Enhanced Learning Experience for New Petrophysicists Using Open-Source Carbonate Data and Python Programming

This paper delves into leveraging open-source carbonate data and Python programming to enhance the learning experience for new petrophysicists. As petrophysical evaluation has advanced significantly with the advent of computer technologies, the integration of computer programming has emerged as a powerful tool for skill development. The study examines the use of quick_pp, an open-source Python library, to apply petrophysical workflows on open-source carbonate data. The aim is to facilitate the capability development of newcomers to petrophysics through hands-on programming and a comprehensive understanding of backend calculations. The paper discusses new insights, limitations, and recommendations for future improvements to optimize the learning experience. Overall, quick_pp showcases its potential in enabling new entrants to conduct thorough and comprehensible petrophysical evaluations.