Shale Shaker - Cuttings Analysis using GenAI Computer Vision
This agent provides an advanced solution for analyzing drill cuttings from shale shakers using Generative AI and Computer Vision. It identifies formation types (sand vs. rock), classifies cutting shapes and sizes, and quantifies cutting volumes to enhance geological analysis accuracy and efficiency.
Collects image and video data of cuttings using AWS Panorama and Lookout for Vision, with support for on-site collection via AWS Outposts.
Automates the migration of table structures from SAP HANA to Snowflake, ensuring schema consistency and data integrity.
Synthetic Data Generation Agent
Uses foundational models like Stability AI SDXL LLM to generate synthetic training data from limited datasets.
Transfers data from SAP HANA to Snowflake, handling large volumes of data efficiently and accurately, while maintaining data relationships and integrity.
Computer Vision Model Agent
Develops and deploys state-of-the-art models to detect sand vs. rock and analyze cutting shape and size.
Migrates views from SAP HANA to Snowflake, converting SQL syntax and ensuring equivalent functionality, to maintain business logic and reporting capabilities.
Cuttings Volume Estimation Agent
Estimates the volume of cuttings using visual data to support drilling operations.
Automates the migration of table structures from SAP HANA to Snowflake, ensuring schema consistency and data integrity.
Analysis and Reporting Agent
Generates actionable insights and reports for geological teams based on classification and volume analysis.
Transfers data from SAP HANA to Snowflake, handling large volumes of data efficiently and accurately, while maintaining data relationships and integrity.
Model Improvement Agent
Continuously refines computer vision models using real and synthetic data and user feedback.
Migrates views from SAP HANA to Snowflake, converting SQL syntax and ensuring equivalent functionality, to maintain business logic and reporting capabilities.
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