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Enhanced oil recovery : field planning and development strategies

著者: V Alvarado; E Manrique
出版: Burlington, MA : Gulf Professional Pub./Elsevier, ©2010.
エディション/フォーマット:   電子書籍 : Document : Englishすべてのエディションとフォーマットを見る
データベース:WorldCat
概要:
Enhanced-Oil Recovery (EOR) evaluations focused on asset acquisition or rejuvenation involve a combination of complex decisions, using different data sources. EOR projects have been traditionally associated with high CAPEX and OPEX, as well as high financial risk, which tend to limit the number of EOR projects launched. In this book, the authors propose workflows for EOR evaluations that account for different  続きを読む
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ジャンル/形式: Electronic books
その他のフォーマット: Print version:
Alvarado, V. (Vladimir).
Enhanced oil recovery.
Burlington, MA : Gulf Professional Pub./Elsevier, c2010
(DLC) 2010012466
(OCoLC)430842982
資料の種類: Document, インターネット資料
ドキュメントの種類: インターネットリソース, コンピューターファイル
すべての著者/寄与者: V Alvarado; E Manrique
ISBN: 9781856178563 1856178560
OCLC No.: 647764718
物理形態: 1 online resource (xv, 192 p.) : ill., maps.
コンテンツ: Introduction --
Part One: Methodology --
Conventional screening, Geological screening, Advanced screening, Evaluation of "soft variables", Performance prediction --
Part Two: Field Cases Type I: Lack of data and time constraints --
Case study A, Case study B, Case study C. --
Part Three: Field Cases II: Not enough time to use sufficient data --
Case study D, Case study E, Case study F.
責任者: Vladimir Alvarado and Eduardo Manrique.

概要:

Enhanced-Oil Recovery (EOR) evaluations focused on asset acquisition or rejuvenation involve a combination of complex decisions, using different data sources. EOR projects have been traditionally associated with high CAPEX and OPEX, as well as high financial risk, which tend to limit the number of EOR projects launched. In this book, the authors propose workflows for EOR evaluations that account for different volumes and quality of information. This flexible workflow has been successfully applied to oil property evaluations and EOR feasibility studies in many oil reservoirs. The methodology associated with the workflow relies on traditional (look-up tables, XY correlations, etc.) and more advanced (data mining for analog reservoir search and geology indicators) screening methods, emphasizing identification of analogues to support decision making. The screening phase is combined with analytical or simplified numerical simulations to estimate full-field performance by using reservoir data-driven segmentation procedures. Case Studies form Asia, Canada, Mexico, South America and the United States Assets evaluated include reservoir types ranging from oil sands to condensate reservoirs. Different stages of development and information availability are discussed.

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