Publications Scientifiques

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Author: search.filters.author.Hadjadj, Ahmed

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    Evaluating Storage Potential and Integrity of Depleted Reservoirs for CO₂ Injection
    (2025) Zakarya, Belimane; Youcefi, Mohamed Ryad; Benbrik, Abderrahmane; Hadjadj, Ahmed
    As global industrial activity grows, carbon dioxide emissions increase, intensifying greenhouse effect and climate change and demanding solutions beyond renewable energy. This study investigates CO₂ sequestration in subsurface formations as a promising mitigation strategy to support international climate goals and reduce carbon levels. Using CMG 2021 software, different trapping mechanisms, including structural, residual, and solubility trapping, were evaluated in detail to determine their individual and combined contributions to overall storage capacity. Results show that integrating all three mechanisms increases storage potential by 30% compared with structural trapping alone. In addition, geological uncertainty was addressed through Monte Carlo simulations. For that, multiple realizations were generated by varying key reservoir parameters such as porosity, permeability and hysteresis-related parameter. This probabilistic approach allows for a more robust assessment of storage capacity variability and enhances prediction confidence. Furthermore, caprock integrity was evaluated using a two-way geomechanical coupling approach with the Bendis model. The findings indicate that injection-induced pressure reduces effective stresses within the caprock, which may promote tensile failures and create potential leakage pathways. This integrated analysis demonstrates that coupling numerical simulation and probabilistic tools support safer, more effective CO₂ storage, which offers a viable long-term solution for global climate change mitigation efforts.
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    AI-Driven Optimization of Drilling Performance Through Torque Management Using Machine Learning and Differential Evolution
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025) Boukredera, Farouk Said; Hadjadj, Ahmed; Youcefi, Mohamed Riad; Ouadi, Habib
    The rate of penetration (ROP) is the key parameter to enhance drilling processes as it is inversely proportional to the overall cost of drilling operations. Maximizing the ROP without any limitation can induce drilling dysfunctions such as downhole vibrations. These vibrations are the main reason for bottom hole assembly (BHA) tool failure or excessive wear. This paper aims to maximize the ROP while managing the torque to keep the depth of cut within an acceptable range during the cutting process. To achieve this, machine learning algorithms are applied to build ROP and drilling torque models. Then, a metaheuristic algorithm is used to determine the optimal technical control parameters, the weight on bit (WOB) and revolutions per minute (RPM), that simultaneously enhance the ROP and mitigate excessive vibrations. This paper introduces a new methodology for mitigating drill string vibrations, improving the rate of penetration (ROP), minimizing BHA failures, and reducing drilling costs
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    Development of an expert-informed rig state classifier using naive bayes algorithm for invisible loss time measurement
    (Springer Nature, 2024) Youcefi, Mohamed Riad; Boukredera, Farouk Said; Ghalem, Khaled; Hadjadj, Ahmed; Ezenkwu, Chinedu Pascal
    The rig state plays a crucial role in recognizing the operations carried out by the drilling crew and quantifying Invisible Lost Time (ILT). This lost time, often challenging to assess and report manually in daily reports, results in delays to the scheduled timeline. In this paper, the Naive Bayes algorithm was used to establish a novel rig state. Training data, consisting of a large set of rules, was generated based on drilling experts’ recommendations. This dataset was then employed to build a Naive Bayes classifier capable of emulating the cognitive processes of skilled drilling engineers and accurately recognizing the actual drilling operation from surface data. The developed model was used to process high-frequency drilling data collected from three wells, aiming to derive the Key Performance Indicators (KPIs) related to each drilling crew’s efficiency and quantify the ILT during the drilling connections. The obtained results revealed that the established rig state excelled in automatically recognizing drilling operations, achieving a high success rate of 99.747%. The findings of this study offer valuable insights for drillers and rig supervisors, enabling real-time visual assessment of efficiency and prompt intervention to reduce ILT.
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    Numerical study of temperature and pressure effects of a yield-power law fluid flow on frictional pressure losses for laminar and turbulent regimes
    (Taylor and Francis, 2024) Messaoud, Nadia; Hadjadj, Ahmed; Ferroudji, Hicham
    The effective determination of pressure losses depends on accurate knowledge of the drilling fluid rheology. As the fluid circulates deeper around the wellbore, its rheological behavior undergoes significant alterations due to the variations in downhole conditions encountered. The present study investigates the effects of the rheological properties of Yield-power law fluid at various pressures and temperatures on annular pressure losses and velocity profiles. Simulations were performed using Computational Fluid Dynamics to examine the fluid flow in turbulent and laminar regimes. Comparison between numerical, experimental and slot approximation model results showed a good agreement. Results indicated that pressure losses have reduced in both regimes with increasing temperature, at a constant pressure. However the pressure has the opposite effect at a constant temperature. For a drilling fluid flow velocity of 1 m/s, the elevation of temperature from 25 °C to 90 °C, decreases the pressure drop gradient by (31% to 48%) at low and high- pressure conditions respectively. Whereas, the influence of increasing pressure on pressure losses is more apparent at 25 °C. Earlier transition from laminar to turbulent is observed with temperature rise. Therefore, the temperature effect on pressure losses in the turbulent region; is shown for different Generalized Reynolds numbers
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    A stiff-String model for torque and drag analysis in directional wells
    (Springer, 2022) Mayouf, Mansour; Hadjadj, Ahmed
    Overcoming friction forces generated from the contact of tubulars with the wellbore is one of the most important challenges in directional drilling, hence the need to accurately predict these friction forces. This paper undertakes the issue of tubular friction modeling in directional wells and presents a new approach for calculating torque and drag which relies on the beam theory for large deformations in the vertical plane. A comparative study using the soft-string model, a commercial stiff-string model, and the proposed model is carried out. To effectively test the validity and limitations of the proposed model, two wells with different geometries are studied. Results indicate that the proposed model gives similar predictions of the axial force and torque compared to the other industry-validated models where the difference of values at surface did not exceed 1% in all operations for smooth trajectories. Opposed to the soft-string model, the proposed model is able to predict the contact side and provide a profiling of the bending moment across the drill string. It is also able to carry out radial clearance analysis which has been shown to be of great importance when tortuosity is an issue where an increase of up to 10.05% of axial force at surface was observed when the hole diameter was reduced from 0.40 to 0.18 m for a tortuous well. The proposed model suffers, however, from the inability to model the post-buckling behavior of tubulars, which could generally be solved by pairing it with already available buckling models
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    3D numerical and experimental modelling of multiphase flow through an annular geometry applied for cuttings transport
    (Elsevier, 2022) Ferroudji, Hicham; Rahman, Mohammad Azizur; Hadjadj, Ahmed; Ofei, Titus Ntow; Khaled, Mohamed Shafik; Rushd, Sayeed; Gajbhiye, Rahul Narayanrao
    Accurate estimation of volume fraction and pressure gradient is considered indicating parameters of efficient cuttings transportation. It is vital, in this regard, to consider all parameters that can affect cuttings volume fraction and pressure drop during enrollment of the drilling process. The analysis was conducted based on the turbulent flow of a power-law fluid through an annular domain by employing the Finite Volume Method. In addition, dimensional relationships were developed with the Buckingham-π theorem. Before carrying out simulations, the numerical schemes were validated using actual measurements made with the flow loop system available in Texas A&M University at Qatar. The simulation results demonstrated the followings: (i) using a power-law type drilling fluid with a shear-thinning character would reduce energy consumption for an inclination greater than 45°; (ii) inclination angles from 45° to 60° would be least desirable for an effective cuttings transportation with a turbulent Ostwald-de Waele fluid
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    Drill string torsional vibrations modeling with dynamic drill pipe properties measurement and field validation
    (American Society of Mechanical Engineers (ASME), 2022) Boukredera, Farouk Said; Hadjadj, Ahmed; Youcefi, Mohamed Riad
    This paper aims to present the drill string torsional dynamics through a lumped parameter modeling using the basic physical notions with continuous measurement of drill pipe mechanical properties (inertia, damping, and stiffness). The model represents the mechanical properties as a variable for each drilled stand. A rock bit interactions model is employed in the system considering the kinetic friction as variable and depends on surface drilling parameters and the well length. Field data, including surface and downhole recorded velocities, are used to validate the model by comparing both velocities and to confirm the existence of drill string vibrations together with the simulation results (bit velocity)
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    Effect of drill pipe orbital motion on non-Newtonian fluid flow in an eccentric wellbore : a study with computational fluid dynamics
    (Springer, 2021) Ferroudji, Hicham; Hadjadj, Ahmed; Ofei, Titus Ntow; Gajbhiye, Rahul Narayanrao; Rahman, Mohammad Azizur; Qureshi, M. Fahed
    To ensure an effective drilling operation of an explored well, the associated hydraulics program should be established care- fully based on the correct prediction of a drilling fluid’s pressure drop and velocity field. For that, the impact of the drill string orbital motion should be considered by drilling engineers since it has an important influence on the flow of drilling fluid and cuttings transport process. In the present investigation, the finite volume method coupled with the sliding mesh approach is used to analyze the influence of the inner cylinder orbital motion on the flow of a power-law fluid (Ostwald-de Waele) in an annular geometry. The findings indicate that the orbital motion positively affects the homogeneity of the power- law axial velocity through the entire eccentric annulus; however, this impact diminishes as the diameter ratio increases. In addition, higher torque is induced when the orbital motion occurs, especially for high values of eccentricity and diameter ratio; nonetheless, a slight decrease in torque is recorded when the fluid velocity increases
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    Modeling surge pressures during tripping operations in eccentric annuli
    (Elsevier, 2021) Belimane, Zakarya; Hadjadj, Ahmed; Ferroudji, Hicham; Rahman, Mohammad Azizur; Qureshi, M. Fahed
    The aim of this paper is to present a new numerical model to study the drilling fluid flow through eccentric annulus during tripping operations and to investigate the effect of the eccentricity on the annular velocity and apparent viscosity profiles. Many published works studied surge and swab phenomenon using simplified numerical models that do not consider the azimuthal variation of the shear stress in the eccentric annuli. In this paper, the developed numerical model takes into consideration this variation. Non-orthogonal, curvilinear coordinates were used to generate a body-fitted elliptic mesh that maps the irregular complicated eccentric annulus into a simple rectangle where flow equations can be discretized using the finite difference method then solved numerically. Besides, a commercial software (ANSYS Fluent 19R3) was used to support the findings of the numerical model. Results of these models were validated against the experimental data from literature where good agreement was observed with an average relative error of 2.6%, 3.8%, and 6.8% for the three Herschel-Bulkley fluids studied in the eccentric case. The profiles of velocity and viscosity were plotted, the contours showed that we cannot use an average velocity or a single value for the apparent viscosity to describe the drilling fluid flowing through an eccentric annulus, but, the whole profile should be used, instead. The developed numerical model was used in a parametric study to investigate the effect of eccentricity on the relationship between surge pressure and the relevant drilling parameters namely tripping velocity, annular geometry, and fluid rheological properties. The results showed that the eccentricity decreases the surge pressure independently of the previous parameters and that the rate of decrease varies from one parameter to another. The outcome of this parametric study was used to construct a surrogate model using Random Forest Regressor. Predictions from the surrogate model fit the numerical data very well with R-squared of 0.99 and 0.97 for training and test data, respectively
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    Real-Time prediction of plastic viscosity and apparent viscosity for Oil-Based drilling fluids using a committee machine with intelligent systems
    (Springer, 2022) Youcefi, Mohamed Riad; Hadjadj, Ahmed; Bentriou, Abdelak; Boukredera, Farouk Said
    he prediction of drilling mud rheological properties is a crucial topic with significant importance in analyzing frictional pressure loss and modeling the hole cleaning. Based on Marsh viscosity, mud density, and solid percent, this paper implements a committee machine intelligent system (CMIS) to predict apparent viscosity (AV) and plastic viscosity (PV) of oil-based mud. The established CMIS combines radial basis function neural network (RBFNN) and multilayer perceptron (MLP) via a quadratic model. Levenberg–Marquardt algorithm was applied to optimize the MLP, while differential evolution, genetic algorithm, artificial bee colony, and particle swarm optimization were used to optimize the RBFNN. A databank of 440 and 486 data points for AV and PV, respectively, gathered from various Algerian fields was considered to build the proposed models. Statistical and graphical assessment criteria were employed for investigating the performance of the proposed CMIS. The obtained results reveal that the developed CMIS models exhibit high performance in predicting AV and PV, with an overall average absolute relative deviation (AARD %) of 2.5485 and 4.1009 for AV and PV, respectively, and a coefficient of determination (R2) of 0.9806 and 0.9753 for AV and PV, respectively. A comparison of the CMIS-AV with Pitt's and Almahdawi's models demonstrates its higher prediction capability than these previously published correlations