TotalEnergies enhanced the quality and accessibility of its data by applying innovative data conditioning and machine learning workflows.
TotalEnergies Exploration, based in Paris, harnessed machine learning and advanced data science tools from SLB to overcome the challenges of managing decades of legacy data across its global operations. By applying innovative data conditioning and machine learning workflows, TotalEnergies enhanced the quality and accessibility of its data, unlocking significant operational value and improving decision-making across its exploration teams.
Watch Olivier Siccardi, from TotalEnergies Exploration, give an overview on how SLB’s data science tools transformed legacy data management.
TotalEnergies collaborated with SLB to deploy log conditioning workflows and machine learning interpretation for well data. These advanced tools enabled the company to efficiently transform decades of disparate and complex data formats into a high-quality, usable format for its team of 90 geoscientists. By leveraging tailored training modules from SLB, TotalEnergies optimized their data workflows, ensuring more accurate and reliable geoscience analysis.
SLB provided customized training sessions that went beyond basic platform usage, focusing on maximizing the geoscientific value extracted from the data. TotalEnergies’ geoscientists worked directly with SLB experts to tailor the platform’s functionality to their specific exploration needs, ensuring that the team could fully utilize data to its potential.
TotalEnergies overcame the historical challenge of using only 10-15% of available well data by implementing SLB data workflows, enabled by its Lumi™ data and AI platform. The integration of machine learning significantly reduced the time required to prepare data, allowing for the generation of high-quality datasets in just weeks. This improvement not only enhanced exploration decision-making but also unlocked the value of previously inaccessible data.
The collaboration between TotalEnergies’ geoscientists and SLB data scientists fostered a deeper exploration of legacy data. This joint effort enabled TotalEnergies to extract maximum value from its extensive data archives, driving better exploration outcomes and unlocking new opportunities for future data-driven strategies.
