Prediction of Oilfield-Increased Production Using Adaptive Neurofuzzy Inference System with Smoothing Treatment
Joint Authors
Chen, Lin
Ma, Nannan
Wang, Yi
Liu, Zhi-bin
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-19
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
A novel modified adaptive neurofuzzy inference system with smoothing treatment (MANFIS) is proposed.
The MANFIS model considered the smoothing treatment of initial data basing on the adaptive neurofuzzy inference system, and we used it to predict oilfield-increased production under the well stimulation.
Numerical experiments show the prediction result of the novel considering smoothing treatment is better than that without smoothing treatment.
This study provides a novel and feasible method for prediction of oilfield-increased production under well stimulation, and it can be helpful in the further study of oilfield development measure planning.
American Psychological Association (APA)
Chen, Lin& Liu, Zhi-bin& Ma, Nannan& Wang, Yi. 2019. Prediction of Oilfield-Increased Production Using Adaptive Neurofuzzy Inference System with Smoothing Treatment. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1195812
Modern Language Association (MLA)
Chen, Lin…[et al.]. Prediction of Oilfield-Increased Production Using Adaptive Neurofuzzy Inference System with Smoothing Treatment. Mathematical Problems in Engineering No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1195812
American Medical Association (AMA)
Chen, Lin& Liu, Zhi-bin& Ma, Nannan& Wang, Yi. Prediction of Oilfield-Increased Production Using Adaptive Neurofuzzy Inference System with Smoothing Treatment. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1195812
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195812