AI Optimization (OPT)

Advanced AI

Lifecycle stages:

Introduction

MLOps journey description: AI optimization focuses on improving system efficiency, reducing costs, and optimizing workflows using machine learning. It includes hyperparameter tuning, model compression, and automated decision-making.

Use case examples: Improving operational efficiency, resource allocation, and decision-making through advanced analytics and optimization algorithms.

• Production optimization for well performance and reservoir output
• Drilling path optimization (e.g., directional drilling strategies)
• Supply chain logistics optimization (e.g., transport route and inventory planning)
• Real-time energy consumption and cost optimization for facilities
• Optimization of blending processes (e.g., crude oil mixing or gas composition control)