Research Article
Geomechanical and Structural Investigations of Production-Induced Stress Changes in Reservoir Sands in Part of Niger Delta Nigeria
Issue:
Volume 10, Issue 2, December 2026
Pages:
63-84
Received:
17 October 2025
Accepted:
8 June 2026
Published:
11 July 2026
Abstract: Hydrocarbon production reduces pore-fluid pressure and increases the effective stress acting on the grain framework of reservoir rocks. This process induces reservoir deformation, compaction, and stress redistribution, often manifesting as fault reactivation, surface subsidence, wellbore instability, and 4D seismic time shifts. In this study, we present a geomechanical and structural interpretation of production-induced stress changes in the Kolo-Creek Field, Coastal Swamp Niger Delta, Nigeria. The analysis integrates 3D seismic interpretation, geomechanical evaluation, well-log analysis, and production data. Time-lapse seismic surveys acquired in 1997 (base) and 2009 (monitor) show clear 4D responses with a root-mean-square repeatability ratio (RRR) of 0.38, indicating excellent survey repeatability. The seismic interpretation reveals fault reactivation and fracturing associated with production-induced stress changes. Geophysical well logs from seven wells were used to delineate and correlate three reservoir zones (Sand A, Sand B, and Sand C). Petrophysical analysis indicates low shale content ranging from 7.74–37.44%, high porosity values between 0.19 and 0.36), and excellent permeability varying from 375–3327 mD, which is consistent with high-quality, coarse-grained sandstones. Production and pressure data provided by SPDC show a decline from 1592.55 to 400.34 bbl/day and from 4766 to 3103 psi over 12 years, respectively, corroborating with the geomechanical interpretation. The integration of geomechanics with seismic and structural analysis demonstrates the influence of reservoir stress changes on fault behavior and reservoir performance, providing insights to optimize production and manage risks in similar deltaic settings. This study could lead to Wellbore Stability Management; Using stress change predictions to guide well placement and drilling orientation, minimizing risks of shear failure, casing deformation, and production losses.
Abstract: Hydrocarbon production reduces pore-fluid pressure and increases the effective stress acting on the grain framework of reservoir rocks. This process induces reservoir deformation, compaction, and stress redistribution, often manifesting as fault reactivation, surface subsidence, wellbore instability, and 4D seismic time shifts. In this study, we pr...
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Research Article
Hybrid Multi-phase Choke Model for Predicting Pressure Drop and Choke Size for Production Optimization
Issue:
Volume 10, Issue 2, December 2026
Pages:
85-99
Received:
29 June 2026
Accepted:
11 July 2026
Published:
22 August 2026
DOI:
10.11648/j.pse.20261002.12
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Abstract: This study addresses the problem of pressure drop and choke size prediction a in high water -cut oil wells by developing a New Multi-Phase Choke Formula (NMPCF) (a hybrid multi-phase choke model), to improve prediction accuracy and operational performance. A robust predictive model was developed that integrates mechanistic, empirical, and machine learning approaches for estimating pressure drop (ΔP) and choke size (Cₛ). Historical well test data were obtained from two fields in Niger Delta with choke sizes ranging from 0.1875-0.4375 inches, flow rates of 270-1673 bbl/day, and water cuts up to 40.26%. Data preprocessing and model implementation were carried out using Python, leveraging libraries such as NumPy, SciPy, and scikit-learn. Random Forest regression was trained on an 80/20 train-test split to learn nonlinear relationships and provide correction terms to the mechanistic model. Results show that the coefficient of determination (R2) is greater than 0.85. The dataset of 1000 samples exhibited a mean water cut of 0.52 and mean choke size of 63.87 inches enhancing model generalization. Pressure drop increased nonlinearly with water cut (Wc), particularly beyond Wc = 0.5, due to increased mixture density and viscosity. The model maintained stable predictions across average flow rates of 420.71 bbl/day. The NMPCF model provides improved accuracy for predicting pressure drop and choke size, making it suitable for optimizing production in high water-cut oil wells.
Abstract: This study addresses the problem of pressure drop and choke size prediction a in high water -cut oil wells by developing a New Multi-Phase Choke Formula (NMPCF) (a hybrid multi-phase choke model), to improve prediction accuracy and operational performance. A robust predictive model was developed that integrates mechanistic, empirical, and machine l...
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