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Geothermal Reservoir Characterization Assistant

Build 3D geothermal reservoir models from logs, cores, and thermal data

3.8(15 reviews)
10+ downloads
Updated Sep 2026
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What You Can Do

You systematically interpret well log suites to identify lithofacies transitions, convert core data into predictive permeability and porosity relationships, and integrate thermal properties into flow models. This allows you to build defensible volumetric estimates, identify compartmentalization risks and fracture zones, and anticipate reservoir response to production and injection scenarios—enabling confident well placement optimization and production forecasting.

Features

Well log interpretation

identify lithofacies, correlation patterns, and petrophysical boundaries across multiple wells

Core-to-log relationships

convert core plug analysis into permeability and porosity predictive models applicable across the reservoir

Thermal property integration

incorporate conductivity, heat capacity, and thermal diffusivity into flow simulation workflows

Fracture zone mapping

recognize and characterize natural and induced fracture systems affecting reservoir compartmentalization and flow paths

Volumetric estimation

calculate net pay, gross rock volume, and flow capacity using integrated data from multiple sources

Production forecasting

model reservoir response to planned production and injection rates using characterized properties

Well placement optimization

recommend drilling locations and spacing based on structural, thermal, and flow capacity mapping

Risk assessment

identify producibility constraints, thermal drawdown risks, and injection-induced seismicity potential

Example Output

Example 1: Lithofacies Interpretation

  • Well A (0–500 m): High-porosity sandstone with moderate permeability (log-derived 200–400 mD), core-confirmed structure; recommended for production well
  • Well B (100–600 m): Interbedded silts and clays, low permeability (10–50 mD); acceptable for injection to minimize near-field thermal losses

Example 2: Permeability Prediction Core plug data (20 samples): k = 10^(0.048×φ + 1.2) [mD, φ in %]. R² = 0.87. Applied to porosity logs: predicted average reservoir k = 280 mD, range 50–650 mD across 8-well appraisal area.

Example 3: Well Placement Recommendation Proposed production well location: structurally high, 150 m from injection well, in highest permeability facies (k avg 420 mD). Thermal breakthrough modeling predicts 25+ year production life before 50°C temperature decline at current rates.

What's Included

  • SKILL.md instruction file: structured methodology for data integration and interpretation workflow
  • Well log interpretation checklist: lithofacies identification, petrophysical correlation, and quality control steps
  • Core-to-log transformation templates: spreadsheet frameworks for porosity-permeability relationships and statistical validation
  • Thermal property integration worksheet: matrix for organizing conductivity, heat capacity, and diffusivity data by lithofacies
  • Fracture characterization worksheet: structured framework for identifying and mapping natural and induced fracture zones
  • Volumetric calculation template: net pay mapping, flow capacity summation, and uncertainty quantification
  • Well placement recommendation template: structured output format for drilling location optimization and risk summary

Who It's For

  • Geothermal reservoir engineers — designing field development plans and well drilling campaigns
  • Petrophysicists — interpreting wireline logs and core analysis for flow property prediction
  • Geoscientists — integrating seismic, thermal, and well data into 3D geological models
  • Drilling engineers — optimizing well placement, spacing, and completion strategies based on reservoir characterization
  • Project managers — assessing producibility risk and capital allocation for geothermal prospects

Best For

  • Initial appraisal of newly drilled geothermal wells with complete log suites
  • Converting core plug data into field-scale permeability and porosity models
  • Integrating thermal property measurements into reservoir simulation workflows
  • Identifying and mapping fracture zones affecting compartmentalization or injection performance
  • Optimizing production and injection well spacing and location in conventional and EGS reservoirs
  • Forecasting long-term production decline and thermal breakthrough timing

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