Generation, migration and accumulation of natural hydrogen and helium in the intracratonic São Francisco Basin, eastern Brazil: implications for the understanding and exploration of natural H <sub>2</sub> systems
Bibliographic record
Abstract
An integrated understanding of H 2 generation, migration, trapping and preservation is required to facilitate H 2 exploration. Hydrogen-rich gas discoveries in the São Francisco Basin in Brazil enable investigation of these processes in intracratonic settings. We used major gas, stable isotope and noble gas isotope geochemistry to develop an advanced geochemical framework that demonstrates, via multiple lines of evidence, migration of components into the basin from underlying cratonic basement. Mass balance shows that hydrogen and helium derive from outside of the fracture-controlled reservoirs from which they were sampled. Radiogenic noble gas data indicate at least two crustal sources for the accumulated gas, from different thermal environments; neon isotope data suggest that one of these is the Archean crystalline basement. The H 2 - and He-bearing gases are associated with the eastern part of the basin, above the Pirapora Aulocagen, where thick-skinned deformation associated with the Araçuaí Orogeny may provide fluid-migration pathways between the basement and the basin fill. The Precambrian crystalline basement has a high H 2 generation potential, but it was previously unknown whether basement-derived H 2 gases could survive migration and accumulation without being entirely consumed by chemical and microbial reactions. While several wells contain an abiotic contribution to the alkane gases, indicating hydrogen consumption, H 2 concentrations of up to 39% imply that, as with noble gases, it is possible for H 2 to survive migration and accumulation on a regional scale. This discovery of natural H 2 gas reservoirs supports a source–migration–trapping model, critical to define effective natural hydrogen plays, enabling economic exploration of this low-carbon resource.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".