Published By Guest Author, Alexia Collier
The uses of big data and analytics are continually growing within the oil and gas industry. In fact, a 2018 study noted that 81% of executives in the field consider big data to be among the top three priorities of oil and gas companies, noting that big data trends can be used to improve many of the industry's processes. These include exploration, drilling, refining, and transportation. However, the researchers also cited plenty of challenges in implementing big data technology. One such issue is how companies can allow for data transfer from the field to data processing facilities. Another is the data literacy gap among the existing workforce and the lack of skilled personnel to help bridge it.
These challenges have driven the need for data experts in the oil and gas industry, adding to an already high demand for professionals with a data science background. Data from the Bureau of Labor Statistics point to a thriving field, with growth rates for management analyst, market research analyst, and operations research analyst jobs at 11%, 18%, and 25% respectively. This is why data science training has become a major career booster for today's professionals, pushing educational institutions to create advanced online programs to cater to the need. In fact, online master's degrees in data analytics allow working professionals to continue developing their skillset remotely and keep up with the evolving demands of industries like oil and gas. These programs cover the most basic techniques of data analysis to advanced practices of data mining and predictive modeling. Plus, they ensure that employees in the oil and gas industry stay up to date with technological trends. This then allows the industry to transition to more modern, digital systems.
Here are some of their most notable benefits:
Optimization of Upstream Practices
Implementing big data and analytics can improve upstream methods by providing operators with the information needed to improve efficiency. For example, exploration processes benefit from the visualization of seismic data. This allows operators to view a subsurface map, which helps them to plan their drilling plans accordingly. While drilling, operators can also gather data from the reservoir to topside equipment, allowing them to capture constraints and potentials throughout the value chain. With this data, they can generate insights that hasten the extraction process.
Preventive Maintenance for Machines
Through predictive analytics, operators can also collect factual data on their machine's mechanical and electrical state. This is done through sensory-monitoring devices, such as smart sensors and schedulers. Using this data, operators can predict when machines should be taken in for maintenance, minimizing the chances of mechanical breakdowns. Predictive analytics can also be used to pinpoint when a machine should be replaced.
Improved Safety Protocols
Data on the current terrain is crucial for ensuring the safety of the workforce, especially during drilling and extraction processes. When extracting resources from underground, employees on the field are always at risk of being exposed to harmful emissions. But seismic data and subsurface maps effectively decrease this risk. It allows companies to identify oil and gas sources without having to send their employees to hazardous operations.
More Efficient Offshore Operations
A study from McKinsey reports that offshore platforms only run at 77% maximum production potential, on average. This is because traditional control tools fall short. Thousands of sensors provide operators with data from every available piece of equipment. However, current data processing systems cannot take all of these factors into account. By implementing more advanced analytics software, companies can leverage automation and machine learning to synthesize the stream of data and gain valuable insights.
These examples are only some of the many uses of big data and analytics systems in the oil and gas industries. However, to fully utilize them, companies must push for data literacy and education among the workforce. Doing this ensures that the oil and gas industry continues to improve.