Sharif Digital Repository

Nitrogen has been appeared as a competitive gas injection alternative for gas-based enhanced oil recovery (EOR) processes. Minimum miscibility pressure (MMP) is the most important parameter to successfully design N2 flooding, which is traditionally measured through time consuming, expensive and cumbersome experiments. In this communication, genetic programming (GP) and constrained multivariable search methods have been combined to create a simple correlation for accurate determination of the MMP of N2-crude oil, based on the explicit functionality of reservoir temperature as well as thermodynamic properties of crude oil and injection gas. The parameters of the developed... 

Interfacial tension (IFT) as one of the main properties for efficient CO2 flooding planning in oil reservoirs depends strongly on pressure, temperature, and composition of the reservoir fluids. Therefore, it is important to measure this property at real reservoir conditions for successful field development plan. In this study, an axisymmetric drop shape analysis (ADSA) has been utilized to measure the equilibrium IFTs between crude oil and CO2 at different temperatures and pressures. Moreover, minimum miscibility pressures (MMP) and first-contact miscibility pressures (P max) of crude oil/CO2 systems at different temperatures are determined by applying the vanishing interfacial tension (VIT)... 

Oil viscosity plays a key role in reservoir simulation and production forecasting, as well as planning thermal enhanced oil recovery methods and these make its accurate determination necessary. In this communication, the most frequently used oil viscosity correlations are evaluated using a large databank of Iranian oil reservoirs which were measured using a Rolling Ball viscometer (Ruska, series 1602). To evaluate the performance and accuracy of these correlations, statistical and graphical error analyses have been used simultaneously. Three of the most accurate correlations for each region, including dead oil viscosity, viscosity below bubble point, viscosity at bubble point and the... 

Nitrogen has been valued as an economical alternative injection gas for gas-based enhanced oil recovery (EOR) processes. Minimum miscibility pressure (MMP) is the most important parameter to successfully design N2 flooding. In this communication, a data bank covering wide ranges of thermodynamic and compositional conditions was gathered from open literature. Afterward, a rigorous approach, namely least square support vector machine (LSSVM) optimized with coupled simulated annealing (CSA) was proposed to develop a reliable and robust model for the prediction of MMP of pure/impure N2–crude oil. The results of this study showed that the proposed model is more reliable and accurate than the... 

Gas flooding processes have emerged as attractive enhanced oil recovery (EOR) methods over the last few decades. Among different gas flooding processes, CO2 flooding is recognized as being most efficient for displacing oil through miscible displacement. Minimum miscibility pressure (MMP) is a crucial parameter for successfully designing CO2 flooding, which is traditionally measured through time-consuming, expensive, and cumbersome experiments. In the present study, a new reliable model based on feed-forward artificial neural networks was presented to predict both pure and impure CO2-crude oil MMP. Among various properties and parameters, reservoir temperature, reservoir oil composition, and... 

In the last years, an appreciable effort has been directed toward developing empirical models to link the relative permeability of gas condensate reservoirs to the interfacial tension and velocity as well as saturation. However, these models suffer from non-universality and uncertainties in setting the tuning parameters. In order to alleviate the aforesaid infirmities in this study, comprehensive modeling was carried out by employing numerous smart computer-aided algorithms including Support Vector Regression (SVR), Least Square Support Vector Machine (LSSVM), Extreme Learning Machine (ELM), Multilayer Perceptron (MLP), Group Method of Data Handling (GMDH), and Gene Expression Programming... 

Nitrogen has emerged as a competitive gas injection alternative for gas-based enhanced oil recovery processes in the past two decades. The injection of nitrogen into the reservoirs has improved the oil recovery efficiency in various oil reservoirs from heavy to volatile oils. As it is known, interfacial tension (IFT) plays a key role in any enhanced oil recovery process, particularly gas injection processes; therefore, its accurate determination is crucial for the design of any gas injection process especially at reservoir condition. In this study, an axisymmetric drop shape analysis (ADSA) was utilized to measure the equilibrium IFTs between crude oil and N2 at different temperature levels... 

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... 

Accurate prediction of the PVT properties of reservoir oil is of primary importance for improved oilfield development strategies. Experimental determination of these properties is expensive and time-consuming. Therefore, new empirical models for universal reservoir oils have been developed as a function of commonly available field data. In this communication, more than 750 experimental data series were gathered from different geographical locations worldwide. Successive linear programming and generalized reduced gradient algorithm as two constrained multivariable search methods were incorporated for modeling and expediting the process of achieving a good feasible solution. Moreover,... 

Steam injection process has been considered for a long time as an effective method to exploit heavy oil resources. Over the last decades, Steam Assisted Gravity Drainage (SAGD) has been proved as one of the best steam injection methods for recovery of unconventional oil resources. Recently, Fast-SAGD, a modification of the SAGD process, makes use of additional single horizontal wells alongside the SAGD well pair to expand the steam chamber laterally. This method uses fewer wells and reduces the operational cost compared to a SAGD operation requiring paired parallel wells one above the other. The efficiency of this new method in naturally fractured reservoir is not well understood.... 

Nitrogen has emerged as a suitable alternative to carbon dioxide for injection into hydrocarbon reservoirs worldwide to enhance the recovery of subsurface energy. Nitrogen typically costs less than CO2 and natural gas, and has the added benefit of being widely available and non-corrosive. However, the underlying mechanisms of recovery following N2 injection into fractured reservoirs that make up a large portion of the world's oil and gas reserves are not well understood. Here we present the laboratory results of N2 injection into carbonate rocks acquired from a newly developed oil reservoir in Iran with a huge N2-containing natural gas reservoir nearby. We investigate the effectiveness of N2... 

Accurate prediction of the solubility of gases in hydrocarbons is a crucial factor in designing enhanced oil recovery (EOR) operations by gas injection as well as separation, and chemical reaction processes in a petroleum refinery. In this work, nitrogen (N2) solubility in normal alkanes as the major constituents of crude oil was modeled using five representative machine learning (ML) models namely gradient boosting with categorical features support (CatBoost), random forest, light gradient boosting machine (LightGBM), k-nearest neighbors (k-NN), and extreme gradient boosting (XGBoost). A large solubility databank containing 1982 data points was utilized to establish the models for... 

A novel mathematical-based approach is proposed to develop reliable models for prediction of saturated crude oil viscosity in a wide range of PVT properties. A new soft computing approach, namely least square support vector machine modeling optimized with coupled simulated annealing optimization technique, is proposed. Six models have been developed to predict saturated oil viscosity, which are designed in such a way that could predict saturated oil viscosity with every available PVT parameter. The constructed models are evaluated by carrying out extensive experimental saturated crude oil viscosity data from Iranian oil reservoirs, which were measured using a "Rolling Ball viscometer." To... 

Permeability as a fundamental reservoir property plays a key role in reserve estimation, numerical reservoir simulation, reservoir engineering calculations, drilling planning, and mapping reservoir quality. In heterogeneous reservoir, due to complexity, natural heterogeneity, non-uniformity, and non-linearity in parameters, prediction of permeability is not straightforward. To ease this problem, a novel mathematical robust model has been proposed to predict the permeability in heterogeneous carbonate reservoirs. To this end, a fairly new soft computing method, namely least square support vector machine (LSSVM) modeling optimized with coupled simulated annealing (CSA) optimization technique... 

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... 

Nowadays, the need for industrial processes with sufficient accuracy, efficiency, and flexibility to compete world markets is inevitable. On the other hand, the advent of control techniques and increased computation power of CPUs allow implementation of complex controllers using optimization techniques to provide higher efficiency and economic productivity. Model predictive control refers to a wide range of optimization-based control methods applying explicit models to predict its prospective use. These methods of control compute control signal by minimizing the cost function so that the process output becomes very close to the optimal path. In this paper, we use a new model predictive... 

High availability of software systems is an essential requirement for pervasive computing environments. In such systems self-adaptation, using dynamic reconfiguration is also a key feature. However, dynamic reconfiguration potentially decreases the system availability by making parts of the system temporary frozen, especially during incomplete or faulty execution of the reconfiguration process. In this paper, we propose Assured Dynamic Reconfiguration Framework (ADRF), consisting of run-time analysis phases, assuring the desired correctness and completeness of dynamic reconfiguration process. We also specify factors that affect availability of reconfigurable software in pervasive computing... 

The problem of gyrocompassing using inertial sensors, i.e., gyros and accelerometers, is addressed. North finding, with an order of accuracy of one arc-min, is not only required for the initial alignment of inertial navigation systems, but also has a critical role to play in the guidance and navigation of ships that navigate for long periods of time. In this work, after extracting the error model of an inertial navigation system and augmenting it with the error model of inertial sensors, a processing algorithm based on the Kalman filter is designed and simulated to process the navigation system velocity error, and to estimate and correct tilt and heading errors along with gyro drifts and...