Productivity prediction and main layer optimization for composite reservoir

  • CHEN Xiaoer ,
  • FAN Kun ,
  • XIONG Yan ,
  • WANG Xiaolan ,
  • WANG Dan ,
  • CHEN Dan
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  • (1. Research Institute of Exploration and Development, PetroChina Changqing Oilfield Company, Xi’an 710018, China; 2. National Engineering Laboratory for Exploration and Development of Low-permeability Oil and Gas Fields, Xi’an 710018, China; 3. Research Center of Ultra-low Permeability Reservoir, PetroChina Changqing Oilfield Company, Xi’an 710018, China

Online published: 2013-11-26

Abstract

There are many factors affected the production of low permeability reservoir, among which the reservoir pore space, permeability and oiliness are the main factors. Taking H195 well field as an example, through correlation analysis of logging parameters and initial productivity, this paper obtained the main logging parameters that can reflect the reservoir characteristics, and established productivity prediction models of productivity coefficient and aggregate index. By analyzing the results of the two methods, we turned the productivity prediction technology from single well to single sand layer, obtained successive evaluation parameters of reservoir productivity, and then optimized main layers and main contributed parts, which could guide the design of horizontal well trajectory.

Cite this article

CHEN Xiaoer , FAN Kun , XIONG Yan , WANG Xiaolan , WANG Dan , CHEN Dan . Productivity prediction and main layer optimization for composite reservoir[J]. Lithologic Reservoirs, 2013 , 25(6) : 117 -121 . DOI: 10.3969/j.issn.1673-8926.2013.06.022

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