Integrated Multiple Parameters Method for Candidate Selection in Refracturing Treatment
- Authors
- Mingjing Lu (China University of Petroleum, Colorado School of Mines) | Yuliang Su (China University of Petroleum) | Wendong Wang (China University of Petroleum) | Ge Zhang (Xianhe Oil producing Plant, Shengli Oilfield, Sinopec)
- DOI
- https://doi.org/10.2523/IPTC-19102-MS
- Document ID
- IPTC-19102-MS
- Publisher
- International Petroleum Technology Conference
- Source
- International Petroleum Technology Conference, 26-28 March, Beijing, China
- Publication Date
- 2019
- Document Type
- Conference Paper
- Language
- English
- ISBN
- 978-1-61399-619-5
- Copyright
- 2019. International Petroleum Technology Conference
- Disciplines
- 2.4 Hydraulic Fracturing, 3 Production and Well Operations, 4 Facilities Design, Construction and Operation, 3.5.1 Candidate Selection, 4.1 Processing Systems and Design, 2 Well completion, 2.5.5 Re-fracturing, 4.1.2 Separation and Treating, 3.5 Well Intervention
- Keywords
- refracturing, restimulation, data analysis, integrated parameters, Candidate selection
- Downloads
- 1 in the last 30 days
- 154 since 2007
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| SPE Non-Member Price: | USD 23.00 |
Refracturing treatment are performed since stimulation effect won't last for entire life. Screening wells for refracturing needs a systematic analysis of huge amounts of data. With literature review, it is obviously that there are many factors controlling the success of refracturing and factors may vary in different oilfields. Proper factors and data processing are the primary principle in candidate selection. The Integrated Multiple Parameters (IMP) method is presented to provide assists in selecting candidate wells.
After deeply researching over 200 restimulated wells, all factors thought to be related with success of refracturing are listed and analyzed, results show that single factor may have great influence on restimulation but no significant patterns can be obtained since too many factors making things complicated. The IMP method proposes five parameters which are all integrated by those single factors. It is emphasized that all parameters have physical or engineering meanings which makes it easier to quantify their correlation in refracturing. Besides, all the parameters are dimensionless which makes it easier for using in mathematical models and statistical analysis.
The five dimensionless parameters are developed considering the most important aspects of candidate wells selection which are showed as followed: fracture reorientation, well completion, reservoir depletion, production decline, oil-water well connectivity. Parameters are calculated for all the restimulated wells to dig into their correlation with the outcomes of refracturing. A simple decision model is built to help with screening wells for refracturing. Results shows that it is more executable to evaluate and predict the success of refracturing with these dimensionless parameters. Fracture reorientation parameter is the primary one to be considered since it leads to fracture reorientation which brings significant production increment. Then two types of potential wells are picked: (a) wells with dissatisfied initial well completion, low production decline rate and high oil-water connectivity parameter; (b) wells with satisfied initial well completion, high well completion parameter, low production decline parameter, reservoir depletion parameter and low oil-water connectivity parameter for wells that are not easy for fracture reorientation. Wells selected are proved to be refracturing potential which verify the reliability and accuracy of IMP method.
The IMP method is an improved approach integrating most of the important factors which makes candidate selection much more predictable and it succeeds in screening out more than 80% of the potential wells in field test. Also, it can be applied widely in different oilfields since all the parameters are dimensionless. By combining with some mathematical methods such as neural networks, it can even predict increment of the restimulation treatment.
| File Size | 1 MB | Number of Pages | 15 |
