The increasingly rapid development of the disciplines of petroleum engineering and petroleum geology has led to new methodologies and interpretation techniques forming new knowledge that should be offered quickly and ...The increasingly rapid development of the disciplines of petroleum engineering and petroleum geology has led to new methodologies and interpretation techniques forming new knowledge that should be offered quickly and efficiently to modern engineers and geologists. This need is equally important for students as well as for young professionals. Access and training to all scientific information is necessary to ensure success in their future careers. Today, e-learning has become a common medium for the management and distribution of on-line educational content. Learning Management Systems （LMSs） were not only developed to handle a large variety of multimedia content that provides an organized knowledge repository used to accelerate access to information and skill acquisition; but, LMSs can also keep detailed statistics on the use of the available material offering a powerful training and educational tool. In this document, the Petroleum Knowledge Tutorial System, an LMS platform offering a variety of online educational and training options to petroleum engineers and geologists, is presented. It was created using Moodle, open- source software that can be used to create on-line courses. The platform covers fundamental educational concepts in a structured way. It follows an optimized ＂workflow＂ that can be applied not only to solve a specific exercise but also any similar problem encountered over the course of one＇s career. The platform was designed to offer a repository of learning material in various forms and to favor user-platform interactions. It can be used for training and evaluation purposes through exercises and problem solving that the user can perform online by using browsing software along with internet access. Special tools were created and implemented on the platform to assist the user in completing a variety of tasks including performing exercises involving calculations with given data and plots of points or lines on graphs without leaving the learning environment. Furthermore, videos with detailed explanations follow each learning module and provide the full solution to every exercise. The LMS automatically keeps a large statistical database including the users＇ access to activities on the platform that can be exported and further processed to improve the platform functionality and evaluate the users＇ performance.展开更多
Due to the high viscosity of heavy crude oils,production from these reservoirs is a demanding task.To tackle this problem,reducing oil viscosity is a promising approach.There are various methods to reduce viscosity of...Due to the high viscosity of heavy crude oils,production from these reservoirs is a demanding task.To tackle this problem,reducing oil viscosity is a promising approach.There are various methods to reduce viscosity of heavy oil:heating,diluting,emulsification,and core annular flow.In this study,dilution approach was employed,using industrial solvents and gas condensate.The viscosity of two Iranian heavy crude oils was measured by mixing with solvents at different temperatures.Dilution of both oil samples with toluene and heptane,resulted in viscosity reduction.However,their effect became less significant at higher concentrations of diluent.Because of forming hydrogen bonds,adding methanol to heavy crude oil resulted in higher viscosity.By adding condensate,viscosity of each sample reduced.Gas condensate had a greater impact on heavier oil;however,at higher temperatures its effect was reduced.Diluting with naphtha decreased heavy oil viscosity in the same way as n-heptane and toluene.Besides experimental investigation,different viscosity models were evaluated for prediction of heavy oil/solvent viscosity.It was recognized that Lederer'model is the best one.展开更多
Density is an important property of natural gas required for the design of gas processing and reservoir simulation.Due to expensive measurement of density,industry tends to predict gas density through an EOS.However,a...Density is an important property of natural gas required for the design of gas processing and reservoir simulation.Due to expensive measurement of density,industry tends to predict gas density through an EOS.However,all EOS are associated with uncertainties,especially at highpressure conditions.Also,using sophisticated EOS in commercial software renders simulation highly time-consuming.This work aims to evaluate performance of adaptive neuro-fuzzy inference system(ANFIS)as a widely-accepted intelligent model for prediction of P-r-T behavior of natural gas.Using experimental data reported in the literature,our inference system was trained with 95 data of natural gas densities in the temperature range of(250-450)K and pressures up to 150 MPa.Additionally,prediction by ANFIS was compared with those of AGA8 and GERG04 which both are leading industrial EOS for calculation of natural gas density.It was observed that ANFIS predicts natural gas density with AARD%of 1.704;and is able to estimate gas density as accurate as sophisticated EOS.The proposed model is applicable for predicting gas density in the range of(250-450)K,(10-150)MPa and also for sweet gases,i.e.,containing a low concentration of N2 and CO2.展开更多
文摘The increasingly rapid development of the disciplines of petroleum engineering and petroleum geology has led to new methodologies and interpretation techniques forming new knowledge that should be offered quickly and efficiently to modern engineers and geologists. This need is equally important for students as well as for young professionals. Access and training to all scientific information is necessary to ensure success in their future careers. Today, e-learning has become a common medium for the management and distribution of on-line educational content. Learning Management Systems （LMSs） were not only developed to handle a large variety of multimedia content that provides an organized knowledge repository used to accelerate access to information and skill acquisition; but, LMSs can also keep detailed statistics on the use of the available material offering a powerful training and educational tool. In this document, the Petroleum Knowledge Tutorial System, an LMS platform offering a variety of online educational and training options to petroleum engineers and geologists, is presented. It was created using Moodle, open- source software that can be used to create on-line courses. The platform covers fundamental educational concepts in a structured way. It follows an optimized ＂workflow＂ that can be applied not only to solve a specific exercise but also any similar problem encountered over the course of one＇s career. The platform was designed to offer a repository of learning material in various forms and to favor user-platform interactions. It can be used for training and evaluation purposes through exercises and problem solving that the user can perform online by using browsing software along with internet access. Special tools were created and implemented on the platform to assist the user in completing a variety of tasks including performing exercises involving calculations with given data and plots of points or lines on graphs without leaving the learning environment. Furthermore, videos with detailed explanations follow each learning module and provide the full solution to every exercise. The LMS automatically keeps a large statistical database including the users＇ access to activities on the platform that can be exported and further processed to improve the platform functionality and evaluate the users＇ performance.
文摘Due to the high viscosity of heavy crude oils,production from these reservoirs is a demanding task.To tackle this problem,reducing oil viscosity is a promising approach.There are various methods to reduce viscosity of heavy oil:heating,diluting,emulsification,and core annular flow.In this study,dilution approach was employed,using industrial solvents and gas condensate.The viscosity of two Iranian heavy crude oils was measured by mixing with solvents at different temperatures.Dilution of both oil samples with toluene and heptane,resulted in viscosity reduction.However,their effect became less significant at higher concentrations of diluent.Because of forming hydrogen bonds,adding methanol to heavy crude oil resulted in higher viscosity.By adding condensate,viscosity of each sample reduced.Gas condensate had a greater impact on heavier oil;however,at higher temperatures its effect was reduced.Diluting with naphtha decreased heavy oil viscosity in the same way as n-heptane and toluene.Besides experimental investigation,different viscosity models were evaluated for prediction of heavy oil/solvent viscosity.It was recognized that Lederer'model is the best one.
文摘Density is an important property of natural gas required for the design of gas processing and reservoir simulation.Due to expensive measurement of density,industry tends to predict gas density through an EOS.However,all EOS are associated with uncertainties,especially at highpressure conditions.Also,using sophisticated EOS in commercial software renders simulation highly time-consuming.This work aims to evaluate performance of adaptive neuro-fuzzy inference system(ANFIS)as a widely-accepted intelligent model for prediction of P-r-T behavior of natural gas.Using experimental data reported in the literature,our inference system was trained with 95 data of natural gas densities in the temperature range of(250-450)K and pressures up to 150 MPa.Additionally,prediction by ANFIS was compared with those of AGA8 and GERG04 which both are leading industrial EOS for calculation of natural gas density.It was observed that ANFIS predicts natural gas density with AARD%of 1.704;and is able to estimate gas density as accurate as sophisticated EOS.The proposed model is applicable for predicting gas density in the range of(250-450)K,(10-150)MPa and also for sweet gases,i.e.,containing a low concentration of N2 and CO2.
