case Study | Oil & Gas
Intelligent Corrosion Detection for Oil & Gas.
A purpose-built platform combining computer vision, sensor fusion, and predictive analytics to detect corrosion earlier and forecast where failures will occur next.
90%
less inspection image review time
70%
less manual inspection effort
95%+
detection accuracy on validated datasets
Months
earlier defect detection than scheduled cycles
The single largest driver of asset failure.
From offshore platforms and subsea pipelines to refineries, storage tanks, and downstream processing units, the slow degradation of metal assets threatens safety, uptime, and profitability every single day. Industry studies estimate that corrosion costs the global oil and gas sector well over $1 billion each year in inspection, repair, deferred production, and environmental remediation.
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Traditional corrosion management is reactive and manual. Inspectors physically survey assets on fixed schedules, capture thousands of images and ultrasonic readings, and interpret them by hand. The process is slow, expensive, dangerous, and inconsistent. By the time a defect is confirmed, the damage is often already advanced.
A single facility can contain tens of thousands of inspection points. Rope-access surveys, confined-space entries, and shutdown-dependent inspections cover only a fraction of assets at a time.
SCALE
Because inspections are periodic, corrosion progresses undetected between cycles. Pinhole leaks, coating breakdown, and localized pitting escalate into wall-thickness loss and unplanned shutdowns.
LATE DETECTION
Two inspectors reviewing the same asset can reach different conclusions. Fatigue, subjectivity, and sheer volume lead to missed defects and false alarms alike.
INCONSISTENCY
Drone footage, ultrasonic readings, thermal scans, and historical reports rarely come together in one place, making it nearly impossible to see trends or prioritize risk across an asset base.
DATA SILOS
Undetected corrosion is a leading cause of loss-of-containment events, with severe consequences for worker safety, the environment, and the license to operate.
SAFETY EXPOSURE
01 The solution
From reactive cost center to proactive advantage.
An end-to-end platform that ingests inspection data from multiple sources, detects and classifies corrosion automatically, and predicts future degradation, all through a single integrity dashboard.
01
Multi-source data ingestion.
High-resolution imagery from drones, crawlers, and ROVs (including subsea); ultrasonic and eddy-current thickness measurements; infrared and thermal imaging; historical inspection records and asset registers; fixed IoT corrosion and cathodic-protection sensors, fused into one continuously updated picture of each asset.
02
AI detection & classification.
A deep-learning vision engine trained on a domain-specific corrosion library detects defects, classifies type and severity (uniform, pitting, crevice, galvanic, erosion-corrosion, stress corrosion cracking), quantifies affected area and wall-thickness loss, and localizes each finding on the asset's digital model. Days of manual review complete in minutes.
03
Predictive analytics & remaining life.
Using historical trends, environmental conditions, material properties, and operating parameters, the platform models corrosion growth rates and estimates remaining useful life. Operators see not just where corrosion is today, but where it will become critical, and when.
04
Risk-based prioritization.
Every finding is ranked by a composite risk score weighing severity, consequence of failure, asset criticality, and location. Integrity teams know which assets demand attention first: true Risk-Based Inspection rather than blanket calendar schedules.
05
Unified integrity dashboard.
Facility-wide corrosion heat maps, drill-down asset views, trend charts, automated inspection reports, and alerts, integrated with existing CMMS, EAM, and inspection-management systems (e.g., SAP, Maximo) so findings flow directly into maintenance workflows.
How it works
01
Capture. Drones, crawlers, ROVs, and fixed sensors collect imagery and measurements, on schedule or on demand.
02
Ingest. Data is securely uploaded, on-premise or in the cloud, and mapped to the digital asset register.
03
Analyze. The AI engine detects, classifies, and quantifies corrosion, then models future degradation.
04
Prioritize. Findings are scored and ranked by risk and remaining life.
05
Act. Integrity teams review results, generate reports, and push work orders into maintenance systems.
06
Learn. Every inspection cycle feeds back into the models, continuously improving accuracy.
02 Key benefits
Key benefits
Automated, consistent analysis surfaces defects long before they become failures, reducing loss-of-containment risk and unplanned downtime.
Cut inspection costs.
Automating image and data review reduces manual inspection effort by up to 70%, freeing skilled engineers for higher-value work and reducing costly rope-access and shutdown time.
Improve safety.
Fewer manual confined-space and at-height inspections mean less human exposure to hazardous environments.
Extend asset life.
Predictive insights enable timely, targeted intervention that maximizes the safe operating life of expensive infrastructure.
Make smarter decisions.
A single source of truth for asset integrity supports Risk-Based Inspection, better capital planning, and defensible regulatory compliance.
Scale effortlessly.
From a single platform to an entire portfolio of facilities, CorroSense AI applies the same rigor to every inspection point.
Agentic AI, applied to a well-defined, guideline-heavy process, does three things at once that legacy automation could not: it collapses cycle time, it enforces consistency, and it makes every decision defensible.
The manual era of underwriting was defined by how much a skilled human could hold in their head. The intelligent era is defined by how well humans and agents work together, and how much of that judgment can finally be made consistent, traceable, and fast.
02 Use case in action
Scenario
A mid-stream operator manages 2,000 km of pipeline and multiple pumping stations across a remote region. Manual inspection cycles took six months to complete a single pass, leaving long windows where developing corrosion went undetected.
Our Solution
Drone and crawler surveys fed directly into the platform. AI analysis flagged early-stage external corrosion under insulation at three stations, findings that prior manual reviews had missed. Risk scoring prioritized two segments for immediate coating repair, while predictive models rescheduled lower-risk assets for later cycles.
Outcome
The operator avoided a potential loss-of-containment event, reduced overall inspection cost by a third in the first year, and shifted from a fixed six-month cycle to a continuous, risk-based integrity program.
Why Sentient Concepts?
Sentient Concepts builds AI systems that solve real industrial problems, engineered with domain expertise, deployed securely, and designed to integrate with the tools operators already use. CorroSense AI is backed by a team that understands both the science of corrosion and the practical realities of running critical energy infrastructure. Whether deployed in the cloud or fully on-premise for sensitive environments, the platform is built for the security, reliability, and scale that oil and gas operations demand.