With high oil prices and ever-increasing demand, upstream, downstream and oil field service companies are profiting handsomely. However, more and more oil and gas companies are investing in improved process control and data analytics to optimize their operations and give them a competitive advantage.

The focus on environment, an uncertain economy and the growing need to get more value from existing resources are concerns for the oil and gas sector. This is putting demands on optimizing production to cut costs and maximize return on investment.

Multivariate analysis (MVA) is widely used in the oil and gas sector for performance prediction, understanding complex processes, planning maintenance and forecasting. Specific applications include:

• Implementation and improvement of process control with multivariate analysis
• Principal Component Analysis (PCA) for locating new oil reserves based on geochemical data
• Controlling the octane number of gasoline during gas blending with real-time prediction from NIR data
• Raw material identification, classification and chemometric analysis of raw material
• At-line process control using a NIR spectrometer
• Design of Experiments to minimize costly trial and error experiments with raw materials
• Multivariate Calibration for Process Analyzers
• Systems studied by high-pressure NIR spectroscopy
• Process understanding

New Opportunities
Searching for new resources or new processes to produce more energy from what is available, so as to meet the rising demand. Fast evaluation of raw material quality and adaptation of the process to available raw material is a competitive advantage that is well served by qualitative modeling and Design of Experiment.

Modeling demand
Understanding the variation in energy demand is also a key tool for optimizing production, it can be achieved using multivariate tools like regression analysis.

Climate change issues
Limiting environmental impact in the production and use of energy is both cost saving and environmental friendly. Running a Principal Component Analysis (PCA) and regression help to get an general overview help in understanding complex processes and determine leverages.

Quality Assessment
Ensuring the extraction of raw material with a specified quality and purity is a key to control the cost of production of oil derived products. On-line analyzers that ensure real-time measurements of this quality using multivariate models is critical in providing consistent high quality products.