سال انتشار: ۱۳۹۴
محل انتشار: چهارمین همایش علمی مخازن هیدروکربوری و صنایع بالادستی علوم و صنایع وابسته
تعداد صفحات: ۱۱
نویسنده(ها):
Seyed Ehsan Eshraghi – Graduate student in Master of Science, P.O Box: 113654563
Mohammad Reza Rasaei – Assistant Professor, Institute of Petroleum Engineering, School of Chemical Engineering,College of Engineering, University of Tehran, Tehran, Iran
Peyman Pourafshary – Assistant Professor, Department of Petroleum and Chemical Engineering, Sultan Qaboos University, Oman
AmirSalar Masoumi – Master of Science, Institute of Petroleum Engineering, School of Chemical Engineering, College of Engineering, University of Tehran, Tehran, Iran
Yousef Kazemzadeh – Master of Science, Young Researchers and Elite Club, Lamerd Branch, Islamic Azad University, Lamerd, Iran

چکیده:

Different scientists have tried to combine petrophysics, geophysics, and thermodynamics with economic factors in order to find out the best recovery scenario. Having a good production scenario and a proper field development strategy require tedious calculations and simulations. Present commercial simulators are complex to work with and time-consuming; therefore, having an overview by less primary data is necessary to manage the field and to optimize the recovery. It was a trigger for reservoir engineers to develop a fast and reliable simulator. Simple predictive models, which usually use material or energy balance on a reservoir to find out its performance, are very fast and low-cost.Capacitance-Resistance Model (CRM) showed efficient as a fast reservoir simulation tool using field-available data of production and injections rates. This approach sets a weighting factor or well-connectivity parameter and a time-constant between each pair of injection and production wells according to their history. In this study, a real case has been modeled using CRM and an efficient and optimum field time-constant, which could be used for entire field, has been determined using CRM simulation results. Its accuracy is verified by comparing the total oil production rate error and well-pair connectivities between original and optimum cases.