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GP-GE-1R4Q79YGeologyReady

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.

Natural-Hydrogen Exploration Play Assessment and Resource Uncertainty project visual
GP-GE-1R4Q79Y · Geology
  • Python 3.12
  • NumPy
  • pandas
  • Matplotlib

Software compatibility

Python 3.12 on macOS, Linux, and Windows

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

01

Play register

Compares serpentinization, radiolysis, deep-crustal, rift, iron-rich, mafic, cratonic, basin and multi-mechanism play concepts.

02

Hydrogen-system model

Separates source potential, generation rate, migration, reservoir quality, seal integrity and preservation.

03

Evidence-quality model

Retains sampling reliability, contamination control, geophysical non-uniqueness, resource scalability and evidence maturity.

04

Workflow FMEA

Ranks stage-criterion combinations from desk study and field sampling through drilling, flow testing and resource classification.

05

Verification pipeline

Regenerates the study, tests the model, validates documents and reproduces the analysis in Docker.

Methodology

Project workflow

  1. 01
    Define the play

    State scale, source hypothesis, structural setting, reservoir, seal, preservation and decision purpose.

  2. 02
    Control the sampling

    Use blanks, duplicates, leak checks, depth profiles, repeat surveys and documented gas-analysis methods.

  3. 03
    Integrate evidence

    Combine geology, geochemistry, geophysics and wells while retaining alternative explanations.

  4. 04
    Test the system

    Progress from occurrence evidence to pressure, reservoir properties, composition and sustained flow.

  5. 05
    Review 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

  1. 01Complete Python source and declared study configuration
  2. 02800 play, exploration-risk, geological-context and evidence cases
  3. 03Ten exploration plays and five hard exploration-risk gates
  4. 04Fifteen validation criteria and a 180-cell workflow FMEA
  5. 05Twelve generated figures and one attributed public-domain literature figure
  6. 0687-page project report in PDF and editable Word formats
  7. 0716-page setup and usage guide in PDF and editable Word formats
  8. 08Fifty-seven annotated references with evidence boundaries and source matrix
  9. 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

  1. 01
    Payment is confirmed

    The project is marked unavailable and cannot be purchased again.

  2. 02
    Repository access is granted

    The buyer's submitted GitHub account receives access to the private repository.

  3. 03
    The purchase record is delivered

    The certification sheet is prepared from the reviewed buyer details and sent privately by email.