SCIRP Mobile Website
Paper Submission

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.

 

Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
   
Paper Publishing WeChat
Book Publishing WeChat
(or Email:book@scirp.org)

Article citations

More>>

Abbaszadeh, M., Fujii, H. and Fujimoto, F. (1996) Permeability Prediction by Hydraulic Flow Units—Theory and Applications. SPE Formation Evaluation, 11, 263-271.
https://doi.org/10.2118/30158-PA

has been cited by the following article:

  • TITLE: An Integrated Method of Data Mining and Flow Unit Identification for Typical Low Permeability Reservoir Prediction

    AUTHORS: Peng Yu

    KEYWORDS: Low Permeability Reservoir, Offshore Oilfield, Hydraulic Flow Unit, Flow Unit Identification, Data Mining

    JOURNAL NAME: World Journal of Engineering and Technology, Vol.7 No.1, January 28, 2019

    ABSTRACT: With the development of oilfield exploration and mining, the research on continental oil and gas reservoirs has been gradually refined, and the exploration target of offshore reservoir has also entered the hot studystage of small sand bodies, small fault blocks, complex structures, low permeability and various heterogeneous geological bodies. Thus, the marine oil and gas development will inevitably enter thecomplicated reservoir stage; meanwhile the corresponding assessment technologies, engineering measures andexploration method should be designed delicately. Studying on hydraulic flow unit of low permeability reservoir of offshore oilfield has practical significance for connectivity degree and remaining oil distribution. An integrated method which contains the data mining and flow unit identification part was used on the flow unit prediction of low permeability reservoir; the predicted resultswere compared with mature commercial system results for verifying its application. This strategy is successfully applied to increase the accuracy by choosing the outstanding prediction result. Excellent computing system could provide more accurate geological information for reservoir characterization.