When Every Barrel Counts: Engineering Resilience into Energy Infrastructure
For operators of long-distance liquid transmission systems, design capacity is only a promise. What actually flows through the pipeline depends on something far less visible: reliability.
Evidence-Driven Strategy
Multi-year Horizon
RAM Analysis
Transforming Infrastructure Assessment
This project redefined how one major midstream energy operator evaluates the performance of its core transportation asset — a large-scale crude oil pipeline spanning challenging terrain and serving critical supply chains. Instead of relying on theoretical throughput or isolated equipment specs, the team built a dynamic digital representation of the entire system, where mechanical behavior, operational logic, maintenance practices, and expansion plans converge into a single source of truth.
The model doesn't assume perfect conditions. It simulates real-world complexity — thousands of possible futures where pumps fail, repairs take time, and redundancy determines continuity. It captures not just what the system was built to do, but what it will actually deliver over years of operation, given the realities of wear, response, and interdependence.
Comprehensive RAM Analysis Approach
Using advanced probabilistic simulation, the team developed two integrated models to assess both current performance and planned expansion scenarios.
Representing the baseline configuration of the pipeline, capturing current pumping capacity, storage capabilities, and control logic to establish performance benchmarks.
Simulating the post-expansion state, incorporating new pumping stations, additional booster units, and enhanced surge storage at key terminals to validate investment decisions.
Collaborative Development Process
The models were built collaboratively with engineering and operations teams, integrating field knowledge, maintenance history, and failure rate data to reflect realistic system behavior. Each component — from primary pumps to backup systems — was assigned reliability parameters and repair dynamics, enabling the simulation of thousands of operational timelines over a multi-year horizon.
Key Achievements
Comprehensive analysis delivering actionable insights for infrastructure optimization and risk management.
Simulated Real-World Variability
Accounts for unplanned outages, scheduled maintenance, repair durations, and standby activation logic, generating statistically robust forecasts.
Validated Expansion Design
Provided independent assessment of major infrastructure upgrade, confirming measurable gains in delivery capacity and resilience.
Identified Critical Bottlenecks
Pinpointed network segments whose reliability disproportionately affects overall performance, highlighting improvement opportunities.
Tested Sensitivity Scenarios
Evaluated alternative operating conditions to understand their impact on continuity and risk exposure under various constraints.
Separated Operational vs. Reliability Constraints
Distinguished between design limitations and those imposed by equipment unreliability — crucial for prioritizing actions.
Established Reusable Framework
Created structured, transparent model that can be updated with new data and replicated across similar assets.
Strategic Impact: From Assumptions to Evidence
The RAM model transforms planning from assumption-based estimation to evidence-driven strategy, enabling leadership to make informed decisions with quantifiable outcomes.
- Justify capital investments by quantifying operational return on redundancy and capacity upgrades
- Optimize maintenance planning based on actual system criticality, not just schedules
- Anticipate low-throughput scenarios and prepare contingency responses in advance
- Align engineering decisions with business outcomes through quantified performance metrics
- Improve cross-functional alignment through shared, dynamic understanding of system performance
- Position model as living tool for ongoing optimization, not one-time deliverable
Industry-Wide Applicability
In an industry where uptime equals revenue and disruption carries cascading consequences, this approach sets a new standard for how critical infrastructure should be understood, optimized, and evolved. Designed for scalability and adaptability, this methodology offers a replicable blueprint for assessing critical infrastructure across the energy sector — where performance isn't measured in design sheets, but in barrels delivered, day after day, under real-world conditions.
Ready to Transform Your Infrastructure Planning?
Move beyond theoretical capacity to understand real-world performance. Let's discuss how RAM modeling can optimize your critical infrastructure investments.