AI-Powered Digital Rock Physics Analysis

Revolutionizing rock parameter estimation with deep learning technology achieving over 95% prediction accuracy

About PETRA

Published Research
Patent EC00202462911
95%+ Accuracy

PETRA is a cutting-edge application that revolutionizes rock sample analysis through advanced machine learning. Our platform provides rapid, accurate predictions of critical rock parameters including porosity, permeability, tortuosity, and grain size - all from digital images of rock samples.

Developed by geologists and data scientists, PETRA combines domain expertise with state-of-the-art deep learning to deliver laboratory-grade results in seconds rather than days. Our models have been trained on thousands of diverse rock samples to ensure reliable performance across a wide range of geological formations.

Rapid Analysis

Get results in seconds compared to traditional lab methods that take days or weeks.

AI-Powered

Advanced deep learning models trained (281M Parameter) on thousands of rock samples for maximum accuracy.

Lab Quality

Results comparable to traditional laboratory measurements with MAPE under 5%.

Key Features & Capabilities

Percolation Analysis

Determines whether the rock sample allows fluid flow (percolating) or not (non-percolating) with 98% accuracy.

Permeability Estimation

Predicts permeability in millidarcies (md) for fluid flow analysis with MAPE under 4%.

Porosity Measurement

Calculates both absolute and effective porosity values with laboratory-grade precision.

Tortuosity Analysis

Measures the tortuosity of pore structures with unprecedented accuracy.

Grain Size Estimation

Determines average grain size automatically from sample images.

Scientific Publication

Estimating two-dimensional physical parameters of digital rocks using deep learning

Read on IOP Science

Rock Sample Analysis

Upload image (recommended size: 256×256 pixels) of your rock sample for immediate analysis. Our AI will process the image and provide detailed physical parameters within seconds.

Drag & drop your rock sample image here
or click to browse files (PNG, JPG supported)
Preview of uploaded rock sample

Processing your rock sample with our AI engine...

Percolating Sample
95%

Analysis Results

Advanced Technical Details
Upload and analyze a sample to view raw prediction data

User Guide & Applications

Usage Guide
Industry Applications

How to Use PETRA for Rock Analysis

  1. Prepare your sample image: Use a high-quality image with clear contrast between grains and pores. Avoid shadows or uneven lighting.
  2. Upload the image: Drag and drop your image file or click to browse your files. Supported formats: PNG, JPG.
  3. Start analysis: Click "Analyze Sample" to begin processing. Our AI will evaluate your sample in seconds.
  4. Review results: The system displays validation status, predicted parameters, and confidence levels.
  5. Interpret findings: Use the detailed output values for your research, reports, or decision-making.

Best Practices for Optimal Results

Image Quality

Use high-resolution images with consistent lighting and focus. Avoid compression artifacts.

Scale Reference

Include a scale reference when possible for more accurate grain size measurements.

Lighting Conditions

Use diffuse, even lighting to minimize shadows and highlight pore structures.

Industry Applications of PETRA

Petroleum Engineering

Evaluate reservoir quality, estimate hydrocarbon recovery potential, and optimize extraction strategies by analyzing core samples rapidly.

Hydrogeology

Assess aquifer properties, predict water flow characteristics, and evaluate groundwater resources in different geological formations.

Geotechnical Engineering

Determine rock properties for construction projects, tunneling, slope stability analysis, and foundation design.

Geothermal Energy

Evaluate reservoir rocks for heat exchange potential and fluid flow characteristics in geothermal systems.

Academic Research

Accelerate geological research by quickly analyzing large numbers of rock samples for comparative studies.

Mining Industry

Characterize ore samples for mineral processing optimization and tailings management.