Sustained low prices have put pressure on the oil and gas industry to become more efficient and lower costs. To become profitable, oil & gas producers depend on a sustainable supply, stable demand, and available storage. All of these have been in flux due to changing market dynamics and growing U.S. energy independence.
Further, the lifeblood of oil and gas has always been exploration and production. The constant search for the next sustainable supply is a key pillar of the industry. However, one resource that hasn’t been fully tapped is Big Data.
Benefits of big data
To reach peak performance, all aspects of an operation must be synchronized. There is no room for error when it comes to managing asset maintenance and risk, particularly when the average cost of unplanned downtime is $7 million per day for an onshore well – and that escalates significantly for offshore facilities.
The industry has invested heavily in sensors and connected machines to improve asset management and better predict maintenance and operational needs. Machine-to-machine connections, information from sensors, and resultant Big Data have taken off.
Cisco Systems estimates that the adoption of the Internet of Things (IoT) by an oil and gas company with $50 billion in annual revenue will generate an 11% improvement in the bottom line from reduced cost and greater production. This is largely driven by improvements in asset utilization and process or supply chain efficiency.
Just because everything is connected and creating massive amounts of data doesn’t immediately benefit the bottom line – it depends on how all this data is converted into useful information and used effectively.
In 2013, only 22% of data from connected devices and machines was considered useful. International Data Corp. predicts useful data will grow to 35% by 2020. For the oil and gas industry, however, the percentage of data being processed is startlingly lower. A recent study by McKinsey & Co. revealed less than 1% of data gathered from sensors on global oil rigs were available for industry decision makers.
While sensors and connected machines are generating more data, there is no advantage for the oil and gas industry if this data sits unused.
It’s safe to assume that production assets are currently operating below peak performance because data from sensors is not being processed. It’s not just field operations but the systemic supply chain that feels the impact of lost oil, downtime, and inefficiencies.
Beyond the reliability of pumps, controls, and other critical equipment, oil and gas companies depend on the consistency of suppliers and scheduled deliveries. Any level of imprecision or uncertainty can mean huge fluctuations in cost.
Implementing the IoT
Managing big data generated from the IoT helps maintain schedules and eliminates downtime with predictive maintenance to avoid catastrophic disasters or production losses. For example, Dakota Gasification, owner of the world’s largest carbon dioxide sequestration facility that converts coal into natural gas and chemicals, needed to consolidate its databases, spreadsheets, and equipment files to better understand asset reliability. The organization also needed to integrate enterprise asset management (EAM) work order history and track production losses against specific assets.
Implementing an asset performance management system (APM) made it evident that Dakota Gas needed to concentrate its risk-based inspection efforts on fixed equipment. Managing tasks within the APM software system, the company was able to keep its EAM system current and accurate in scheduling inspections. Personnel could also track change management, production losses tied to specific assets, work history, corrosion analysis, asset criticality, and equipment saves. By integrating its big data from an EAM system and tracking production losses against specific assets, Dakota Gas saved $8 million.
As more data becomes integrated and used across the discovery, harvesting, refining, and delivery segments, the market will maintain a steadier cost structure.
Data allows stakeholders to pinpoint how much supply is required to meet shifting demands and adjust business operations to avoid waste. While equipment sensors offer real-time data about operations, the information is not properly collected, managed, analyzed, and transformed into reports for all levels of the organization to make immediate or long-term planning decisions. Even worse is the lack of context for sensor data from critical pieces of equipment – those exposed to extreme enviorments that may also contain highly corrosive materials.
Current affordability and capability of sensors, computer processing, and memory means more data will be coming soon – in large volumes.
Advanced software that collects pertinent data in a single location, converts it into actionable information, and makes it available transparently where, when, and in the format needed, is going to help realize the promise of the IoT and Big Data.
Dakota Gasification Co.
About the author: Eddie Amos, chief technology officer of Meridium Inc., can be reached at email@example.com.