Data Analysis and Application Guidelines for the Microgel Field Applications
Abstract
Excess water production is a major problem in water-flooded mature oilfields. Recently, using microgel treatment as a conformance control method to reduce water production has drawn increasing attention in oil industry. The success of microgel treatments highly depends on in-depth understanding where and when microgel can be successfully applied, how to design the injection parameters, and how well the performances of microgel treatments in different reservoir conditions. To better solve these problems, a total of 154 field application data from microgel-treated injection wells was collected from 2005 to 2016. These data are statistically analyzed by using histograms, boxplots, and scatterplots. Histograms are used to analyze the reservoir and well characteristic data in order to find out where and when microgels are generally used. Scatterplots are used to uncover some general trends that can guide field engineers to design injection parameters and improve the treatment performances. Boxplots compare the injection parameters among different types of reservoirs and outline special cases that are far different from the majority of the cases. These special cases are further studied because they contain additional information during the treatment. Throughout the comprehensively data analysis, the application guidelines for microgel treatments are presented, which includes screening guidelines, design considerations, and treatment performances. The instructional guidelines can help to maximize the likelihood of microgel treatment projects being technically successful.
Recommended Citation
Y. Qiu et al., "Data Analysis and Application Guidelines for the Microgel Field Applications," Fuel, vol. 210, pp. 557 - 568, Elsevier Ltd, Jan 2017.
The definitive version is available at https://doi.org/10.1016/j.fuel.2017.08.094
Department(s)
Geosciences and Geological and Petroleum Engineering
International Standard Serial Number (ISSN)
0016-2361
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Elsevier Ltd, All rights reserved.
Publication Date
01 Jan 2017