Research Article
Enhancing Fractional Flow Curve Modeling with Advanced Data-driven Techniques: A Comparative Evaluation of Machine Learning Frameworks
Issue:
Volume 14, Issue 1, February 2026
Pages:
1-9
Received:
1 October 2025
Accepted:
14 October 2025
Published:
2 February 2026
Abstract: Modeling fractional flow curves accurately is essential for optimizing reservoir performance and improving hydrocarbon recovery. This study introduces a robust analytical framework utilizing advanced computational techniques to predict fractional flow behavior. The model leverages Gradient Boosted Decision Trees (GBDT) and integrates key physical parameters such as water saturation, viscosity ratios, and relative permeability. The performance of the proposed framework was evaluated using data from reservoir simulations and experiments. The model demonstrated high predictive accuracy, achieving a Root Mean Square Error (RMSE) of 0.005, a Coefficient of Determination (R2) of 0.99, and a Mean Absolute Percentage Error (MAPE) of 1%. Compared to conventional fractional flow models based on Buckley-Leverett theory, which yielded an RMSE of 0.16 and a MAPE of 12.8%, the new approach showed significant improvement. Additionally, it outperformed other computational approaches, including Random Forest (RMSE: 0.02, MAPE: 10.4%) and Artificial Neural Networks (RMSE: 0.016, MAPE: 6.0%), providing both enhanced accuracy and consistency. A sensitivity analysis confirmed the robustness of the model across a range of viscosity ratios, showing strong alignment with physical principles, such as shock front behavior and saturation constraints. The practical utility of this model lies in its ability to accurately predict fractional flow under varying conditions, bridging gaps between analytical methods and data-driven techniques, while remaining computationally efficient. This development enhances the tools available for reservoir engineers, offering new insights for waterflooding strategies, enhanced oil recovery (EOR), and other multi-phase flow applications, with direct relevance to field operations.
Abstract: Modeling fractional flow curves accurately is essential for optimizing reservoir performance and improving hydrocarbon recovery. This study introduces a robust analytical framework utilizing advanced computational techniques to predict fractional flow behavior. The model leverages Gradient Boosted Decision Trees (GBDT) and integrates key physical p...
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Research Article
Performance Evaluation and Comparative Analysis of Avocado Seed Oil as a Sustainable Flow Improver for Waxy Crude-Oil in the Niger Delta Region
Issue:
Volume 14, Issue 1, February 2026
Pages:
10-16
Received:
28 February 2026
Accepted:
18 March 2026
Published:
2 April 2026
DOI:
10.11648/j.ogce.20261401.12
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Views:
Abstract: Precipitation and deposition of paraffin wax in subsea pipelines remain a critical flow assurance challenge in the Niger Delta petroleum industry. As crude oil temperatures drop below the Wax Appearance Temperature (WAT) during transport, high-molecular-weight alkanes crystallize to form an interlocking gel network, leading to increased viscosity, pressure drops, and potential pipeline blocking. Conventional remediation using synthetic Pour Point Depressants (PPDs) like Ethylene Vinyl Acetate (EVA) is economically demanding due to importation costs and poses environmental toxicity risks. This study evaluates the technical feasibility of Avocado Seed Oil (ASO), derived from agricultural waste, as an eco-friendly wax inhibitor. Bio-oil was extracted via Soxhlet extraction using n-hexane and characterized using Gas Chromatography (GC). Its rheological performance was tested on a medium waxy crude sample (API: 32.08°, Wax Content: 33.28%) and benchmarked against commercial EVA. Results indicate that ASO contains 52.23% Oleic acid, a potent crystal modifier. At an optimum concentration of 3% w/v, ASO depressed the pour point from 38°C to 31°C (T = 7°C), matching the efficiency of the synthetic EVA. Furthermore, rheological analysis revealed a significant reduction in plastic viscosity and yield stress at temperatures approaching the pour point (C). The study establishes Avocado Seed Oil as a viable, cost-effective, and sustainable alternative for flow assurance in the Niger Delta waxy crude oil.
Abstract: Precipitation and deposition of paraffin wax in subsea pipelines remain a critical flow assurance challenge in the Niger Delta petroleum industry. As crude oil temperatures drop below the Wax Appearance Temperature (WAT) during transport, high-molecular-weight alkanes crystallize to form an interlocking gel network, leading to increased viscosity, ...
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,
Oluwatoyin Akinsete
