Improvement of accuracy for estimating reservoir properties by Markov-Bayes method using two soft data

Lingdan Xia, Masanori Kurihara

    研究成果: Paper査読

    抄録

    Geostatistics has been playing an important role in reservoir characterization and modeling. The principal objective of reservoir characterization is to provide a reservoir model for accurate reservoir performance prediction. To attain this objective, the integration of information from various data sources is an essential task in reservoir characterization. In this study, the geostatistical program that includes the sub-programs for kriging and conditional simulation was coded. Especially, the sub-program for Markov-Bayes simulation that enables the estimation of reservoir property distribution using two soft data was developed. This process is not available in conventional geostatistical software. This paper presents the results of reservoir property distributions estimated by various geostatistical methods and discusses the comparison among them. Through this comparison, the advantage of Markov-Bayes method using two soft data for the improvement of the accuracy for estimating reservoir properties is demonstrated.

    本文言語English
    出版ステータスPublished - 2014 1 1
    イベント20th Formation Evaluation Symposium of Japan 2014 - Chiba, Japan
    継続期間: 2014 10 12014 10 2

    Other

    Other20th Formation Evaluation Symposium of Japan 2014
    国/地域Japan
    CityChiba
    Period14/10/114/10/2

    ASJC Scopus subject areas

    • 地質学
    • エネルギー工学および電力技術
    • 経済地質学
    • 地球化学および岩石学
    • 地盤工学および土木地質学

    フィンガープリント

    「Improvement of accuracy for estimating reservoir properties by Markov-Bayes method using two soft data」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

    引用スタイル