کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8912201 | 1639324 | 2017 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Dynamic and static comprehensive prediction method of natural fractures in fractured oil reservoirs: A case study of Triassic Chang 63 reservoirs in Huaqing Oilfield, Ordos Basin, NW China
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
ژئوشیمی و پترولوژی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
In consideration of the limited adaptability scope, low accuracy and high demand of great cost data of existent fracture prediction methods, a new fracture predicting method was advanced by implementing geological static data and production dynamic data from the Triassic Chang 63 reservoirs in the Huaqing Oilfield. Five constraints, lithology, sedimentary facies, thickness, rock rupture index and fracture intensity controlling the development of fractures were sorted out based on the static geological data. The multiple linear regression method was adopted to work out the quantitative relationships between the five constraints and fracture density, and the fracture density property of the whole area was calculated. Based on production dynamic data of well history, tracer, well interference test and intake profile test, the direction and distribution of fracture horizontally and vertically were figured out by reservoir engineering analysis method. The fracture density property was verified and quantitatively corrected with numerical simulation, and a 3D discrete fracture geological model in agreement with both geological cognition and dynamic production performance was built. The numerical simulation shows that the fracture model has higher fitting consistency, high reliability and adaptability.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Petroleum Exploration and Development - Volume 44, Issue 6, December 2017, Pages 972-982
Journal: Petroleum Exploration and Development - Volume 44, Issue 6, December 2017, Pages 972-982
نویسندگان
Hao SU, Zhengdong LEI, Diqiu ZHANG, Junchao LI, Zeren ZHANG, Binshan JU, Zhiping LI,