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{ "item_title" : "Ensemble History Matching", "item_author" : [" Geir Evensen", "Dean S. Oliver", "Remus G. Hanea "], "item_description" : "This open-access book aims to formulate the history-matching problem consistently and present state-of-the-art ensemble solution methods. The content aims to help practitioners in the field understand the properties of ensemble methods better when used to history-match reservoir models. The book provides educational information for graduate students and researchers in petroleum, geothermal, and hydrological engineering and sciences. It introduces and explains various algorithms used in data assimilation and parameter estimation, focusing on ensemble methods, particularly the most popular ones in the petroleum community. It discusses challenges associated with these techniques, such as dealing with high-dimensional models, finite number of realizations, parameterization, and handling uncertainties in the observations and model parameters. ", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/3/03/199/154/3031991540_b.jpg", "price_data" : { "retail_price" : "59.99", "online_price" : "59.99", "our_price" : "59.99", "club_price" : "59.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Ensemble History Matching|Geir Evensen

Ensemble History Matching : Conditioning Reservoir Models on Dynamic Data

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Overview

This open-access book aims to formulate the history-matching problem consistently and present state-of-the-art ensemble solution methods. The content aims to help practitioners in the field understand the properties of ensemble methods better when used to history-match reservoir models. The book provides educational information for graduate students and researchers in petroleum, geothermal, and hydrological engineering and sciences. It introduces and explains various algorithms used in data assimilation and parameter estimation, focusing on ensemble methods, particularly the most popular ones in the petroleum community. It discusses challenges associated with these techniques, such as dealing with high-dimensional models, finite number of realizations, parameterization, and handling uncertainties in the observations and model parameters.

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Details

  • ISBN-13: 9783031991547
  • ISBN-10: 3031991540
  • Publisher: Springer
  • Publish Date: November 2025
  • Dimensions: 9.34 x 6.48 x 0.66 inches
  • Shipping Weight: 1.11 pounds
  • Page Count: 199

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