BASIC WELL LOG INTERPRETATION IN PYTHON PROGRAMMING LANGUAGE

Python has rapidly become the programming language of petroleum geoscientists during the last decade. It is used widely in development, research and scientific activities and is included in many commercial software as an option for additional scripting purposes. Geophysical well log data interpretation is one of the most useful and important tools available to a petroleum geologist [12]. The results of log analysis and interpretation play an important role in the decision making in oil and gas activities throughout the exploration, development and production stages. The standard log interpretation workflow for petrophysical analysis of the wells includes: data loading, QC and editing (1); borehole environmental corrections (2); calculation of shale volume (3); porosity calculation (4); water saturation calculation (5); identification of lithology type (6); estimation of net and pay thickness (7). In this tutorial it is shown how to use Python programming code to carry out the standard well log interpretation steps. Third-party libraries have been used in the tutorial: Matplotlib was used in the graphical parts of the scripts; Pandas library was used as a data analysis and manipulation tool. In addition, the following specifically designed Python libraries were used for log data reading and calculations: Lasio, a Python package to read and write Log Ascii Standard (LAS) files and petrophysics, which is a library containing a petrophysical collection of formulas written as Python functions.