September 12, 2016
Oil and Gas (O&G) companies all over the globe have been hit hard by the recent oil price drop. Since the crash began in June 2014, the 300 largest global oil and gas companies have recorded $2.3 trillion in stock market losses. Companies in the U.S. and further afield are finding themselves crippled with huge debts, leading to the closure of hundreds of wells in the U.S. alone, and high levels of staff layoffs, with more than one fifth of oil and gas workers losing their jobs in the most recent round of layoffs.
The O&G industry has been notoriously slow to advance technologically, but with low oil prices making it harder to make a profit using traditional methods, leading companies are turning to new technology to cut costs and improve efficiency. However, on top of using new tech to pull themselves out of the oil price slump, the O&G industry is also under pressure to make their operations more ecologically friendly.
So, how is new technology saving an old school industry and the planet at the same time?
What new technology could cut costs?
In a report released in March 2016, McKinsey estimates that each of the world’s major oil companies could reap $1 billion in cost savings and production increases from the adoption of digital technologies. At the recent OPEC meeting in Doha, 72 percent of oil and gas executives surveyed by Accenture highlighted cost reduction as the most important business challenge that digital advancement could bring, with roughly one half of those surveyed stating the intent to spend more on digital technologies over the next three to five years.
Internet of Things
At the forefront of this cost-cutting technology is the use of the Internet of Things (IoT) and data analysis to reduce costs in machinery maintenance, highlight low and high producing sites, and spot production trends.
According to IDC, by 2020 the market for IoT will be $8.9 trillion with 212 billion connected things around the world. Traditionally, O&G sites which sprawled over huge zones were manually checked for maintenance purposes, which was costly, slow, dangerous, and inefficient. Leaks or spills were often noted too late, and responses were slowed down by the geographic location of pipelines and wells, which could have devastating effects on the environment. Experts state that the IoT could massively improve efficiency, safety and ecological effects in all three stages of the O&G process.
Using new technology from companies such as WellAware, Algo Engines and C3 , companies can monitor their sites digitally and receive real time updates and analytics straight to their computer or even smartphone. Installing the IoT data collection devices can drastically reduce expenses related to manual processes, unaccounted for production, equipment maintenance, supplies and repairs.
New Big Data analytics reduce the amount of manpower needed on site, but human teams would still be needed to undertake repairs and day to day tasks related to extraction, production, processing and transport. Ditch diggers of the past are the well paid and trained excavator operators of today. Technology is empowering new types of work in Industry. Companies will also train their manual workers as operators, technicians, and data analysts for the intuitive new technology.
Christopher Helman argues that as companies roll out IoT monitors on their sites, vehicles and even employees using wearable technology, decision-making will become much faster and more accurate. When linked with historical data records from various sites, it will allow managers to make better, safer decisions, and spot trends which could help them improve production, and avoid spills and accidents.
Data Analysis and Big Data
Many leading O&G companies have thousands of employees, working on multiple sites in different locations, leading to the creation of a huge amount of data. Companies like Skynet Labs and Rockwell Automation have created systems designed specifically for the O&G industry to help them make sense of the massive amounts of raw data being created. These companies have created secure real-time O&G analysis and optimization software, which allows companies to make more informed drilling decisions. Every year roughly $15 billion is wasted due to manual drilling calculation errors. Skynet software is designed to take the slack for drilling engineers in their day to day tasks, improve operational efficiency, mitigate data risk and secure data collaboration between teams.
O&G giants like Royal Dutch Shell have begun to focus their efforts on creating data-driven oilfields in an attempt to cut costs, especially when drilling new wells. The giant is harnessing the power of big data to sniff out the most probable sites for deep water oil wells, which cost on average $100 million per project.
Aside from potentially saving hundreds of millions of dollars on fruitless drill projects, this new tech is also reducing the risk of catastrophic environmental disasters related to offshore and onshore drilling. By using Hadoop provided by platforms like MapR companies can analyze millions of data points from potential drill sites allowing them to identify anomalies in real time. As a result, well maintenance problems can be detected before they become serious, and drills can be shut off quicker in order to prevent environmental damage.
Artificial Intelligence and Drone Technology
Chevron is harnessing the power of machine learning artificial intelligence to trawl through troves of current and historical data on well sites to identify the most and least productive sites, and identify trends and anomalies. With a growing trend of companies focusing on data-driven oilfields, it is logical that the next step would be to automate the data projects using machine learning artificial intelligence. While the use of AI is still in its early growth stages in the O&G industry, a number of startups around the U.S. have their eye on what could potentially be a billion-dollar prize.
In late 2015 Chevron started flying drones over its California oil fields to collect data to for big data projects, and build high-definition maps of their site. Traditionally the only way to gather information on job sites for well pads and oil sites was with manned teams. Using traditional methods, this would cost at least a thousand dollars a day for a multi-man team, and would take up to a month to complete. On top of being labor and cost intensive, the data gathered was slow to process. Using drones, the same project could be done without the need for manual teams, at a fraction of the time and cost.
For now, it is up to leading companies in the U.S. and further afield to turn to technology to help them ride out the storm for as long as possible, in a cost-effective manner which reduces ecological damage and pollution. Automatization of procedures and data management empowers companies to carefully select their projects, choosing only sites which will be profitable. The new data-driven landscape is ushering in a bright new future of industrial efficiency, safety, and opportunity.
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