Ildar Abdulin

Skilled in predictive engineering analytics and quantitative research.

Location: EU     LinkedIn: linkedin.com/in/abdulin/

💼 Relevant Projects

1. Gazprom Neft | Hydrodynamic Oil Production Forecasting (2D Quasilinear Diffusion Equation) | Python 3 | 08/2022 – 01/2023
Objective: Develop open-source alternative to commercial simulators for production forecasting under reservoir engineering constraints
Implementation: Designed finite element solver (FiPy) implementing pressure-dependent permeability modeling, benchmarked against tNavigator
Outcome: Achieved 95-99% parity with industry-standard simulator results while eliminating arbitrary parameter tuning [GitHub: Solver Implementation]


2. Freelance | Commercial Real Estate Valuation Analytics (Moscow Market) | Python 3 | 05/2023 - 07/2023
Objective: Identify systematically undervalued commercial properties in high-potential Moscow districts
Implementation: Built CIAN.ru web scraper (BeautifulSoup/CloudScraper) + XGBoost valuation model with expert-defined feature engineering
Outcome: Delivered 3 expert-validated investment opportunities within MVP period, reducing noise by 40% through NLP filtering [GitHub: Parser Architecture]


3. Gazprom Neft | Excel-to-VBA Forecasting Model Migration | VBA | 08/2021 – 01/2022
Objective: Modernize legacy spreadsheet-based forecasting model (600+ formulas across 7 sheets)
Implementation: Developed automated formula parser converting Excel logic to modular VBA with unified GUI interface
Outcome: Eliminated manual calculation errors and improved operational efficiency through single-interface solution [GitHub: Conversion Module]


4. Gazprom Neft | Production Drivers Analysis & Stochastic Forecasting | Python 3 | 03/2020 – 09/2020 | [1] – Publication
Objective: Quantify key production influencers and develop probabilistic forecasting framework
Implementation: Multivariate regression analysis + Monte Carlo simulation
Outcome: Identified 5 statistically significant production drivers (p<0.01) with SHAP value interpretation


5. Research lab. GAMMETT | Fractal Reservoir Pressure Modeling | Maple | 2020 | [2, 4] – Publications
Objective: Incorporate fractal properties of the medium into a mathematical model for oil pressure.
Implementation: Designed a new model in collaboration with a Physicist Scientist. Tested using real-world data.
Outcome: The use of the model can improve the accuracy of predicted values by up to 20%.


6. Research lab. GAMMETT | Singular PDE Numerical Methods | Maple/Python 3 | 2019 | [3] – Publication
Objective: Develop stable numerical scheme for integro-differential equation
Implementation: Created adaptive mesh refinement algorithm handling solution singularities
Outcome: Published convergence proof and field validation results


7. Research lab. GAMMETT | Fractal Derivatives in Oil Production Modeling | Maple / Python 3 | 2018 | [5, 6] – Publications
Objective: Develop and compare new modeling approach (fractal derivative) for physical model with differential equations (oil production)
Implementation: Prototyped a Monte Carlo algorithm article arxiv.org/abs/0906.0676. Developed a model with fractal derivatives in collaboration with two Research Scientists.
Outcome: Conducted comparative analysis with a simpler model. [EN Description]

📈 Relevant Experience

🎓 Education and Certifications

🛠️ Skills

📝 Publications

1. Oil Industry Journal (Scopus-indexed), Production forecast method based on statistical analysis of a small sample of production data for an unconventional formation, 2021.
2. Oil Industry Journal (Scopus-indexed), Identification of fractal properties and parameters upscaling of layered heterogeneous medium, 2020.
3. American Institute of Physics Conference Series (Scopus-indexed), Numerical investigation of radial steady-state fluid flow model with Riesz potential, [PDF], 2020.
4. One-Dimensional Models of Single-Phase Fluid Flow in Media with Fractal Structure, Conference "12th All-Russian Congress on the Fundamental Problems of Theoretical and Applied Mechanics", 2019.
5. Modified Buckley-Leverett Models Based on Power Law and Fractal Calculus, Conference "Nigmatullin Readings" (Math Modeling), 2018.
6. Mathematical Models of Fluid Flow in Porous Media with Fractal Properties of Geometrical Characteristics, Conference "Current Issues in Applied Mathematics", 2018.
7. (page 299) Models of Two-phase Filtration in Fractal Porous Media, Conference "International Conference on Mathematical Modelling in Applied Sciences", 2017.