Oil and Gas
Oil and Gas | Unconventional Resources
Introduction to Statistical Modeling and Big Data Analytics
Format and Duration:
1 days
This training course will provide an introduction to statistical modeling and big data analytics for petroleum engineering and geoscience applications. Topics to be covered include: (a) easy-to-understand descriptions of the commonly-used techniques, and (b) case studies demonstrating the applicability, limitations and value-added proposition for these methods. This course will inform engineers and geologists about techniques for data-driven analysis that can convert data into actionable information for reducing cost, improving efficiency and/or increasing productivity in oil and gas operations.
Schedule
Duration and Training Method
A one-day classroom course consisting of lectures with worked examples.
Course Overview
Learning Outcomes
Participants will learn to:
- Apply foundational concepts in probability and statistics for basic data analysis
- Interpret linear regression for building simple input-output models
- Examine multivariate data reduction and clustering for finding sub-groups of data that have similar attributes
- Converse with confidence about big data, data analytics and machine learning terminology and fundamental concepts
- Differentiate machine learning techniques for regression and classification for developing data-driven input-output models
- Critique uncertainty quantification studies for probabilistic performance forecasting
Course Content
- Big data technologies, basic data analytics and machine learning terminology/concepts
- Exploratory data analysis, probability distributions, confidence limits
- Basic linear regression
- Data reduction, cluster analysis and data visualization
- Machine learning basics, techniques for regression and classification problems
- Machine learning case studies
- Uncertainty quantification
- Wrap-up
Who Should Attend and Prerequisites
This course is for designed for petroleum engineers, geoscientists, and managers interested in learning about the basics of statistical modeling and data analytics.
Instructors
Srikanta Mishra
Background
Dr. Srikanta Mishra is currently a Research Professor at Texas A&M University, where he researches Energy Transition and Subsurface Data Analytics. He also serves as a Technical Advisor to the US-DOE NETL’s SMART Initiative (Science Informed Machine Learning to Accelerate Real-time Decisions for Subsurface Applications) and instructs courses on CO2 Geological Storage and Machine Learning.
Dr. Mishra retired in 2023 as the Technical Director for Geo-energy Modeling & Analytics at Battelle Memorial Institute. At Battelle, he led a technology portfolio related to computational modeling and data analytics for geological carbon storage, improved oil recovery projects, and shale gas/oil development. His recent work focused on full-physics and reduced-order modeling, and pressure-based monitoring, of CO2 geologic sequestration projects. He served as PI or co-PI on several CO2 geological storage and EOR projects funded by the US Department of Energy.
Dr. Mishra has presented lectures and conducted short courses on CO2 geologic sequestration in many US universities and in academic and research organizations worldwide. He is an editor of the book “CO2 Injection in the Network of Carbonate Fractures” and the author of ~200 technical publications.
Dr. Mishra is a member of the Technical Advisory Board of the SMART initiative organized by the US Department of Energy’s Carbon Storage Program. He was an SPE Distinguished Lecturer for 2018-19 on Big Data Analytics. He has also served as an Adjunct Professor of Petroleum and Geosystems Engineering at The University of Texas at Austin.
Affiliations and Accreditation
PhD Stanford University - Petroleum Engineering
MS Stanford University - Petroleum Engineering
BTech Indian School of Mines - Petroleum Engineering
Courses Taught
N479: Applied Statistical Modeling and Big Data Analytics
N480: Introduction to Statistical Modeling and Big Data Analytics
N535: Carbon Capture Sequestration (CSS)
N567: Carbon Capture, Utilization and Storage
Accreditation and Certification
CEU: 0.7 Continuing Education Units
PDH: 7 Professional Development Hours
Certificate: Certificate Issued Upon Completion
RPS is accredited by the International Association for Continuing Education and Training (IACET) and is authorized to issue the IACET CEU. We comply with the ANSI/IACET Standard, which is recognised internationally as a standard of excellence in instructional practices.
We issue a Certificate of Attendance which verifies the number of training hours attended. Our courses are generally accepted by most professional licensing boards/associations towards continuing education credits. Please check with your licensing board to determine if the courses and certificate of attendance meet their specific criteria.