A specialized 7B parameter model for oil and gas engineering, optimized for technical calculations, engineering analysis, and real-time optimization in petroleum operations.

OGAI Reasoner

OGAI Reasoner is an advanced engineering system for oil and gas operations, built on the DeepSeek architecture. It specializes in petroleum engineering calculations, real-time optimization, and technical analysis.

Model Details

Base Architecture: DeepSeek (Qwen2)
Parameters: 7.62B
Quantization: Q4_K_M
Size: 4.7GB
License: MIT

Key Features

Advanced petroleum engineering calculations
Real-time optimization capabilities
Comprehensive uncertainty quantification
Industry-standard compliance
Multi-domain expertise:
- Reservoir Engineering
- Well Engineering & Drilling
- Production Engineering

Capabilities

Reservoir Analysis
- PVT calculations
- Material balance
- Pressure transient analysis
- Decline curve interpretation
Well Engineering
- Trajectory optimization
- Drilling parameter optimization
- Wellbore stability analysis
- Completion design
Production Engineering
- Nodal analysis
- Artificial lift optimization
- Network optimization
- Production forecasting

Technical Specifications

Temperature: 0.7 (Balanced precision)
Top-p: 0.95 (High coherence)
Top-k: 50 (Diverse solutions)
Presence/Frequency Penalties: 0.1

Input/Output Format

Structured JSON inputs
Standardized calculation outputs
Comprehensive metadata
Industry-standard units support

Usage Examples

# Basic calculation request
{
    "calculation_type": "pvt_analysis",
    "inputs": {
        "parameters": {
            "pressure": 3000,
            "temperature": 180,
            "oil_gravity": 35
        },
        "units": "field"
    }
}

Installation

ollama pull gainenergy/ogai-reasoner:latest

Deployment Requirements

Minimum 8GB RAM
10GB storage
CUDA-compatible GPU recommended

Best Practices

Provide complete input parameters
Specify units explicitly
Include data quality metrics
Document assumptions
Validate results against standards

Support

For technical support and questions: - GitHub Issues - Documentation: docs/ - Community Forum: discuss.gainenergy.ai

License

MIT License - See LICENSE file for details

Acknowledgments

DeepSeek team for the base model architecture
SPE for industry standards and best practices
Our partners, Merlin ERD
Open-source contributors

Note: This model is optimized for engineering calculations and technical analysis. While it provides recommendations, all results should be validated by qualified engineers before implementation.