Volume 7, Issue 2, March 2019, Page: 60-66
Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool
Anthony Kerunwa, Department of Petroleum Engineering, School of Engineering and Engineering Technology, Federal University of Technology, Owerr, Nigeria
Obinna Anyanwu Chukwujioke, Department of Petroleum Engineering, School of Engineering and Engineering Technology, Federal University of Technology, Owerr, Nigeria
Received: Mar. 28, 2019;       Accepted: May 15, 2019;       Published: Jun. 12, 2019
DOI: 10.11648/j.ogce.20190702.13      View  139      Downloads  18
Abstract
Predicting the performance of reservoirs help engineers to evaluate reserves, carryout development planning which requires thorough understanding of the reservoir characteristics, develop a model that can mimic the physical processes occurring in the reservoir such that forecast can be made with reasonable accuracy. This study used the material balance software, MBAL which is an allocation tool to evaluate the reserves of reservoir Buza and thereafter predictions were carried out on the reservoir. This was achieved by determining the dominant energy in the reservoir, performing non-linear regression on the uncertain parameters and performance predictions to obtain cumulative oil production and recovery factor. The results obtained showed that water injection at an average rate of 22000STB/D was the main energy in the reservoir providing about 68% of the total energy in the system. The recovery forecast at 31/12/2022 will be 42.8% with cumulative oil production of 98MMSTB. These results are necessary and important for reservoir engineers and policy makers in reservoir management.
Keywords
Performance, Reservoir, Dominant Energy, Production, Recovery, Prediction
To cite this article
Anthony Kerunwa, Obinna Anyanwu Chukwujioke, Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool, International Journal of Oil, Gas and Coal Engineering. Vol. 7, No. 2, 2019, pp. 60-66. doi: 10.11648/j.ogce.20190702.13
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Holstein, E. (2007). Petroleum Engineering Handbook: Reservoir Engineering andPetrophysics. Texas: Society of Petroleum Engineers.
[2]
Mohammed, N., Ameer, S., Ali, S. (2017). Reservoir Performance Prediction Using MBAL Software: A Case Study.
[3]
Gupta, J. (2010). PVT correlations for Indian Crude Oil Using Artificial Neural NetworksJournal of Petroleum Science Engineering 72 (1): p. 93-109.
[4]
Osman, E., Abdel -Wahhab, A., Al-Marhoun, E. (2001). Prediction of oil PVT Propertiesusing Neural Networks. Paper SPE 68233 presented at the SPE Middle East oil show, 17 –20 March, Manama, Bahrain.
[5]
Abu, M. (2007). Reservoir Characterization from Material BalanceResultsAnalysis, paper SPE108648 presented at the SPE International OilConference and Exhibition, 2 – 4 August, Veracruz, Mexico.
[6]
Manzir M. P., Beka F. T. and Kadana R. I. (2015): Predicting Reservoir PerformanceChanges with Time. International Journal for Research in Emerging Science and Technology, Volume-2, Issue-9, Sep-2015.
[7]
Petrowiki. (2018). Material balance in oil reservoirs. http://petrowiki.org/material_balance_in_oil_reservoirs.
[8]
Mogbolu, E., Okereke, O. (2015). Using Material Balance Single Tank Model to Evaluate Future Well Performance in Reservoirs with Distinct Geological Units. Paper SPE 178484 presented at the SPE Nigeria Annual International Conference and Exhibition, 4 - 6 August, Lagos, Nigeria.
[9]
Nwaokorie, C., Ukauku, I. and Emelle, C. (2013). Material Balance Modeling of Reservoirsin a single system: case studies. Paper SPE 160988 presented at the SPE Nigeria AnnualInternational Conference and Exhibition, 29 July – 2August, Lagos, Nigeria.
[10]
Ogbodu, E. D. (2011). Estimation of Fluid Transmissibility and Oil Production Allocationin Faulted Multi Layered Reservoirs using Material Balance Analysis. Paper SPE 152361presented at SPE Annual Technical Conference and Exhibition, 30 October–2 NovemberDenver, Colorado, USA.
[11]
Mogbolu, E., Okereke, O., Olatope, V., Ukauku, I. (2016). Evaluation of the Impact of Inter-Reservoir Communication on Resource Volume Via Material Balance Multi TankModel. Paper SPE 184349 presented at the SPE Nigeria Annual International Conference and Exhibition, 2 – 4 August, Lagos, Nigeria.
[12]
MBalTM Manual, (2007). Reservoir Engineering Tool Kit, User Guide, Version 10.5.
Browse journals by subject