I am an experienced data scientist and engineer, and a life-long learner. I am skilled in analyzing data, developing creative AI and ML solutions, and translating them into winning business strategies.
I was exposed to data analytics during my first job at MI3 Petroleum Engineering. I lead a project in collecting, cleaning, and analyzing data to predict the candidate oilfields for future CO2 injection, and enabled our clients to make difficult decisions under subsurface uncertainty. Eventually, the predictive model and the database were sold to a major oil and gas producing company in the US six months after preparation.
My enthusiasm for learning and interest in finding better-informed decisions have taken me from petroleum engineering to data science. As a principal investigator in NeuDax, I raised and managed $225K from the National Science Foundation in 2019 for developing an AI-based software. By leveraging the machine learning algorithms and feature engineering, I build predictive models to forecast the production and optimize the hydraulic fracturing characteristics in unconventional reservoirs. Working with top engineers and data scientists at NeuDax showed me understanding the field development business and having a strong background in data analytics can help me avoid misleading interpretations. By work in a fast-paced, collaborative environment, I gain lots of experience in developing a prototype, testing, and improving the product development process.
Everything I have engaged in so far has all been driven by my keen interest in learning and pushing boundaries. Even as a petroleum engineer, I dedicated some part of my day to learning new things. With an engineering background, I am constantly working to improve my skills, and currently pursuing Business Analytics Program at Harvard University.
Data Scientist | Chief Engineer (September 2019 – Present), NeuDax Data Analytics - Houston, Texas
• Lead Permian basin exploratory data analysis. The outcomes are used to develop predictive models based on specific features and clustered data.
• Develop Python scripts and predictive models. By leveraging AI and ML methods, create models for oil and gas production companies to design their horizontal wells and fracturing stages to maximize well production and minimize their cost within two weeks instead of months.
• Use DBSCAN to find pad locations automatically. Applied this unsupervised machine learning technique to identify the pad location. The outcome is used as a feature to calculate well spacing and increase the predictive model accuracy.
• Visualize completion evolution in the Permian basin. This is a Voila model that runs on AWS and visualizes incremental changes of proppant and fluid loads and winning practices in the Permian basin.
• Create dashboards on Google Data Studio to compare the performance of production companies in the Permian basin and reveal the successful practices. The results of this work have been submitted as a paper for URTeC 2021.
• Accomplish decline curve analysis for 6000 wells in Permian, DJ, and Appalachian basins. By completing those projects, NeuDax client could decide about investing on few oil and assets in Appalachian and Permian basins.
• Set-up AWS EC2 to run the NeuDax predictive models on cloud.
• Brought $14K project from Great Western Oil and Gas company in 2019 for analyzing well tortuosity data.
• Lead customer discovery to address the customer pain points and identify the value propositions. Identify the market, validate customer segment, and build the minimum viable product using the outcomes of those 150 customer discovery interviews.
• Raised and managed $225K found from National Science Foundation in 2019 for developing an AI-based software to improve the recovery and profitability of unconventional oil and gas production.
Reservoir Engineer (November 2016 – June 2019), Apex Petroleum Engineering (previously SIGMA3 Integrated Reservoir Solutions) - Englewood, Colorado
• Accelerated deployment of the FieldPro software by completing reservoir modeling of few unconventional fields in the Permian basin using CMG, FieldPro, and IHS Harmony. The comprehensive results of this work were used to debug the back-end code and modify the user interface.
• Matched depth values of logs using Techlog. The results improved the reserve estimation in the reservoir characterization practices.
Reservoir Engineer | Data Analyst (September 2012 – October 2016), MI3 Petroleum Engineering - Golden, Colorado
• Coordinated and developed a comprehensive CO2-EOR database sold to a major oil and gas production company six months after preparation. I lead the screening project to identify potential oil fields for CO2-EOR in the US. Completed a feasibility study for CO2 -EOR implementation at the candidate fields in six states in the US.
• Fulfilled economic analysis and risk assessments of CO2-EOR implementation in fields and pilots. Those economic analyses helped operator companies to make decision based on cost and availability of CO2.
• Launched reservoir simulation using Tempest-MORE to fulfill the reserve estimation, forecast generation, plan development, and economic evaluation for oil and gas fields and pilots. Those comprehensive simulations maximized the profit of CO2 injection by accurately forecasting oil production and minimizing the operational cost.
Awards and Certifications
• 2019- NSF SBIR Phase I Grant ($225K)
• 2018- NSF I-Corps Program, Technical Lead, San Diego Cohort, San Diego, California
• 2018- Mid-West I-Corps Node, University of Purdue, West Lafayette, Indiana
• 2008- Master Thesis Award, National Iranian Oil Company
• 2005- Ranked 10th in national Reservoir Engineering entrance exam
• Data mining and data analysis
• Data visualization (Data Studio, Tableau)
• Machine learning packages (Pandas, SciKit Learn, Numpy, Plotly, Voila, Keras)
• Computer programming (Python, R, VBA, Mathematica, MATLAB)
• AI decision support system
• Reservoir simulation
• Economic evaluation
• Reservoir characterization and reservoir management
• Production forecast and risk analysis
• Professional Software (CMG, Tempest-MORE, IHS Harmony, FieldPro, Techlog, Kappa, Surfer, Didger, Global Mapper)
Business Analytics Program, Harvard Business School (June 2021)
Ph.D. in Petroleum Engineering, Technical University of Freiberg - Freiberg, Germany (February 2012)
M.Eng. in Petroleum Engineering, University of Calgary - Calgary, Canada (September 2007)
Petroleum Engineering, Petroleum University of Technology - Tehran, Iran (September 2007)
B.Sc. in Reservoir Engineering, Petroleum University of Technology - Ahwaz, Iran (September 2005)