PCA-FNN based performance prediction for water injection in oilfields.
Tian, Yajuan; Cheng, Guojian; Wang, Zhe
In order to solve the problem of uncertain cycle of water injection in the oilfield, this paper proposed a numerical method based on PCA-FNN, so that it can forecast the effective cycle of water injection. PCA is used to reduce the dimension of original data, while FNN is applied to train and test the new data. The correctness of PCA-FNN model is verified by the real injection statistics data from 116 wells of an oilfield, the result shows that the average absolute error and relative error of the test are 1.97 months and 10.75% respectively. The testing accuracy has been greatly improved by PCA-FNN model compare with the FNN which has not been processed by PCA and multiple liner regression method. Therefore, PCA-FNN method is reliable to forecast the effectiveness cycle of water injection and it can be used as an decision-making reference method for the engineers.
Tian, Y., Cheng, G., & Wang, Z. (2014). PCA-FNN based performance prediction for water injection in oilfields. Advanced materials research, 909, 410-417. https://doi.org/10.4028/www.scientific.net/AMR.909.410
|Journal Article Type||Article|
|Acceptance Date||Sep 9, 1999|
|Deposit Date||Jun 1, 2016|
|Publisher||Trans Tech Publications|
|Peer Reviewed||Peer Reviewed|
|Keywords||Cycle prediction; effect of water injection; FNN; PCA;|
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