Laboratory Investigation of Carbon Dioxide Flooding by Focusing on the Viscosity and the Swelling Factor Changes for one of the Iranian Southwestern Oil Reservoirs
Publish place: 02nd Iranian Petroleum Engineering Congress
Publish Year: 1386
نوع سند: مقاله کنفرانسی
زبان: English
View: 1,015
This Paper With 11 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
IPEC02_117
تاریخ نمایه سازی: 22 خرداد 1391
Abstract:
Carbon dioxide () flooding is an efficacious method of enhanced oil recovery (EOR) that has nowadays become one of the most important EOR processes. It is a very complicated process, involving phase behavior that could increase oil recovery by means of swelling, evaporating and lowering oil viscosity. The present investigation reports the results of extensive experimental and theoretical work (with the aim of computer software, ECLIPSETM) to determine the viscosity and swelling factor changes of the live oil in the Cheshmeh Khoshk reservoir at southern of Iran (Ilam District) and also minimum miscible pressure is determined. In this study, we want to study the potential of injection application in improving oil recovery by simulating a slim tube experiments. In order to get representative fluid samples of a reservoir, it was necessary that the right operation of mixing the separator oil and gas samples to match the bubble point pressure be carried out. And, the potential application of the study is that we could have a good estimate of the recovery improvement under gas injection, which will be the basic input parameters for the economic feasibility study and also a decision can then be made whether to implement or abandon the prospective project.
Keywords:
Authors
Bahram Mokhtari
Iranian Elite Academy, Aghdasieh, Tehran, Iran
Masoud Enayati
Lavan Laboratory, Iranian Offshore Oil Co
Pedram Mahzari
MS Student of University of Tehran, Reservoir Engineering
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :