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Energy

ADNOC

AI drilling optimization increases oil recovery by 23% while reducing drilling costs $480M annually

23%
Oil Recovery Rate
$480M
Drilling Costs
34%
Equipment Uptime

The Challenge

Abu Dhabi National Oil Company (ADNOC), one of the world's largest oil producers with output of 4 million barrels per day, faced declining well productivity as easily accessible reservoirs depleted. Traditional drilling techniques left 60-70% of oil in the ground, and exploration costs exceeded $12 billion annually. The company needed AI to optimize drilling trajectories, enhance recovery rates, and predict equipment failures before costly downtime.

The Approach

ADNOC deployed AI-powered drilling optimization analyzing real-time sensor data from drill bits, seismic imaging, reservoir models, and historical well performance. Machine learning models recommended optimal drilling paths to reach untapped pockets within existing fields. Predictive maintenance AI forecast equipment failures 24-72 hours in advance, preventing unplanned shutdowns. Computer vision analyzed core samples to assess rock properties faster than human geologists. The AI platform integrated across ADNOC's 200+ oil and gas fields.

Results

23%
Oil Recovery Rate
Increase in percentage of oil extracted from reservoirs
$480M
Drilling Costs
Annual savings from optimized drilling and maintenance
34%
Equipment Uptime
Improvement through AI predictive maintenance
AI transforms how we extract energy resources. We're getting more oil from existing fields while dramatically reducing costs and environmental impact.
Chief Technology Officer, ADNOC

This case study is based on publicly available information about ADNOC.

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