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This study investigates natural hydrogen (H2) occurrences in the Paris Basin, using Optical Character Recognition (OCR) technology to analyze an extensive, yet underexploited, database that contains historic drilling records. The potential of natural hydrogen has been largely unexplored in conventional oil and gas wells. Utilizing the in‐house CVAGeoDB database based on public well data, 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 French sedimentary basins. The hydrogen occurrences in the Aquitaine Basin may be explained by the geological context and in particular the presence of a mantle body at shallow depth. On the contrary, the detection of H2 in the Paris Basin cannot be explained in a straightforward manner as the presence of ultramafic or U‐rich rocks is poorly documented so far. In the Paris Basin, H2 has been detected in four main formations: the Lusitanian, the Dogger, and Triassic aquifers as well as in the basement. The highest hydrogen concentration (52 vol%) was measured in the Dogger aquifer. These wells are primarily located along the Bray Fault, indicating at least a structural influence on H2 distribution. Finaly, the presence of serpentinzed dunite from the Lizard complex associated with the bedrock may have played the role as a source for H2. This research demonstrates the effectiveness of OCR in reassessing historical drilling data for natural hydrogen exploration, highlighting the need for comprehensive exploration methodologies in this emerging field. Plain Language Summary: This study explores the presence of natural hydrogen (H2) in the Paris Basin, employing Optical Character Recognition (OCR) technology to sift through an extensive database of old drilling records that have not been fully utilized in the past. As the world increasingly seeks carbon‐neutral energy sources, natural hydrogen produced through interactions between water and rocks emerges as a promising alternative to fossil fuels. Our research focuses on the CVAGeoDB database, which contains detailed information on drilling activities but in a non‐searchable PDF image format. OCR is a tool that turns images containing text, such as scanned documents, into text files that one can easily search and analyze. Our findings indicate the presence of H2 in several wells across French sedimentary basins. The Paris Basin, exhibits unexpected H2 occurrences not directly linked to anticipated geological factors classically used in H2 exploration. In the Paris Basin, the highest hydrogen concentration (52 vol%) was discovered in the Dogger aquifer. These wells are predominantly situated along the Bray Fault, suggesting a structural control on the distribution of hydrogen. This research underscores the utility of OCR in re‐evaluating historical drilling data for natural hydrogen exploration. Key Points: Natural hydrogen exploration in former oil and gas provinceUse of the Optical Character Recognition algorithm to optimize processing of a large drilling report databaseIndices for a potential H2 system (source, migration, trap) in the Paris Basin [ABSTRACT FROM AUTHOR] |
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