Induced-Seismicity Risk Framework for Geothermal and Fluid-Injection Projects
Explore how fluid pressure, fault geometry and uncertain assumptions change an induced-seismicity assessment.
Software compatibility
Word, PDF and editable slides explain the study. Optional Python 3.12 analysis uses only the standard library. Matplotlib is needed to regenerate figures. Docker is optional. No web framework, API key or field equipment is required.
Project definition
Problem statement
Fluid injection can change effective stress on a fault. The interpretation depends on fault orientation, stress, friction and pressure, not only on a single observed magnitude.
Stopping an operation also does not immediately remove every subsurface process. A defensible assessment must distinguish conditional mechanics, event probability, exposure and the limits of available evidence.
Project objectives
- Review induced-seismicity literature while recording exactly which source material was inspected.
- Resolve published stress estimates onto attributed fault-plane geometries.
- Compare friction-margin signs across an explicit pressure and friction grid.
- Distinguish exact finite-count magnitude quantiles from large-count approximations.
- Compare matched post-stop event-rate tails over finite time horizons.
- Explore delayed pressure pulses and conditional exposure calculations without claiming a field forecast.
Project structure
Project components
Literature review
Eleven annotated sources connect fault mechanics, monitoring, probability, operational history and risk-assessment evidence.
Fault mechanics
Three-dimensional traction calculations use six stress estimates and eight fault-plane estimates with explicit coordinate conventions.
Sensitivity analysis
A 432-row grid examines how pressure and friction assumptions affect the sign of a conditional margin.
Event probabilities
Exact finite-count calculations and matched exponential and Omori tails retain their different assumptions.
Pressure and exposure
A one-dimensional pressure pulse and a separate conditional-loss illustration explain limits that a single score can hide.
Methodology
Project workflow
- 01Read the evidence
Separate published estimates, reviewed equations, hypothetical cases and uninspected source material.
- 02Check conventions
Follow the stress sign, orientation and effective-compression assumptions before interpreting margins.
- 03Reproduce the tables
Run the optional offline checks without changing the supplied outputs.
- 04Compare assumptions
Inspect friction, pressure, event count and finite-horizon tail sensitivity.
- 05Discuss limitations
Explain why conditional calculations do not establish a safe operating threshold or site forecast.
Demonstration scenario
Across the declared pressure and friction rectangle, 18 of 48 stress-plane combinations retain a positive margin, four retain a negative margin and 26 change sign. This illustrates assumption sensitivity, not the probability that a fault will slip.
Engineering
Tools and method
- Tools
- The project uses Python 3.12, Matplotlib for subject analysis, simulation, and results.
- Domain study
- The documentation develops geological evidence, mechanics, probability, methodology, results and further work.
- Optional calculations
- Standard-library Python regenerates all six CSV outputs without an online service.
- Independent checks
- Analytical identities, principal directions, numerical integration, limiting cases and invalid inputs test the model.
- Editable material
- Word documents, native presentation charts and SVG figures support supervised extension. Recheck contents after repagination.
Testing
Evaluation
Evaluation measures
- Published input transcription and source attribution
- Traction, stress invariants and coordinate conventions
- Margin-sign changes across pressure and friction assumptions
- Finite-count quantiles and approximation error
- Finite-horizon tail matching and delayed pressure response
- Numerical consistency across tables, figures, documentation and slides
Project boundaries
- Published stress and geometry estimates retain their attribution; no new field measurements are claimed.
- The geometry-based exercise is retrospective, not a forecast issued before the Pohang event.
- Pressure, friction, tail and exposure scenarios are hypothetical and are not fitted site predictions.
- The pressure model is a one-dimensional prescribed-boundary illustration, not a radial well-injection model.
- No universal safe threshold, operational controller, annual risk estimate or safety certification is provided.
- Native Microsoft Word and PowerPoint application rendering has not been tested.
Included
- 0175-page project documentation in PDF and editable Word formats
- 02Six-page student guide in PDF and editable Word formats
- 0316-slide editable presentation with five native charts and five native tables
- 0411 annotated references and a source matrix with access limitations
- 0511 report tables, six original figures and editable mathematical equations
- 06Six published stress estimates and eight attributed fault-plane estimates
- 07Six reproducible analysis tables containing 963 calculation rows
- 08Complete Python source, 189 automated tests and offline reproduction
Project record
No information is collected on this page.
- Permanent project ID
- GP-GE-0AC15WE
- Catalogued
- 21 Aug 2026
- Completed
- 06 Sept 2026
- Verified
- 06 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.