Jardine, a DNV company, is a leading provider of consulting services for performance optimisation. The Jardine consultancy group was acquired by DNV in January 2005 following several years of DNV and Jardine working closely in an operating alliance.
Our Approach
Focus on improving production efficiency is not new. A typical asset often has some 30 to 50 reliability and production optimisation initiatives to improve performance each year. The question is: how successful have these been and how successful will they be in the future?
DNV utilises advanced simulation software (MAROS for the upstream industry; TARO for downstream; and TRAIL for railways) to capture the complex and inter-dependant parameters required for accurate performance forecasting:
- Production /feedstock profiles
- Asset design
- Equipment reliability
- Maintenance strategy
- Operations strategy
- Product demand profiles
In conjunction with the simulation software, DNV has developed a very successful methodology for asset performance forecasts:
- Assess current (historical) asset performance
- Establish best-in-class performance reference case
- Quantify the gap between current and best-in-class performance
- Review and rank potential field improvement initiatives in terms of impact on future production efficiency
- Forecast production year-on-year (efficiency, volumes, on-stream factors)
- Repeat for all assets in portfolio
- Provide a portfolio forecast of production year-on-year
Our Solutions
We provide quantitative asset performance forecasting including:
Benefits
- Accurate forecast of future production supporting the business plan
- A "road-map" of how the performance will improve from today’s performance level to future expected level
- Quantitative ranking of the potential success of initiatives based on production efficiency impact and cost effectiveness
- Assessment of the performance initiatives’ impact on safety and asset integrity
- Gives performance initiatives a voice in the business plan through assessing their combined impact on production efficiency for future years, i.e. translates engineering language to management language
