Natural-Hydrogen Exploration Play Assessment and Resource Uncertainty
A completed geology study comparing natural-hydrogen exploration plays while keeping source, migration, preservation, sampling, sustained flow, resource maturity and uncertainty visible.

Software compatibility
The released results use the frozen 3 September 2026 evidence catalogue, pinned Python packages, 20,000 uncertainty draws per play, and random seed 20260903. Changed evidence positions or regional data require a fresh validation run.
Project definition
Problem statement
Natural hydrogen can be generated by several geological processes, but an occurrence or seep does not by itself establish a preserved, rechargeable or producible accumulation.
The geology problem is to connect source, generation, migration, reservoir, seal, preservation, sampling reliability and sustained-flow evidence without turning early observations into unsupported discovery or resource claims.
Project objectives
- Compare ten natural-hydrogen exploration-play concepts through twelve evidence dimensions.
- Apply hard source, migration, preservation, sampling and sustained-flow gates before ranking.
- Compare balanced, geological, resource and field-programme decision scenarios.
- Map fifteen validation criteria across twelve exploration stages.
- Quantify evidence-position uncertainty with 20,000 fixed-seed draws per play.
- Retain complete results, figures, tests, references and editable documentation.
Project structure
Project components
Play register
Compares serpentinization, radiolysis, deep-crustal, rift, iron-rich, mafic, cratonic, basin and multi-mechanism play concepts.
Hydrogen-system model
Separates source potential, generation rate, migration, reservoir quality, seal integrity and preservation.
Evidence-quality model
Retains sampling reliability, contamination control, geophysical non-uniqueness, resource scalability and evidence maturity.
Workflow FMEA
Ranks stage-criterion combinations from desk study and field sampling through drilling, flow testing and resource classification.
Verification pipeline
Regenerates the study, tests the model, validates documents and reproduces the analysis in Docker.
Methodology
Project workflow
- 01Define the play
State scale, source hypothesis, structural setting, reservoir, seal, preservation and decision purpose.
- 02Control the sampling
Use blanks, duplicates, leak checks, depth profiles, repeat surveys and documented gas-analysis methods.
- 03Integrate evidence
Combine geology, geochemistry, geophysics and wells while retaining alternative explanations.
- 04Test the system
Progress from occurrence evidence to pressure, reservoir properties, composition and sustained flow.
- 05Review uncertainty
Inspect gates, scenario reversals, FMEA priorities, intervals and sensitivity before advancing.
Demonstration scenario
The retained multi-mechanism play leads the balanced screen under the declared evidence positions. That result is a research-priority signal only. A play must still pass source, migration, preservation, sampling and sustained-flow gates, and no score is treated as a discovery probability or resource estimate.
Engineering
Tools and method
- Tools
- The project uses Python 3.12, NumPy, pandas, Matplotlib for subject analysis, simulation, and results.
- Declared inputs
- Python data structures retain every normalized play position, context factor and decision boundary.
- Deterministic analysis
- NumPy and pandas generate all 800 play, risk, context and evidence cases.
- Risk analysis
- Validation criteria, assurance crosswalk and FMEA expose geological, sampling, drilling and resource risks.
- Uncertainty
- Fixed-seed Monte Carlo and one-factor sensitivity test stability of the declared evidence positions.
- Evidence
- CSV, JSON, PNG, PDF and Word files retain the complete analysis, source catalogue and report.
- Release verification
- Tests, linting, dependency checks, vulnerability audit, document QA, repository validation and Docker verify the handover.
Testing
Evaluation
Evaluation measures
- Screening score and hard-gate result by play and exploration risk
- Source, migration, reservoir, seal and preservation positions
- Sampling reliability, geophysical detectability and sustained-flow boundary
- Severity-weighted validation gaps and workflow FMEA priorities
- Assurance crosswalk and decision-scenario reversals
- Monte Carlo intervals and evidence-position sensitivity
Project boundaries
- All numerical inputs are literature-informed evidence positions rather than field measurements.
- A hydrogen occurrence, soil-gas anomaly or seep does not establish a producible accumulation.
- The study does not estimate in-place, recoverable or commercial resources and does not select a drilling target.
- Geophysical anomalies are non-unique and gas measurements require strict contamination controls.
- A real programme requires qualified geology, geochemistry, geophysics, drilling, reservoir, safety, environmental and regulatory review.
Included
- 01Complete Python source and declared study configuration
- 02800 play, exploration-risk, geological-context and evidence cases
- 03Ten exploration plays and five hard exploration-risk gates
- 04Fifteen validation criteria and a 180-cell workflow FMEA
- 05Twelve generated figures and one attributed public-domain literature figure
- 0687-page project report in PDF and editable Word formats
- 0716-page setup and usage guide in PDF and editable Word formats
- 08Fifty-seven annotated references with evidence boundaries and source matrix
- 09Ten automated tests, repository validation and Docker reproduction
Project record
No information is collected on this page.
- Permanent project ID
- GP-GE-1R4Q79Y
- Catalogued
- 21 Aug 2026
- Completed
- 03 Sept 2026
- Verified
- 03 Sept 2026
- Demonstration
- Included in repository
Handover
After purchase
- 01Payment is confirmed
The project is marked unavailable and cannot be purchased again.
- 02Repository access is granted
The buyer's submitted GitHub account receives access to the private repository.
- 03The purchase record is delivered
The certification sheet is prepared from the reviewed buyer details and sent privately by email.