The choice of enhanced oil recovery (EOR) methods for specific reservoir conditions is one of the most difficult tasks for a reservoir engineer. Taber (Taber, 1980; Taber et al., 1997a,b) gave informative overview of EOR research history. He also offered technical screening guides for EOR nowadays known as Taber's tables. It should be noted that the approach recommended by Taber could not be taken as strong mathematical ranking of EOR methods. The authors propose an approach for EOR methods selection, based on fuzzy logic, possibility theory, and Bayesian inference mechanisms. Rankings were made by way of best EOR method selection for every criteria using fuzzy intervals comparison. Final correction of each EOR selection coefficient was performed by the generalized Bayesian inference mechanism. Application of this methodology for reservoir conditions of Alberta oil field, as well as the offshore field "Guneshli, " allowed for choosing the most effective EOR method, confirming the accuracy and feasibility of the proposed approach. Simple calculation (not more than five iterations) allows the automation of the process of selecting the most effective EOR method for a particular field.

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The choice of Enhanced Oil Recovery methods for specific reservoir conditions is one of the most difficult tasks for a reservoir engineer. Taber gave informative overview of Enhanced Oil Recovery research history. He also offered technical screening guides for Enhanced Oil Recovery nowadays known as Taber's tables. It should be noted that the approach recommended by Taber could not be taken as strong mathematical ranking of Enhanced Oil Recovery methods. This paper proposes approach for Enhanced Oil Recovery methods selection, based on fuzzy logic, possibility theory and Bayesian inference mechanisms. Ranking made by way of best Enhanced Oil Recovery method selection for every criteria using fuzzy intervals comparison. Final correction of each Enhanced Oil Recovery selection coefficient performs by the generalized Bayesian inference mechanisms. Application of this methodology for reservoir conditions of Alberta oil field allowed choosing the most effective EOR method, confirming the accuracy and feasibility of the proposed approach.

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This paper presents the effect of light-weight metal nanofiller onto compressive strength of polymer gels used in Enhanced Oil Recovery. Non-destructive method based on ultrasonic-wave passing was applied for compressive strength evaluation. The investigations revealed effect gain in strength of gel system by 65% when addition of nanoparticles. The evidence of nanoparticles uniform distribution was utilized by measurements of electrical conductivity changes and percolation task. The kinetic mechanism of nanofiller effect on gel forming and determination of inflection points has been presented and proved. On the basis of polymer consumption due to nanofillers usage, it appears that it is economically efficient.