ARCHIVES
VOL. 12, ISSUE 10 (2025)
Enhanced oil reservoir simulation using an improved black oil model and modified conjugate gradient algorithm
Authors
Lim Eng Aik
Abstract
This paper proposed an enhanced oil reservoir simulation framework that
integrates an improved Black Oil model with a modified Conjugate Gradient
algorithm to address the limitations of conventional approaches in capturing
complex fluid dynamics and achieving efficient numerical solutions. The
improved Black Oil model incorporates more accurate representations of phase
behavior and interactions, thereby refining the predictions of pressure and
saturation distributions in heterogeneous reservoirs. The modified Conjugate
Gradient algorithm is designed to accelerate convergence and stabilize the
solution process for the large, sparse linear systems arising from the
discretized model equations. Our methodology combines these advancements to
achieve higher computational efficiency without sacrificing physical fidelity,
which is critical for practical reservoir management and decision-making. The
proposed framework demonstrates significant improvements in simulation accuracy
and performance, as validated through comparative studies with existing
methods. Furthermore, the adaptability of the modified solver makes it suitable
for a wide range of reservoir conditions, including those with strong
nonlinearities and multiphase flow effects. This work contributes to the ongoing
efforts in reservoir engineering by providing a robust tool for optimizing
production strategies and reducing uncertainties in reservoir characterization.
The results highlight the potential of our approach to enhance the reliability
of reservoir simulations, ultimately supporting more informed field development
planning and operational efficiency.
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Pages:63-70
How to cite this article:
Lim Eng Aik "Enhanced oil reservoir simulation using an improved black oil model and modified conjugate gradient algorithm". International Journal of Multidisciplinary Research and Development, Vol 12, Issue 10, 2025, Pages 63-70
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