کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8127187 | 1522829 | 2013 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Grid sensitivity studies in hydraulically fractured low permeability reservoirs
ترجمه فارسی عنوان
مطالعات حساسیت شبکه در مخازن نفوذ پذیری کم هیدرولیکی شکسته
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
حساسیت شبکه، مخازن مایع شیل، شبیه سازی مخزن،
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
زمین شناسی اقتصادی
چکیده انگلیسی
The accuracy and hence the validity of reservoir simulation results largely depend on the grid system used in the simulation. It is observed that when there is a large difference in permeability between two adjacent layers, conventional grid systems do not accurately predict reservoir behaviors. Grid refinement is used near the well bore and fractures to better resolve the fluid flow between grid blocks. Logarithmically refined grids are commonly applied near the well bore region as there are large changes in pressure and saturation in this zone. Grid refinement must be applied even more carefully when dealing with the production of condensates. Effects of grid refinement on simulation results such as cumulative gas, cumulative oil, condensate-gas ratio (CGR) or gas-oil ratio (GOR), and planar pressure distribution were studied using a generic reservoir model with one horizontal well and one vertical planar fracture for wet gas, gas-condensate and black oil fluids. These results were generated using a full-feature compositional simulator. The results from these studies were used to develop empirical relationships between the dimensionless fracture conductivity and the grid size necessary to achieve converging results.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Petroleum Science and Engineering - Volume 112, December 2013, Pages 78-87
Journal: Journal of Petroleum Science and Engineering - Volume 112, December 2013, Pages 78-87
نویسندگان
Palash Panja, Tyler Conner, Milind Deo,