File size: 5,636 Bytes
f9995fb 2615f9a f9995fb 2615f9a f9995fb 2615f9a f9995fb 2615f9a f9995fb b5bbd4a f9995fb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 |
---
license: apache-2.0
datasets:
- GainEnergy/quantum-oil-gas-dataset
base_model:
- GainEnergy/OGAI-R1
library_name: transformers
tags:
- oil-gas
- quantum-computing
- hybrid-ai
- reservoir-engineering
- well-optimization
- retrieval-augmented-generation
- fine-tuned
- quantum-llm
- upstrima
model-index:
- name: OGAI-Quantum
results:
- task:
type: text-generation
name: Quantum AI for Oil & Gas Engineering
dataset:
name: GainEnergy Quantum Oil & Gas Dataset
type: custom
metrics:
- name: Quantum Reservoir Simulation Speedup
type: benchmark
value: Coming Soon
- name: Hybrid AI Computational Efficiency
type: benchmark
value: Coming Soon
- name: Quantum-RAG Retrieval Score
type: accuracy
value: Coming Soon
---
# **OGAI-Quantum: The Future of Oil & Gas AI (Coming Soon)**
[](LICENSE)
🚀 **OGAI-Quantum** is a **next-generation hybrid AI model** that fuses **quantum computing principles with classical deep learning** to deliver breakthrough performance in **reservoir modeling, drilling optimization, seismic analysis, and energy AI workflows**.
🌍 **COMING SOON**: Currently in **final development and quantum validation testing**.
---
## **🫠 Capabilities**
- **⚡ Quantum-Accelerated Simulations** – Faster reservoir modeling and seismic analysis.
- **🧠 Hybrid AI-Quantum Workflows** – Integrates quantum variational circuits with deep learning.
- **📚 Quantum-RAG for Technical Knowledge Retrieval** – Advanced AI-driven document retrieval for energy data.
### **📌 Core Quantum Use Cases**
| **Use Case** | **Quantum Advantage** |
|--------------------------------|-----------------------|
| **Reservoir Simulation** | Multi-state quantum superposition for faster modeling |
| **Seismic Data Processing** | Quantum-based feature recognition in seismic datasets |
| **Well Placement Optimization** | Quantum annealing for high-dimensional search spaces |
| **Production Optimization** | Quantum variational circuits for real-time gas lift & production tuning |
---
## 🏢 **Quantum-Classical Hybrid Framework**
OGAI-Quantum is powered by **Upstrima's Quantum AI Engine**, combining **quantum-enhanced decision-making** with traditional deep learning.
```yaml
System Architecture:
├── Quantum Simulation Layer
│ ├── Quantum Gate Operations
│ ├── Qiskit & PennyLane Integration
│ ├── Variational Quantum Circuits (VQC)
│ ├── Quantum Annealing for Optimization
│ ├── Quantum Reservoir Simulation Models
│ ├── Seismic Data Quantum Processing
├── Classical AI Model
│ ├── Fine-Tuned TinyR1-32B Model
│ ├── Hybrid Engineering Knowledge Base
│ ├── Neural Retrieval-Augmented Generation (RAG)
│ ├── Classical Physics-Based Simulations
│ ├── AI-Powered Technical Document Understanding
│ ├── Adaptive Learning & Model Refinement
└── Hybrid Orchestration Layer
├── Quantum-Classical Task Partitioning
├── Quantum State Virtualization Engine
├── Quantum Pipeline API for High-Performance Computing
├── Real-Time Quantum State Synchronization
├── Cloud & Edge Deployment Support
├── API Integration with Upstrima AI Suite
```
---
## 📦 **Model Variants**
| **Model Name** | **Base Model** | **Quantum Features** | **Context Window** | **Use Case** |
|-------------------|----------------|----------------|----------------|-------------|
| **OGAI-Quantum** | OGAI-R1 + Quantum | Yes | TDB tokens | **Hybrid AI for Energy & Engineering** |
| **OGAI-R1** | TinyR1-32B | No | 128k tokens | **Reservoir AI & RAG** |
| **OGMOE** | Mixtral-8x7B + MoE | No | 32K tokens | **Drilling Optimization & Decision Support** |
---
## 🚀 **Deployment & Integration**
OGAI-Quantum will be available on:
- **Hugging Face Inference API**
- **AWS Braket for Hybrid Quantum-Classical Workflows**
- **On-Premise Quantum-Classical HPC Deployment**
### **🔧 Technical Stack**
- **Quantum Libraries:** `Qiskit`, `PennyLane`, `Cirq`
- **AI Frameworks:** `Transformers`, `AutoGPTQ`, `PEFT`
- **Data Pipelines:** `FAISS`, `Pinecone`, `LangChain`
---
## ⚠️ **Limitations**
🚧 **Quantum Hardware Dependency** – While designed for hybrid execution, full quantum acceleration requires cloud-based quantum backends.
🚧 **Experimental Hybrid AI** – Model performance is still undergoing validation for real-world **engineering applications**.
🚧 **Not General-Purpose** – Optimized specifically for **oil & gas industry workflows**.
---
## 🔗 **Resources**
- **[Quantum Applications in Oil & Gas](https://huggingface.co/docs/quantum-oil-gas-applications)** – Technical whitepaper on **hybrid AI for energy**.
- **[GainEnergy AI Platform](https://gain.energy)** – Explore AI-powered **quantum-enhanced energy solutions**.
- **[Upstrima Quantum Computing Extension](https://huggingface.co/docs/upstrima-quantum-extension)** – WebAssembly-powered quantum simulation.
---
## 📚 **Citing OGAI-Quantum**
```bibtex
@article{ogai-quantum-2025,
title={OGAI-Quantum: Hybrid Quantum-Classical AI for Oil & Gas Engineering},
author={GainEnergy AI Team},
year={2025},
publisher={Hugging Face Models}
}
``` |