Assisted History Matching for Unconventional Reservoirs

Assisted History Matching for Unconventional Reservoirs
Author :
Publisher : Gulf Professional Publishing
Total Pages : 290
Release :
ISBN-10 : 9780128222430
ISBN-13 : 0128222433
Rating : 4/5 (433 Downloads)

Book Synopsis Assisted History Matching for Unconventional Reservoirs by : Sutthaporn Tripoppoom

Download or read book Assisted History Matching for Unconventional Reservoirs written by Sutthaporn Tripoppoom and published by Gulf Professional Publishing. This book was released on 2021-08-05 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: As unconventional reservoir activity grows in demand, reservoir engineers relying on history matching are challenged with this time-consuming task in order to characterize hydraulic fracture and reservoir properties, which are expensive and difficult to obtain. Assisted History Matching for Unconventional Reservoirs delivers a critical tool for today's engineers proposing an Assisted History Matching (AHM) workflow. The AHM workflow has benefits of quantifying uncertainty without bias or being trapped in any local minima and this reference helps the engineer integrate an efficient and non-intrusive model for fractures that work with any commercial simulator. Additional benefits include various applications of field case studies such as the Marcellus shale play and visuals on the advantages and disadvantages of alternative models. Rounding out with additional references for deeper learning, Assisted History Matching for Unconventional Reservoirs gives reservoir engineers a holistic view on how to model today's fractures and unconventional reservoirs. - Provides understanding on simulations for hydraulic fractures, natural fractures, and shale reservoirs using embedded discrete fracture model (EDFM) - Reviews automatic and assisted history matching algorithms including visuals on advantages and limitations of each model - Captures data on uncertainties of fractures and reservoir properties for better probabilistic production forecasting and well placement


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