Home > Papers

 
 
Reservoir connectivity evaluation based on the reservoir architecture
Yin Taiju 1 *,ZHANG Changmin 2,GONG Fuhua 2
1.Yangtze University
2.College of Geoscience, Yangtze University
*Correspondence author
#Submitted by
Subject:
Funding: 博士点基金(No.20060489002)
Opened online:15 January 2010
Accepted by: none
Citation: Yin Taiju,ZHANG Changmin,GONG Fuhua.Reservoir connectivity evaluation based on the reservoir architecture[OL]. [15 January 2010] http://en.paper.edu.cn/en_releasepaper/content/39035
 
 
Reservoir connection is a key factor for water flooding recovery. Ways for connection evaluation is though well test or radioactive injection and its output survey. In fact there are great deference in permeability among different genetic sandbodies. In L3 block the permeability of distributaty channel is 4 to 10 times higher than the other genetic sandbody such as levee, crevasse splay sand. Because of its densely well space, we can get detailed genetic sandbodies distribution for every layer. In the framework it is easy to evaluate the connectivity of every layer among inject wells and output wells based on the genetic sandbodies distribution. Generally wells drilled on the same distributay channel or on the different channel sandbody which superposed together is well connected, while the wells suited on the channel and other genetic sand is poor connected. In L3 fault block, the upper layer is better connected than lower layer. The connectivity evaluation is proved by the output and press data. As a summery we believe it is possible to evaluate the connectivity through reservoir architecture analysis.
Keywords:reservoir connectivity;reservoir architecture;fluid flow;reservoir framework
 
 
 

For this paper

  • PDF (0B)
  • ● Revision 0   
  • ● Print this paper
  • ● Recommend this paper to a friend
  • ● Add to my favorite list

    Saved Papers

    Please enter a name for this paper to be shown in your personalized Saved Papers list

Tags

Add yours

Related Papers

Statistics

PDF Downloaded 494
Bookmarked 0
Recommend 5
Comments Array
Submit your papers