Case Study
Oil & Gas
Challenge
At an olefins production facility in Saudi Arabia, the mixed-bed polisher unit within the demineralized water system suffered repeated mechanical failures for over a decade. These failures disrupted operations and incurred substantial maintenance costs.
Solution
Ingenero conducted a detailed root cause analysis leveraging engineering models and instrumentation logic. The team identified design and control flaws and recommended modifications, including reconfiguration of motor-operated valves (MoVs) and specific process adjustments to eliminate the failure triggers.
Outcome
- Chronic failure condition fully resolved
- Significant improvement in equipment reliability
- Maintenance and downtime drastically reduced
- $1.8 million/year in verified availability and maintenance cost savings
Challenge
An oil production company in India was facing frequent off-spec production, lower uptime, and inefficient diagnostics.
Solution
Ingenero implemented Continuous Proactive Operations Support using advanced analytics and remote decision insights.
Outcome
- $6.5 million savings
- Improved asset availability
- Real-time problem identification
Challenge
A US midstream operator with 40+ NGL processing sites struggled with feed variability, quality loss, and inconsistent profits.
Solution
Ingenero developed digital twins for each site and deployed centralized analytics to optimize operations and feed blends.
Outcome
- 22% increase in profitability
- Asset visibility across all sites
- Systematic issue resolution
An EPC firm engaged Ingenero to validate and redesign a pipeline in Russia. Using custom simulation models with terrain and elevation mapping, Ingenero identified a design flaw that limited capacity. The revised design increased total flow capacity by 12%, enabling the client to meet strategic throughput targets.
Verified Benefit: 12% higher capacity; legacy design flaw corrected
Challenge
A gasification plant in South Africa was experiencing recurring failures and needed to shift from reactive to predictive maintenance.
Solution
Ingenero used ML models based on five years of historical data, metallurgy, and design parameters to forecast failures with longer lead time.
Outcome
- 80% accuracy on 22-day prediction horizon
- 4% increase in availability across 80 gasifiers
