My name is Ildar Abdulin. Exp.:
• a total of 5+ years of experience in mathematical modeling of oil production
(computational fluid dynamics, diff. equations, numerical methods, data science).
Highlights
In 2023 I have developed a predictive hydrodynamics model (2D diffusion differential equation) using Python 3 open source libraries, maximum deviation with commercial simulator tNavigator - 5% github.com/ResearchMachine/hydrodynamic-in-predictive-complex
In 2021 I have developed a data analysis methodology for experimental groups of oil wells, proposed recommendations to technology of production doi.org/10.24887/0028-2448-2021-9-76-81
In 2020 I have developed a new architecture of the hydrodynamic model taking into account new physical properties, which increased the accuracy of the model by 20% doi.org/10.24887/0028-2448-2020-1-46-49
1.5 years в Gazprom Neft (the third largest oil producer in Russia) as lead Model Engineer / Data Analyst / Data Scientist in 3 projects: 03.2020 – 09.2021, 08.2021 – 01.2022, 08.2022 – 01.2023 and private consultations. Department - Technology Partnerships LLC (Bazhen Technology Centre). Located in Moscow, Russia. Links:
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3 years 11 months in math lab. GAMMETT as Research Engineer (application of modern maths for architect of oil production predictive models): 2017 – 2020. Math lab. GAMMETT is engaged R&D in the field of mathematical modeling and group analysis of differential equations. Located in Ufa State Aviation Technical University, Ufa, Russia. Links:
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>5 years freelance consultations on mathematics and analytics: statistics, diff. equations, complex analysis and etc.
Education and Certificates
2018 and 2016, MSc and BSc of Applied Mathematics and Computer Science, Ufa State Aviation Technical University. [MSc Diploma], [BSc Diploma]. Links:
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2020, Data Analysis Based on Machine Learning, Bashkir State University, Russia
Full List of Projects
💼 2023, Data Mining of Commercial Real Estate in Moscow in Team with Real Estate Expert, Freelance, Python 3 github.com/ResearchMachine/ml-mvp-insight-in-real-estate-moscow
• Data parser for daily monitoring from website of one segment of Moscow real estate was developed (≈1500 objects) • Top30 extractor algorithm of undervalued commercial real estate was developed • 3 objects from result of Top30 extractor algorithm were marked by Real Estate Experts as more than 30% below market value
💼 2023, Forecast of Oil Production of Special Group of Wells. Hydrodynamic Simulator Development, Finite Element Method , Gazprom Neft, Python 3 github.com/ResearchMachine/hydrodynamic-in-predictive-complex/blob/main/FipyFracSolver.ipynb
• Target - production volume of oil well accumulated for 180 days
• A model solver based on an open-source library has been developed (Fipy lib)
• 95% agreement developed model with results of the commercial simulator (tNavigator)
• MVP App with visualization of the necessary parameters was developed
💼 2022, Oil Production Predictive Model Transfer. VBA Parser from Excel Spreadsheet to VBA Code, Gazprom Neft, VBA github.com/ResearchMachine/parcing-of-predictive-complex
Improved the usability of the company's tool (>600 Excel formulas) by developing a VBA application with a simple GUI
Corrected the mathematics of the company model, which increased its accuracy
💼 2021, Data Mining of a small group of oil wells with new production technology. Recommendations of Improving Oil Production Process. , Gazprom Neft, Python 3 doi.org/10.24887/0028-2448-2021-9-76-81
Target - production volume of oil well •
Significant factors with high statistical significance were discovered, which considerably impact the volume of oil production •
+110% increase in oil production is expected if Data Mining recommendations and certain conditions are met •
A forecast of the oil production volume for a new well was conducted using the Monte Carlo method
💼 2020, New architecture of the hydrodynamic model taking into account of fractal properties of oil reservoir. Inverse coeff problem for Diffusion Equation. , math lab. GAMMETT, Maple doi.org/10.24887/0028-2448-2020-1-46-49, elibrary.ru/kbretj
• +20% accuracy achieved by developing a new model accounting for fractal properties of the medium •
+10% accuracy achieved without increasing complexity, through adjustments in input data averaging •
An algorithm for calculating new parameters from real data has been developed •
The model has been tested using Rosneft's project institute's commercial simulator, more complex scenarios of using model (oil + gas 2 phase flow) are researched
💼 2019, . Diffusion equation model with the Riesz potential (memory). Accounting for Special Properties of Reservoir During Oil Production, math lab. GAMMETT, Maple + Python 3 ui.adsabs.harvard.edu/abs/2020AIPC.2293P0071A
Developed a computational algorithm for math. physics models with new architecture (memory accounting)
💼 2018, Derivation and Study of New Mathematical Model of Oil Movement in Fractally Inhomogeneous Media., math lab. GAMMETT, Maple + Python 3 elibrary.ru/ytsxtn, elibrary.ru/vkekou
Developed and prototyped a new hydrodynamic model architecture that allows for more accurate consideration of the heterogeneity of a porous medium. Differential calculus on fractals.
🎓 2018, Prototyping of math models of fluid flow in media with fractal properties, Master Degree Project
🎓 2016, Solutions of System of Nonlinear Partial Differential Equations. Exact solutions of one of the three-phase filtration model, Bachelor Degree Project