A pattern-based approach to waterflood performance prediction using knowledge management tools and classical reservoir engineering forecasting methods

Artun E., Vanderhaeghen M., Murray P.

INTERNATIONAL JOURNAL OF OIL GAS AND COAL TECHNOLOGY, vol.13, no.1, pp.19-40, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 13 Issue: 1
  • Publication Date: 2016
  • Doi Number: 10.1504/ijogct.2016.078046
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.19-40
  • Keywords: waterflooding, predictive data analytics, performance prediction, knowledge management, decline curve analysis, carbonate reservoirs, pattern flood, dashboards, business intelligence, pressure monitoring
  • Middle East Technical University Affiliated: Yes


An efficient and rapid workflow is presented to estimate the recovery performance of an existing vertical-well, pattern-based waterflood recovery design using knowledge management and reservoir engineering in a collaborative manner. The knowledge management tool is used to gather production data and calculate pattern-based recoveries and injection volumes by defining pattern boundaries and allocating annual well injection/production volumes in a systematic manner. Classical reservoir engineering forecasting methods, namely, a combination of oil cut versus cumulative recovery performance curves, and decline curve analyses are applied to forecast the performance of the waterflood pattern of interest. Extrapolating established trends of oil cut vs. recovery for each pattern quantified future performance assessments. Time is attached to the performance by introducing liquid rate constraints. Forecasting using both constant and declining liquid rates differentiated the impact of deteriorating reservoir pressure and oil-cut trends on individual pattern oil rate forecasts thus defining current efficiency of each pattern.