Advanced Benchmarking Methodology Applied to a Gas Processing Facility: A Case Study

An AP-Networks Case Study

Executive Summary

When a major energy company needed to validate their cost and schedule targets for a new billion-dollar+ gas processing facility, they turned to AP-Networks’ Advanced Benchmarking Methodology (ABM) to cut through uncertainty and provide data-driven answers. The facility, designed to process over a billion cubic meters of gas annually containing H₂S and condensate for domestic market supply, represented a significant capital investment requiring rigorous validation.

The benchmarking revealed a mixed picture: while project costs aligned with industry standards, the proposed schedule stretched 16% longer than typical projects of similar scope and complexity.

The Challenge

Large-scale gas processing projects carry inherent risks. Cost overruns and schedule delays can transform profitable ventures into financial disasters. For this particular project, stakeholders needed confidence that their estimates reflected realistic market conditions and achievable targets.

The nature of the Front End Loading (FEL), and partial Front End Engineering Development (FEED) package completion added layers of uncertainty. This, combined with the nature and desired location of the plant, required careful consideration. Each characteristic of the project carries cost and schedule implications that needed validation against industry data and experience.

Our Approach: Leveraging AP-Networks’ Industry Intelligence

Proprietary Database Foundation: AP-Networks drew from our extensive proprietary database of gas processing plants in our onshore project repository. This wasn’t just a collection of numbers—it represented real-world project outcomes spanning various complexity levels, from basic processing to facilities with NGL recovery, fractionation, and sweetening capabilities.

Regional Context: Ten major projects from the same geographic region provided location-specific insights. A recently executed project in the area offered current market conditions and contractor performance data, enabling precise location adjustments to the analysis.

Scale Validation: Regional projects up to $1 billion provided direct comparisons, while mega-projects ranging from $1 billion to over $50 billion TIC offered insights into scale effects and complexity premiums.

Systematic Assessment: AP-Networks’ analysis followed a comprehensive checklist covering every critical processing elements as well as consideration for class of estimate, contingency and management reserve allocations.

What the Data Revealed

The Good News: Competitive Costs – The deterministic project cost estimate aligned with industry standards. Years of market analysis and contractor engagement had produced a realistic baseline. The estimate incorporated appropriate risk premiums across all categories, including materials, reflecting current market conditions.

The Reality Check: Extended Timeline – Construction schedule projections ran 16% longer than industry averages. This finding triggered deeper analysis into the drivers: Was this realistic planning or conservative padding? The data suggested a combination of both.

Labor Economics in Focus: Labor hours exceeded benchmarks, but competitive regional wage rates offset much of the impact. The project strategy emphasized local resources more than typical industry megaprojects—a approach that traded efficiency for reduced execution risk and community benefits.

Engineering Efficiency Questions: FEED and Engineering costs appeared 12% below industry averages relative to material costs. This raised questions: Had engineering scope been adequately defined, or did efficiencies in design and project management account for the variance?

Field Work Intensity: Direct field hours ran 23% above industry norms for greenfield work, driven primarily by extensive civil work and steel structures including piperacks. Brownfield hours showed even greater variance at 100% above industry averages, concentrated in concrete and piping work.

Critical Insights for Decision-Making

Cost Floor Reality: The current estimate represented a cost minimum with limited flexibility for scope changes. This finding carried significant implications for project execution strategy and change management protocols.

Risk Management Recommendations: AP-Networks’ Risk Manager assessment recommended setting aside additional low-percentage contingency reserves and validating specific areas of concern within the deterministic estimates.

Productivity vs. Scope Questions: Higher field hours could indicate either greater material quantities than peer projects or lower productivity assumptions. Distinguishing between these factors would prove crucial for execution planning.

The Bottom Line

This AP-Networks benchmarking effort provided stakeholders with the clarity they needed. The cost estimate earned validation as acceptable to the business unit, while the extended schedule received verification as realistic given project-specific factors.

Most importantly, the analysis identified specific areas requiring attention: engineering scope validation, field productivity optimization opportunities, and brownfield work efficiency improvements. These insights transformed abstract concerns into actionable focus areas for project development.

AP-Networks’ Advanced Benchmarking Methodology didn’t just validate numbers—it provided a roadmap for project success, highlighting both strengths to leverage and risks to manage as the project advanced beyond Pre-FEED into detailed engineering and execution.

For more information about AP-Networks’ Advanced Benchmarking Methodology and project intelligence services, contact our team of industry experts.

TJ

Each week, TJ Felts, Director of Capital Projects at Asset Performance Networks, explores the industry’s challenges and how innovative portfolio management tools are transforming the landscape of capital project management.