Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool

Anthony Kerunwa; Obinna Anyanwu Chukwujioke

doi:doi:10.11648/j.ogce.20190702.13

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Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool

Anthony Kerunwa, Obinna Anyanwu Chukwujioke

Published in International Journal of Oil, Gas and Coal Engineering (Volume 7, Issue 2)

Received: 28 March 2019 Accepted: 15 May 2019 Published: 12 June 2019

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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.

Published in	International Journal of Oil, Gas and Coal Engineering (Volume 7, Issue 2)
DOI	10.11648/j.ogce.20190702.13
Page(s)	60-66
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Performance, Reservoir, Dominant Energy, Production, Recovery, Prediction

References

[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]	MBal^TM Manual, (2007). Reservoir Engineering Tool Kit, User Guide, Version 10.5.

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APA Style

Anthony Kerunwa, Obinna Anyanwu Chukwujioke. (2019). Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool. International Journal of Oil, Gas and Coal Engineering, 7(2), 60-66. https://doi.org/10.11648/j.ogce.20190702.13

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ACS Style

Anthony Kerunwa; Obinna Anyanwu Chukwujioke. Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool. Int. J. Oil Gas Coal Eng. 2019, 7(2), 60-66. doi: 10.11648/j.ogce.20190702.13

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AMA Style

Anthony Kerunwa, Obinna Anyanwu Chukwujioke. Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool. Int J Oil Gas Coal Eng. 2019;7(2):60-66. doi: 10.11648/j.ogce.20190702.13

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@article{10.11648/j.ogce.20190702.13,
  author = {Anthony Kerunwa and Obinna Anyanwu Chukwujioke},
  title = {Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool},
  journal = {International Journal of Oil, Gas and Coal Engineering},
  volume = {7},
  number = {2},
  pages = {60-66},
  doi = {10.11648/j.ogce.20190702.13},
  url = {https://doi.org/10.11648/j.ogce.20190702.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ogce.20190702.13},
  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.},
 year = {2019}
}

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TY  - JOUR
T1  - Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool
AU  - Anthony Kerunwa
AU  - Obinna Anyanwu Chukwujioke
Y1  - 2019/06/12
PY  - 2019
N1  - https://doi.org/10.11648/j.ogce.20190702.13
DO  - 10.11648/j.ogce.20190702.13
T2  - International Journal of Oil, Gas and Coal Engineering
JF  - International Journal of Oil, Gas and Coal Engineering
JO  - International Journal of Oil, Gas and Coal Engineering
SP  - 60
EP  - 66
PB  - Science Publishing Group
SN  - 2376-7677
UR  - https://doi.org/10.11648/j.ogce.20190702.13
AB  - 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.
VL  - 7
IS  - 2
ER  -

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Author Information

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

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APA Style

Anthony Kerunwa, Obinna Anyanwu Chukwujioke. (2019). Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool. International Journal of Oil, Gas and Coal Engineering, 7(2), 60-66. https://doi.org/10.11648/j.ogce.20190702.13

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ACS Style

Anthony Kerunwa; Obinna Anyanwu Chukwujioke. Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool. Int. J. Oil Gas Coal Eng. 2019, 7(2), 60-66. doi: 10.11648/j.ogce.20190702.13

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AMA Style

Anthony Kerunwa, Obinna Anyanwu Chukwujioke. Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool. Int J Oil Gas Coal Eng. 2019;7(2):60-66. doi: 10.11648/j.ogce.20190702.13

Copy | Download

@article{10.11648/j.ogce.20190702.13,
  author = {Anthony Kerunwa and Obinna Anyanwu Chukwujioke},
  title = {Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool},
  journal = {International Journal of Oil, Gas and Coal Engineering},
  volume = {7},
  number = {2},
  pages = {60-66},
  doi = {10.11648/j.ogce.20190702.13},
  url = {https://doi.org/10.11648/j.ogce.20190702.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ogce.20190702.13},
  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.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Performance Prediction of Niger Delta Reservoir BUZA Using Allocation Tool
AU  - Anthony Kerunwa
AU  - Obinna Anyanwu Chukwujioke
Y1  - 2019/06/12
PY  - 2019
N1  - https://doi.org/10.11648/j.ogce.20190702.13
DO  - 10.11648/j.ogce.20190702.13
T2  - International Journal of Oil, Gas and Coal Engineering
JF  - International Journal of Oil, Gas and Coal Engineering
JO  - International Journal of Oil, Gas and Coal Engineering
SP  - 60
EP  - 66
PB  - Science Publishing Group
SN  - 2376-7677
UR  - https://doi.org/10.11648/j.ogce.20190702.13
AB  - 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.
VL  - 7
IS  - 2
ER  -

Copy | Download