Challenges and solutions in stochastic reservoir modelling : geostatistics, machine learning, uncertainty prediction

• Main Authors: Demyanov, Vasily, (Author), Arnold, Dan, (Author)
• Format: eBook
• Language: English
• Published: Houten, Netherlands : EAGE Publications, [2018]
• Subjects: Geological modeling.; Geology > Statistical methods.; elektronické knihy; electronic books
• ISBN: 9781523119875; 152311987X
• Physical Description: 1 online resource
• Access: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty

Many advances in stochastic reservoir modelling have been introduced in the past decade. Novel method of data integration and more accurate representation of geology have been developed with the advances in spatial statistics. However, integrated approach for predictive reservoir modelling still attracts continuous effort to manage reservoir decisions under uncertainty and make better use of the increasing amounts of data and domain knowledge accumulated in the field. Many solutions to these challenges lie in the cross-disciplinary vision, where modern rigour of computer science and statistics brought together with core geological and engineering domain expertise and basic physical conceptual thinking.