Int. J. of Oil, Gas and Coal Technology   »   2016 Vol.12, No.3

 

 

Title: Performance prediction of a reservoir under gas injection using Box-Jenkins model

 

Authors: Berihun Mamo Negash; Lemma Dendena Tufa; M. Ramasamy

 

Addresses:
Petroleum Engineering Department, Universiti Teknologi Petronas, 32610 Bandar Seri Iskandar, Perak Darul Ridzuan, Malaysia
Chemical Engineering Department, Universiti Teknologi Petronas, 32610 Bandar Seri Iskandar, Perak Darul Ridzuan, Malaysia
Chemical Engineering Department, Universiti Teknologi Petronas, 32610 Bandar Seri Iskandar, Perak Darul Ridzuan, Malaysia

 

Abstract: Current approaches used in prediction of a reservoir performance are less reliable and require much computational effort and time. In this study, system identification, which is common in economics and similar fields, is proposed for predicting performance of a reservoir under gas injection. Efficacy of the proposed method is verified using two synthetic case studies. Box-Jenkins, model structure which is common in system identification, is applied to capture dynamics of the reservoirs and predict their future performance. Box-Jenkins model with order BJ(2-2-2-2-1) is found to be efficient in terms of fitness during validation and having a reasonably less number of parameters. The model is validated using cross validation principle and the results found are auspicious for further investigation. Comparison of BJ(2-2-2-2-1) model with decline curve analysis, which is a well-recognised technique in oil and gas industry, shows that BJ(2-2-2-2-1) is superior in forecasting reservoir performance under gas injection. [Received: October 25, 2014; Accepted: January 31, 2015]

 

Keywords: reservoir performance prediction; system identification; time series analysis; Box-Jenkins model; reservoir modelling; gas injection; oil and gas industry; bottomhole pressure; BHP; reservoirs.

 

DOI: 10.1504/IJOGCT.2016.076808

 

Int. J. of Oil, Gas and Coal Technology, 2016 Vol.12, No.3, pp.285 - 301

 

Available online: 24 May 2016

 

 

Editors Full text accessAccess for SubscribersPurchase this articleComment on this article