Dr. Asmae Dahrabou Email & Phone Number

Greater Pau Area

Neuchâtel, Switzerland

• Optimizing geomechanical parameters estimation workflow: My postdoctoral research builds upon the foundation laid during my PhD, focusing on refining the computational workflow for calibrating geomechanical parameters and predicting failure in deep geothermal boreholes (up to 5 km).• Optimizing a user-friendly software tool I developed during my PhD for calibrating geomechanical models and predicting borehole failure severity in deep geothermal boreholes.• Conducting extensive testing on diverse real cases (Soultz-Sous-Forêts (France), Deep Heat Mining geothermal project (Basel, Switzerland), Haute Sorne (Jura, Switzerland)) to validate the GUI's robustness.

Teaching and mentoring High school, Bachelor and Master students in Mathematics, and Physics.

Copenhagen Metropolitan Area

• Client Interaction: Engaged with clients globally, translating complex technical information into accessible insights tailored to diverse industry needs.• Project Management: Led projects from inception to completion, including scope definition, objective setting, and coordination with engineering teams and clients to ensure timely and budget-compliant delivery.• Lead Generation & Proposal Development: Leveraged data-driven insights to craft targeted proposals and strategies, enhancing lead generation and sales pipeline efficiency.

Zurich, Switzerland

• Developed a systematic stress and strength estimation workflow : Utilized breakout characteristics (width, extension, azimuth) and DITFs in a systematic computational framework to calibrate stress and strength using inverse methods and study the stability of deep geothermal boreholes.• Modified Shen’s method to compute breakout extension : Improved accuracy was achieved by accounting for progressive failure mechanisms, thereby enhancing its applicability across a wider range of wellbore conditions.• Implemented regularized pilot points method (RPPM) in second order calibration : Ensured accurate depiction of stress and strength variations at different depths within the calibration workflow.• Implemented rejection and calibration filtering criteria : Used Andersonian theory and available breakout measurements to ensure robust and realistic estimation of geomechanical parameters.• Developed a computational stochastic methodology for borehole failure prediction : Incorporated first and second order predictions to address parameter variability in the deepest sections of the well.• Explored geomechanical parameter correlations : Utilized Multi-Point Statistics (MPS) to capture complex dependencies between geomechanical parameters and enhance prediction accuracy.• Provided unique in-situ stress and strength depth profiles : Enhanced understanding of subsurface mechanics through evaluation of heterogeneity.• Conducted sensitivity analysis : Evaluated the impact of borehole deviations and breakout intensity on prediction accuracy.• Analyzed natural fractures : clustered the fracture data in fractures sets based on their orientation, computed fracture spacing as well as their slip and dilation tendency.• Created a user-friendly standalone GUI : Facilitated easy transfer of the computational workflow to industrial applications, ensuring accessibility and usability.

Orléans, France

Study of the hydrodynamics and heterogeneity of underground reservoirs as part of the H-CUBE project funded by ANR (National Agency of Research), aimed at improving CO2 sequestration strategies for the preservation of the environment.• Conducted stochastic simulations of Fluvial Reservoir Heterogeneities : generated a diverse set of 3D models representing fluvial reservoir heterogeneities for carbon capture and storage (CCS) applications.• Stochastic Modeling: Used Python and Gocad for stochastic modeling and simulation to address uncertainties in complex geoscience datasets.• Clustering Analysis: Implemented clustering techniques to group similar models and performed hierarchical clustering to enhance data insights.• Topological Analysis: Applied Betti numbers from algebraic topology to analyze and quantify topological features in geoscience models.• Statistical Tests: Performed parametric and non-parametric tests to analyze data variability and compare means across groups.

Marseille, Provence-Alpes-Côte D'Azur, France

— Advanced Statistical Analysis : Conducted various advanced statistical tests, including the Wallis test, analysis of variance (ANOVA), Kruskal-Wallis test, Student’s t-test, regression analysis, and correlation analysis, to characterize differences in reservoir geobody networks and connectivity.— Simulation Model Selection : Applied multivariate statistical methods, including dendrogram analysis, to identify representative simulation models for predicting subsurface fluid flow patterns in fluvialreservoirs.— Scientific Writing: Wrote a scientific paper for the international CTIC (Computational Topology in Image Context) conference, detailing all the developed and used methodologies, results and conclusions

Nancy, Grand Est, France

Title: " Horizontal wells in the reservoir engineering: optimal length "— Conducting a state-of-the-art review in reservoir engineering, covering key phases in the development of horizontal wells for oil and natural gas, including a comparison between horizontal and vertical wells, the typical length of horizontal wells, their applications, design considerations, and well length optimization.— Developing a mathematical model to express the flow rate versus the length of both vertical and horizontal wells.— Optimizing the length of horizontal wells to maximize oil extraction rates.

Doctor Of Philosophy - Phd, Geothermics And Geomechanics

Development of a novel workflow for calibrating geomechanical parameters and predicting the severity of failures in deep geothermal.

Master Of Science - Ms, Reservoir Engineering

Activities and Societies: ENSEM Eco-Marathon ShellBackground in geosciences, geostatistics, reservoir engineering, geospatial data.

Master Of Science - Ms, Engineering Technology, General

A solid background in electrical and mechanical engineering, mathematics, computer science, statistics, the theory of probability, data.

Bachelor Of Science - Bs, Advanced Mathematics, Physics And Computer Science

Intensive training at CPGE (Preparatory Classes to top engineering schools) in Advanced Mathematics, Physics, Programming (MATLAB, C++, C.

Baccalaureate, Computational And Applied Mathematics, With Distinction

BACCALAURÉAT S, specializing in Mathematics, \textit{with distinction