Introducing Python Coding to Petroleum Engineering Undergraduates: Excerpts from a Teaching Experience
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The post-Covid world is witnessing a rise in automation and remote work models.
Oilfield operations are becoming increasingly innovation-driven with advances such
as digitalization technologies, smart fields and intelligent wells. Proliferation of data is
extending career frontiers in data analytics, machine learning and artificial
intelligence. Human competence in computer programming is a key enabler of these
trends. As a contribution to the Nigerian oil/gas human resources development, the
petroleum engineering program at Covenant University recently developed and is
implementing a course module on Python programing with oil/gas applications. This paper documents the philosophy, pedagogy, and prospects of this initiative and
provides a guide for its implementation across the Nigerian educational space.
The module opens with a seminar on the emerging oil/gas opportunities in data
science – to stimulate students’ interest. Thereafter, a gentle introduction to
computer programming is taught. At its core, the module teaches basics of Python
programming language – input/output, objects (values, variables, keywords),
conditional and repetitive structures, functions, lists, tuples and dictionaries. The
module is enriched with applications in reservoir volumetrics, material balance
equation, PVT properties, reservoir discretization and simulation. Hands-on
experience is enhanced with class demos and take-home programming assignments
featuring simple algorithms. Also, the course features a training on the use of
distributed version control (GitHub) for collaboration between students and
instructors. All course materials are available on an open-access GitHub repository,
with hyperlinks embedded in lecture notes. Ultimately, the course assesses students’
skills with exams set in the context of quasi-real-life projects. The future prospects
targeted in this initiative includes a follow-up module on petroleum data analytics and
machine learning, incorporation of Python coding into other modules, and a shortcourse
for industry professionals.
Keywords
TP Chemical technology