Refracturing candidate selection for MFHWs in tight oil and gas reservoirs using hybrid method with data analysis techniques and fuzzy clustering
| Autor: | Liang Tao, Jianchun Guo, Qi-wu Yin, Zhihong Zhao |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Fuzzy clustering
Petroleum engineering Computer simulation Computer science 020209 energy Tight oil Metals and Alloys General Engineering Weight coefficient 02 engineering and technology 010502 geochemistry & geophysics 01 natural sciences Key factors Metallic materials 0202 electrical engineering electronic engineering information engineering Data analysis Selection (genetic algorithm) 0105 earth and related environmental sciences |
| Zdroj: | Journal of Central South University. 27:277-287 |
| ISSN: | 2227-5223 2095-2899 |
| DOI: | 10.1007/s11771-020-4295-0 |
| Popis: | The selection of refracturing candidate is one of the most important jobs faced by oilfield engineers. However, due to the complicated multi-parameter relationships and their comprehensive influence, the selection of refracturing candidate is often very difficult. In this paper, a novel approach combining data analysis techniques and fuzzy clustering was proposed to select refracturing candidate. First, the analysis techniques were used to quantitatively calculate the weight coefficient and determine the key factors. Then, the idealized refracturing well was established by considering the main factors. Fuzzy clustering was applied to evaluate refracturing potential. Finally, reservoirs numerical simulation was used to further evaluate reservoirs energy and material basis of the optimum refracturing candidates. The hybrid method has been successfully applied to a tight oil reservoir in China. The average steady production was 15.8 t/d after refracturing treatment, increasing significantly compared with previous status. The research results can guide the development of tight oil and gas reservoirs effectively. |
| Databáze: | OpenAIRE |
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