Block Selection Mode of the Fire Flooding Based on Influence Factors Analysis

Yuan Shi-bao1, *, Jiang Hai-yan1, Wang Boyi1, Li Qing-qing2
1 Xi’an Shiyou University, Xi’an 710065, P. R. China
2 China University of Petroleum, Qing Dao 266555, P. R. China

Article Metrics

CrossRef Citations:
Total Statistics:

Full-Text HTML Views: 914
Abstract HTML Views: 530
PDF Downloads: 4
ePub Downloads: 3
Total Views/Downloads: 1451
Unique Statistics:

Full-Text HTML Views: 492
Abstract HTML Views: 344
PDF Downloads: 4
ePub Downloads: 3
Total Views/Downloads: 843

© 2017 Shi-bao et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Xi'an Shiyou University, Xi'an, Shaanxi Province, 710065, P. R. China; Tel: +86 15339145717; E-mails:,



In-situ combustion is a complex process with multi-factors, like geology, development and engineering. All of the factors can affect the ultimate effect of in-situ combustion.


Strengthen the research of candidate reservoir screening method and mode for fire flooding.


On the basis of summarizing formers' single factor screening conditions, and according to the strength degree of the influence factors on geology and development. The candidate reservoirs are divided into three types for screening, first, second and not suitable. Then the in-situ combustion process is taken as a grey system on the analysis of the influence factors. The fire flooding evaluation model is established using the method of correlation analysis that selects the main factors.


Block selection mode of fire flooding is established and using an example to calculate and evaluate the applicability.


This fire flooding reservoir screening model breaks through the traditional single index screening model, and selects out suitable reservoirs for fire flooding, which improved the test success rate. The J function is convenient to calculate the fire flooding effect, and accurately guide the in-situ combustion experimental blocks screening and in-situ combustion project evaluation.

Keywords: Uncertainty, Multi-factors, Correlation analysis, Grey system, Fire flooding, Porosity.