Kwantis is embarking on a transformative digitalization project in the drilling domain for a leading oil and gas company. The primary objective is to achieve a complete automation in interpreting Formation Integrity Tests (FIT) and Leak-Off Tests (LOT) through the implementation of machine learning algorithms.
This strategic move is in response to longstanding challenges in accurately defining formation characteristics and then, accordingly the right drilling parameters. Over the years, these challenges have displayed in issues such as lost circulation, well control problems, and premature casing setting depths.
By integrating advanced machine learning algorithms, it will be possible to streamline and enhance the interpretation process. This innovation promises not only precise interpretation of FIT and LOT tests but also a structured workflow to data gathering and collection ready to use for future analysis and studies.