石油学报 ›› 2010, Vol. 31 ›› Issue (1): 73-77.DOI: 10.7623/syxb201001012

• 地质勘探 • 上一篇    下一篇

基于多尺度数据融合Markov链模型的岩性随机模拟

李 军 1 熊利平 1 方 石 2 唐 林 3 霍 红 1   

  1. 1中国石化石油勘探开发研究院 北京 100083; 2吉林大学地球科学学院 吉林长春 130061; 3中国石化胜利油田分公司河口采油厂 山东东营 257200
  • 收稿日期:2009-02-03 修回日期:2009-05-20 出版日期:2010-01-25 发布日期:2010-05-21
  • 通讯作者: 李 军

Lithology stochastic simulation based on Markov chain models integrated with multi-scale data

LI Jun 1 XIONG Liping 1 FANG Shi 2 TANG Lin 3 HUO Hong 1   

  • Received:2009-02-03 Revised:2009-05-20 Online:2010-01-25 Published:2010-05-21
  • Contact: LI Jun

摘要:

Markov链模型在储层随机建模中发挥着越来越重要的作用,但难以融合岩心、测井、地震等多尺度数据限制了它在实际中的应用。依据前人研究的结果,提出了将多尺度数据融入到Markov链模型中的相关方法和公式,即将大尺度数据作为条件数据以贝叶斯公式表达,同时利用公式将小尺度数据转换为井点硬数据。应用此方法对SL盆地Y地区过井剖面进行的岩性模拟表明,相对于无数据融合的方法,此方法能更加直观、准确地揭示薄岩性层的分布。

关键词: Markov链模型, 多尺度数据, 融合方法, 岩性随机模拟, 薄岩层分布

Abstract:

The Markov chain models have played a more important role in the reservoir stochastic modeling, but the models are difficult to be integrated with the multi-scale data such as logging, core data and seismic data, which limits the application of the models. A new method and some formula were proposed for integrating the multi-scale data with the Markov chain models. The large-scale data were added into the models and taken as the conditional data, and the small-scale data were used to get exact data of well points by formula. The application of the method to simulate lithology of a section across wells in Y region of SL Basin shows that the fine lithology distribution obtained from the new method is more accurate and distinctive than that of the previous method.

Key words: Markov chain model, multi-scale data, integration, lithology stochastic simulation, fine lithology distribution