Könyv Oil Field Optimization Hyokyeong Lee

Oil Field Optimization

Optimization and Machine Learning Approaches

Szerző: Hyokyeong Lee
Nyelv: Angol
Kötés: Puha kötésű
Kiadó: Scholars' Press
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
20 057 Ft
A major task of every oil company is oil field optimization, i.e. maximizing oil production and redu...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2014
oldal
120
EAN
9783639708622
ISBN
3639708628
Enbook ID
06994618
Súly
186
Méretek
152 x 229 x 7

Teljes leírás

A major task of every oil company is oil field optimization, i.e. maximizing oil production and reducing operational cost. Knowledge about injector-producer relationships (IPRs) is crucial for optimal operation of oil fields. However, inferring IPRs has been a challenging problem due to the unknown underlying structure of oil fields, continuous change of the underlying structure over time, and the large number of wells, i.e. typically, hundreds of injection wells and hundreds of production wells. This book provides two different approaches which map the IPRs problem to a large-scale parameter estimation problem. One approach is constrained nonlinear optimization and the other is machine learning approach. The two approaches demonstrate that not only prediction accuracy but also computational efficiency can be achieved for large-scale parameter estimation problems. This book should help field engineers optimally operate oil fields and show researchers practical examples about how to apply optimization and machine learning techniques to oil field optimization.

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