method to mitigate the deposition of asphaltene in well columns.

In this study, a three-dimensional model was examined for the evaluation of CO2 diffusivity in pure water and silicon oxide, aluminum oxide and titanium oxide nanofluids with the concentrations of 0.05, 0.1, and 0.2 wt%, respectively. Different parameters such as temperature and the nanoparticles weight percentage on CO2 diffusivity in a diffusivity cell were studied in COMSOL software. Next, CO2 diffusivity was compared with the experimental results. The modeling results showed that water was saturated with gas at 36,000 seconds, and the highest amount of absorbed gas happened at 0.32 m. The CFD results were then validated with the experimental data. Furthermore, temperature was found to have a significant effect on the diffusivity, and it improved by increasing nanofluid concentration until the critical value of 0.1 wt% in all conditions. Moreover, TiO2 NF was introduced as an appropriate nanofluid for the phenomenon of mass diffusivity.

The main goal of this study is to simulate the polymer injection test using previously synthesized sulfonated acrylamide copolymer namely, acrylamide/2-acrylamido-2-methylpropane sulfonic acid (AM/AMPS). Phase-field approach was applied for the simulation studies. Tuning parameters of this simulation study were interfacial tension (2×10-6 N/m) and the contact surface thickness (0.305mm). The reported contact angle was 40° for the tuned model. Comsol Multiphysics software was applied for the simulation. The selected polymer solution was prepared using equal ratios of AM and AMPS polymers, namely AMP55 with concentration of 2000 ppm and the injection test was performed in micromodel. The recovery factor for the experimental and modeling studies, were reported 26.91% and 29.4%, respectively, which represented a good agreement between experimental and simulation studies. The effective injection test parameters on oil recovery factor for polymer flooding experiments were investigated, including injection rate, copolymer solution viscosity, and the wettability of the porous media. The results were represented in a mathematical relation showing the relative effect of each parameter on the oil recovery factor.