Characterizing Natural Hydrogen Occurrences in the Paris Basin Using OCR-Enhanced Well Database Studies

This study investigates natural hydrogen (H2) occurrences in the Paris Basin, using Optical Character Recognition (OCR) technology to analyze an extensive, yet historically underexploited, well database that contains older drilling records. With the growing demand for carbon-free energy, natural hydrogen, produced through processes like serpentinization and water radiolysis, offers a promising alternative to fossil fuels. However, its potential has been largely unexplored in conventional oil and gas wells. Utilizing the BEPH (Office of Exploration and Production of Hydrocarbons) French database, which includes well logs, mudlogs, and End Drilling Reports (EDRs) in PDF image format, we applied the Tesseract-OCR Engine to convert these documents into searchable formats for efficient data analysis. Our analysis revealed several H2-bearing wells across the French sedimentary basins. The hydrogen occurrences in the Aquitaine Basin correlate with the geological context, but those in the Paris Basin present an anomaly, as their H2 occurrences do not align with the expected geological factors. In the Paris Basin, H2 has been detected in four main formations: the Lusitanian aquifer, Dogger aquifer, Triassic aquifer, and the basement. The highest hydrogen concentration (52 vol%) was found in the Dogger formation. These wells are primarily located along the Bray fault and thrust, indicating a geological influence on H2 distribution. This research demonstrates the effectiveness of OCR in reprocessing historical drilling data for natural hydrogen exploration, highlighting the need for comprehensive exploration methodologies in this emerging field.