Modeling of steam distillation mechanism during steam injection process using artificial intelligence

Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods

Modeling of Steam Distillation Mechanism during Steam Injection Process Using Artificial Intelligence

Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods

SPONTANEOUS IMBIBITION OIL RECOVERY BY NATURAL SURFACTANT/NANOFLUID: AN EXPERIMENTAL AND THEORETICAL STUDY

Organic surfactants have been utilized with different nanoparticles in enhanced oil recovery (EOR) operations due to the synergic mechanisms of nanofluid stabilization, wettability alteration, and oil-water interfacial tension reduction. However, investment and environmental issues are the main concerns to make the operation more practical. The present study introduces a natural and cost-effective surfactant named Azarboo for modifying the surface traits of silica nanoparticles for more efficient EOR. Surface-modified nanoparticles were synthesized by conjugating negatively charged Azarboo surfactant on positively charged amino-treated silica nanoparticles. The effect of the hybrid application of the natural surfactant and amine-modified silica nanoparticles was investigated by analysis of wettability alteration. Amine-surfactant-functionalized silica nanoparticles were found to be more effective than typical nanoparticles. Amott cell experiments showed maximum imbibition oil recovery after nine days of treatment with amine-surfactant-modified nanoparticles and fifteen days of treatment with amine-modified nanoparticles. This finding confirmed the superior potential of amine-surfactant-modified silica nanoparticles compared to amine-modified silica nanoparticles. Modeling showed that amine surfactant-treated SiO2 could change wettability from strongly oil-wet to almost strongly water-wet. In the case of amine-treated silica nanoparticles, a strongly water-wet condition was not achieved. Oil displacement experiments confirmed the better performance of aminesurfactant- treated SiO2 nanoparticles compared to amine-treated SiO2 by improving oil recovery by 15%. Overall, a synergistic effect between Azarboo surfactant and amine-modified silica nanoparticles led to wettability alteration and higher oil recovery

A Comprehensive Review of Fracture Characterization and Its Impact on Oil Production in Naturally Fractured Reservoirs

Naturally fractured reservoirs are indescribable systems to characterize and difficult to produce and forecast. For the development of such reservoirs, the role of naturally forming fractures in the different development stages needs to be recognized, especially for the pressure maintenance and enhanced oil recovery stages. Recent development in the field of naturally carbonate fractured aimed at fracture characterization, fracture modeling, and fracture network impact of fracture networks on oil recovery were reviewed. Consequently, fracture identification and characterization played pivotal roles in understanding production mechanisms by integrating multiple geosciences sources and reservoir engineering data. In addition, a realistic fracture modeling approach, such as a hybrid, can provide a more accurate representation of the behavior of the fracture and, hence, a more realistic reservoir model for reservoir production and management. In this respect, the influence of different fracture types present in the reservoir, such as major, medium, minor, and hairline fractures networks, and their orientations were found to have different rules and impacts on oil production in the primary, secondary, and EOR stages. In addition, any simplification or homogenization of the fracture types might end in over or underestimating the oil recovery. Improved fracture network modeling requires numerous considerations, such as data collection, facture characterization, reservoir simulation, model calibration, and model updating based on newly acquired field data are essential for improved fracture network description. Hence, integrating multiple techniques and data sources is recommended for obtaining a reliable reservoir model for optimizing the primary and enhanced oil recovery methods

Asphaltene Deposition Modeling during Natural Depletion and Developing a New Method for Multiphase Flash Calculation

The specific objective of this paper is to develop a fully implicit compositional simulator for modeling asphaltene deposition during natural depletion. In this study, a mathematical model for asphaltene deposition modeling is presented followed by the solution approach using the fully implicit scheme. A thermodynamic model for asphaltene precipitation and the numerical methods for performing flash calculation with a solid phase are described. The pure solid model is used to model asphaltene precipitation. The transformation of precipitated solid into flocculated solid is modeled by using a first order chemical reaction. Adsorption, pore throat plugging, and re-entrainment were considered in the deposition model. The simulator has the capability of predicting formation damage including porosity and permeability reduction in each block. A new set of independent unknowns in a fully implicit scheme is presented for asphaltene deposition modeling. In order to find the solution of these variables, the same number of equations is also presented. The description of how to solve the nonlinear system of equations is also described

Investigating the Effects of Heterogeneity, Injection Rate, and Water Influx on GAGD EOR in Naturally Fractured Reservoirs

The gas-assisted gravity drainage (GAGD) process is designed and practiced based on gravity drainage idea and uses the advantage of density difference between injected CO2 and reservoir oil. In this work, one of Iran western oilfields was selected as a case study and a sector model was simulated based on its rock and fluid properties. The pressure of CO2 gas injection was close to the MMP of the oil, which was measured 1740 psia. Both homogeneous and heterogeneous types of fractures were simulated by creating maps of permeability and porosity. The results showed that homogeneous fractures had the highest value of efficiency, namely 40%; however, in heterogeneous fractures, the efficiency depended on the value of fracture density and the maximum efficiency was around 37%. Also, the effect of injection rate on two different intensities of fracture was studied and the results demonstrated that the model having higher fracture intensity had less limitation in increasing the CO2 injection rate; furthermore, its BHP did not increase intensively at higher injection rates either. In addition, three different types of water influxes were inspected on GAGD performance to simulate active, partial, and weak aquifer. The results showed that strong aquifer had a reverse effect on the influence of GAGD and almost completely disabled the gravity drainage mechanism. Finally, we inventively used a method to weaken the aquifer strength, and thus the gravity drainage revived and efficiency started to increase as if there was no aquifer

The Performance Evaluation of Viscous-Modified Surfactant Waterflooding in Heavy Oil Reservoirs at Varying Salinity of Injected Polymer-Contained Surfactant Solution

ABSTRACT: This study examines the effects of change in the concentrations of monovalent and divalent ions in the polymer-contained surfactant solution on the macroscopic behavior of viscous-modified surfactant waterflooding in heavy oil reservoirs. Salts that are used in this set of floods were sodium chloride, magnesium chloride, and calcium chloride. The results indicate that four different ranges of salinity (in terms of CaCl 2 concentration) exist. Each of these ranges renders a unique behavior regarding the ultimate oil recovery trends. There exists a range of salinity in which the ultimate oil recovery does not change with the salinity increase. The second salinity range is beyond the salt tolerance (i.e., first salinity range) of the polymer-contained surfactant solution, which results in a decrease in the ultimate oil recovery. In the third range of salinity, ultimate oil recovery is enhanced due to the plugging of high-permeable pores. In the fourth salinity range, precipitation increases as the salinity increases and more pore throats (even some pores with intermediate permeability) are plugged and, thus, the ultimate oil recovery decreases

Screening of inhibitors for remediation of asphaltene deposits: Experimental and modeling study

One of the most severe problems during production from heavy crude oil reservoirs is the formation of asphaltene precipitation and as a result deposition in the tubing, surface facilities and near wellbore region which causes oil production and permeability reduction in addition to rock wettability alteration in the reservoir. So one of the economical ways to prevent such incidents is using the chemicals which are called asphaltene inhibitor.In this study, the influence of three commercial inhibitors, namely; Cetyl Terimethyl Ammonium Bromide (CTAB), Sodium Dodecyl Sulfate (SDS), Triton X-100 and four non-commercial (Benzene, Benzoic Acid, Salicylic Acid, Naphthalene) inhibitors on two Iranian crude oils were investigated. This study extends previous works and contributes toward the better understanding of interactions between asphaltene and inhibitor. Effect of functional groups and structure of inhibitors on asphaltene precipitation were studied and it seems clear that the nature and polarity of asphaltene (structure and amount of impurities presented) has a significant impact on the selection of inhibitors. asphaltene dispersant tests and Core flood tests were designed for evaluation of inhibitors in static and dynamic conditions. The results revealed distinguished mechanisms for asphaltene solubilization/dispersion (such as hydrogen bonding, π–π interaction and acid-base interaction) and influence of additional side group (OH) on inhibition power of inhibitor.During the experiments, it was found that increasing inhibitor concentration may lead to the self-assembly of inhibitor and declining of asphaltene stabilization. So, finding optimum concentration of inhibitor with high efficiency and available at a reasonable price is very important. The results suggest that 600 ppm of CTAB and 300 ppm of SDS were approximately optimum concentrations for the studied crude oils. One of the most important findings that differ from previous studies is the revelation of the mechanism behind the SDS/asphaltene behavior in various concentrations of inhibitor. Effect of chosen inhibitors on asphaltene precipitation and consequently deposition in porous media was studied, and then experimental data were modeled for evaluation of permeability impairment mechanisms. Permeability revived after inhibitor squeezing and cake formation mechanism played an important role in permeability reduction before and after treatment in porous media. The findings can also be applied to prediction of future behavior of reservoirs in oil field scale and evaluation of formation damage in the different period of production if needed any treatment process. Keywords: Asphaltene, Precipitation, Deposition, Inhibitor, Permeability reductio