عنوان
پدید آورنده
موضوع
رده
کتابخانه
محل استقرار
TL48026
انگلیسی
Fuzzy and neural network models for predicting interaction between hydraulic fracture and natural fracture
[Thesis]
[Thesis]
[Thesis]
[Thesis]
Peng Chen
Rahman, Mohammed Motiur
The Petroleum Institute (United Arab Emirates)
2014
129
Committee members: Haroun, Mohammed; Sarma, Hemanta Kumar
Place of publication: United States, Ann Arbor; ISBN=978-1-321-32452-5
M.S.
Petroleum Engineering
The Petroleum Institute (United Arab Emirates)
2014
Tight gas resource has been getting more and more focus due to its huge potential all over the world. Hydraulic-fracturing treatments have become an essential technology for tight gas field development. Tight gas formations often contain natural fractures (NF). In presence of natural fractures, more complex fracture networks may form during the hydraulic treatment. The interaction between fractures may alter the way the hydraulic fracture (HF) propagates through the formation, causing a complex network of fractures, which can significantly influence the overall geometry and effectiveness of hydraulic fracture. The hydraulic fracture may cross, dilate or slip into the fracture plane upon its arrival at the natural fractures. Although there have been studies on investigation of the interaction between HF and NF, most of them cannot be applied reliably due to the inherent assumptions in the analytical formulation and numerical work. In cases of laboratory studies, the limitation of the equipment could also be a factor.
Petroleum engineering
Applied sciences;Computer science;Fuzzy systems;Hydraulic fracturing;Neural networks
Motameni, Ahmad R.
Rahman, Mohammed Motiur
Petroleum Engineering
The Petroleum Institute (United Arab Emirates)
1636536009; 1568709
مطالعه متن کتاب p
[Thesis]
276903
a
Y
