Sharif Digital Repository

Dew-point pressure is one of the most important quantities for characterizing and successful prediction of the future performance of gas condensate reservoirs. The objective of this study is to present a reliable, computer-based predictive model for prediction of dew-point pressure in gas condensate reservoirs. An intelligent approach based on least square support vector machine (LSSVM) modeling was developed for this purpose. To this end, the model was developed and tested using a total set of 562 experimental data points from different retrograde gas condensate fluids covering a wide range of variables. Coupled simulated annealing (CSA) was employed for optimization of hyper-parameters of... 

Bubble point pressure is a crucial PVT parameter of reservoir fluids, which has a significant effect on oil field development strategies, reservoir evaluation and production calculations. This communication presents a new mathematical model to calculate the saturation pressures of crude oils as a function of temperature, hydrocarbon and non-hydrocarbon reservoir fluid compositions, and characteristics of the heptane-plus fraction. The model was developed and tested using a total set of 130 experimentally measured compositions and saturation pressures of crude oil samples from different geographical locations covering wide ranges of crude oil properties and reservoir temperatures. In-depth... 

Multiple contact miscible floods such as injection of relatively inexpensive gases into oil reservoirs are considered as well-established enhanced oil recovery (EOR) techniques for conventional reservoirs. A fundamental factor in the design of gas injection project is the minimum miscibility pressure (MMP), whereas local sweep efficiency from gas injection is very much dependent on the MMP. Slim tube displacements, and rising bubble apparatus (RBA) are two main tests that are used for experimentally determination of MMP but these tests are both costly and time consuming. Hence, searching for quick and accurate mathematical determination of gas-oil MMP is inevitable. The objective of this... 

Appropriate execution of drilling operation, in particular for high pressure and high temperature wells, requires accurate knowledge of behavior of the drilling fluid density as a function of pressure and temperature. In this communication, a novel mathematicalbased approach is presented to develop a reliable model for predict the density of four drilling fluid including water-based, oil-based, Colloidal Gas Aphron (CGA) and synthetic. To pursue our objective, a predictive model is proposed using a robust soft computing approach namely least square support vector machine (LSSVM) modeling optimized with coupled simulated annealing (CSA) optimization tool. Moreover, leverage approach, in which... 

Precipitation and scaling of calcium sulfate have been known as major problems facing process industries and oilfield operations. Most scale prediction models are based on aqueous thermodynamics and solubility behavior of salts in aqueous electrolyte solutions. There is yet a huge interest in developing reliable, simple, and accurate solubility prediction models. In this study, a comprehensive model based on least-squares support vector machine (LS-SVM) is presented, which is mainly devoted to calcium sulfate dihydrate (or gypsum) solubility in aqueous solutions of mixed electrolytes covering wide temperature ranges. In this respect, an aggregate of 880 experimental data were gathered from... 

Viscosity of crude oil is a fundamental factor in simulating reservoirs, forecasting production as well as planning thermal enhanced oil recovery methods which make its accurate determination necessary. Experimental determination of reservoir oil viscosity is costly and time consuming. Hence, searching for quick and accurate determination of reservoir oil viscosity is inevitable. The objective of this study is to present a reliable, and predictive model namely, Least-Squares Support Vector Machine (LSSVM) to predict reservoir oil viscosity. To this end, three LSSVM models have been developed for prediction of reservoir oil viscosity in the three regions including, under-saturated, saturated... 

Precipitation of asphaltene leads to rigorous problems in petroleum industry such as: wettability alterations, relative permeability reduction, blockage of the flow with additional pressure drop in wellbore tubing, upstream process facilities and surface pipelines. Experimentally determination of the asphaltene precipitation is costly and time consuming. Therefore, searching for some other quick and accurate methods for determination of the asphaltene precipitation is inevitable. The objective of this communication is to present a reliable and predictive model namely, the least - squares support vector machine (LSSVM) to predict the asphaltene precipitation. This model has been developed and...