by Fred Haubold, Director of Americas SAS Global Oil & Gas Business Unit

With the days of easy oil behind us, oil and gas companies are investing in new and innovative ways to maximize the performance of their assets. As their infrastructures age, the need for analytics to predict asset behavior and optimize equipment performance becomes even more critical. Now, the emphasis on margins and productivity in the oil and gas industry is greater than ever before. Deploying sophisticated analytics in the area of integrated operations can significantly impact these key performance indicators.

The high cost of failure

Equipment failures and unplanned production stops are expensive. A shutdown of a major platform in the Gulf of Mexico for one day may cost a company more than $6 million (USD) in lost production. If you shut down a refinery processing 300,000 barrels of oil a day for a week, costs may surge up to $18 million (USD). In addition, unforeseen production stops can make it difficult for companies to stay compliant with Sarbanes-Oxley and other accounting rules. And maintenance problems can also create safety issues and harm the environment.

Following an explosion at a Texas refinery in 2005, BP paid $21 million in fines and set aside $1.6 billion to pay claims. The U.S. Chemical Safety Hazard and Investigation Board’s final report said that much of the “refinery’s infrastructure and process equipment were in disrepair.” New, innovative approaches can be used to help companies predict if and when events like what happened in Texas will occur. By monitoring the condition of in-service equipment, companies can use their sensor data to build real-time models. These models employ analytics to predict and prevent costly incidents before they happen.

For example, critical pieces of equipment like compressors have vibration sensors that monitor the condition of the compressor. When these sensors detect vibration, it is already too late to correct the issue. These vibrations can cause irreparable damage and can potentially lead to an unplanned shutdown. Using analytical models, companies can detect the early warning signs that a compressor vibration may occur. This foresight enables companies to prevent equipment failure before it happens—avoiding catastrophic events. If you expand this methodology to an entire asset, or to an entire company, it can make a significant impact.

Taking predictive analytics to the next level The North Sea is rich in both oil and brutal conditions that make maintaining steady production capacity difficult. But that environment has also bred creative thinkers at companies, who are willing to think outside the box. One such company decided it wanted to be able to predict maintenance problems. Within a few years of applying analytics, it improved productivity by 20 percent, increased production by five percent and reduced unplanned downtime by as much as 80 percent.

The company didn’t do this by having a computer tell it to rigorously adhere to the manufacturer’s recommended maintenance schedule. These schedules often reflect “ideal” or average circumstances—not the ones on a North Sea oil platform. Instead, it used predictive analytical models. These models use data pulled together from field instruments and sensors scattered across the production environment. Analytics are then applied to detect underlying patterns, find the root cause of reliability and identify efficiency and quality issues.

You can go one step further by combining predictive modeling with financial systems and ERP, CMMS, PI and HSE databases. This approach to integrated operations gives you a 360-degree view of your operation and enables you to optimize your asset.

A necessity not a luxury

Achieving integrated operations is no easy task. It involves executive sponsorship, change management and master data management built upon an analytical framework. Through this significant investment, companies are able to reinvent the way they do business. And in the new age of energy, obtaining maximum performance from your asset is not only a competitive advantage, but a necessity.