Development of an analytical model to predict oil reservoirs performance using mechanical waves propagation

  • Hesham Abu Zaid Belayim Petroleum Company (Petrobel)
  • Sherif Akl Cairo University
  • Mahmoud Abu El Ela Faculty of Engineering - Cairo University
  • Ahmed El-Banbi The American University in Cairo
  • Mohamed Helmy Sayyouh Cairo University

Abstract

The mechanical waves have been used as an unconventional enhanced oil recovery technique. It has been tested in many laboratory experiments as well as several field trials. However, there is no established analytical or numerical modeling technique that can predict the performance of such EOR method. This paper presents a robust forecasting model that can be used as an effective tool to predict the reservoir performance while applying seismic EOR technique. This model is developed by extending the wave induced fluid flow theory to account for the change in the reservoir characteristics as a result of wave application. A MATLAB program has been developed to perform calculations based on the modified theory. The wave’s intensity, pressure, and energy dissipation spatial distributions are calculated. The portion of energy converted into thermal energy in the reservoir is assessed. The changes in reservoir properties due to temperature and pressure changes are considered. The incremental oil recovery and reduction in water production as a result of wave application are then calculated. Results from this program are validated by comparison to the results from Liaohe oil field observations. The model results show that the wave application increases oil production from 33 to 47 ton/day and decreases water-oil ratio from 68 to 48%, which is close to the field measurements. A parametric analysis is performed to identify the important parameters that affect reservoir performance under seismic EOR. In addition, the study determines the optimum ranges of reservoir properties where this technique is most beneficial.

Published
2021-11-17
Section
Petroleum Engineering