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AI-Driven CO₂ Storage Screening – North Sea (Gullfaks Field)
An AI-assisted subsurface screening study evaluating COâ‚‚ storage potential in the Gullfaks Field. Using petrophysical logs and machine learning, key reservoir parameters such as porosity, permeability, and net-to-gross are analyzed. This workflow enables rapid identification of viable storage intervals, accelerating early-stage CCUS decision-making.
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AI-Powered Global Supply Shock Intelligence Platform
A next-generation platform leveraging RAG and LLMs to assess global energy supply risks in real time. By integrating subsurface data across multiple basins, it enables rapid identification of alternative supply sources during disruptions. Designed to transform fragmented well data into actionable geopolitical and operational intelligence.
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AI Knowledge System for Multi-Well Analysis – Australia (NWS Basin)
A RAG-based system that converts unstructured well reports into a searchable, intelligent knowledge base. Enables real-time querying of drilling, geological, and reservoir insights across multiple wells. Demonstrates how AI can significantly reduce manual interpretation and accelerate subsurface workflows.
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AI & GenAI Subsurface Intelligence – Granite Wash, Oklahoma
An AI-driven reservoir evaluation integrating OCR, log digitization, and petrophysical interpretation. Transforms legacy scanned well logs into structured datasets for geological analysis and mapping. Provides actionable insights into stratigraphy and reservoir quality within the Granite Wash system.
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Raster Well Log Digitization using AI
Raster well log digitization using AI involves converting scanned images of well logs into digital data formats that can be used for analysis in the petroleum industry. Well logs are essential tools in oil and gas exploration and production, providing detailed records.
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Automated Well Log Splicing to Streamline Exploration and Production Operational Efficiency
In the fast-paced world of oil and gas exploration and production (E&P), the quest for efficient, accurate, and scalable well log analysis is more critical than ever. This paper provides an in-depth look at AutoSpliceTM innovative methodology.
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Prediction Of Missing Well Logs Using AI And ML
Predicting missing well logs in the oil and gas industry is crucial for reservoir characterization and decision-making processes. However incomplete or missing well log datapose significant challenges in accurately assessing subsurface formations.
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Unlocking Subsurface Value from Legacy Data Using AI & Gen AI – Granite Wash wells from OK
We would like to share how Drake AI is helping operators unlock actionable subsurface insight from legacy well logs and regulatory data using a combination of Artificial Intelligence (AI) and Generative AI (GenAI). As a recent demonstration, our team completed an AI-driven subsurface intelligence study of the Granite Wash reservoirs in the Anadarko Basin, Oklahoma, focused on wells across Beckham and Roger Mills Counties.
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