The oil and gas industry is constantly facing a wide range of industry-based challenges that include lack of insight into a more complex operational process, equipment for life-cycle management, the complications of performance improvement, meeting environmental regulations, and logistics complexity. Now, the enormous amount of data produced by the oil and gas industry can overcome these challenges when they are crunched into systematic and meaningful insights.
Big data analytics helps to streamline the essential gas and oil operations like delivery, production, drilling, explorations, in all three sectors, downstream, midstream, and upstream.
The Upstream Sector
Big data solutions can be implemented in this sector for:
1. Managing seismic data
The first step of upstream analytics starts with the collection of seismic data across the area of interest to search for petroleum sources. When the data is acquired, it is processed as well as analyzed for determining the perfect location for drilling. The data can be even paired with various other data sets for determining the oil reservoirs’ capacity.
2. Optimizing drilling processes
Drilling processes are optimized by customizing predictive models that can estimate potential equipment failures. The equipment is firstly fitted with sensors for collecting data throughout the drilling operations. The data is then paired with the metadata of the equipment to run them via machine learning algorithms. This helps in identifying usage patterns that have a possibility to end during breakdowns.
3. Improving reservoir engineering
Downhole sensors like pressure sensors, acoustic sensors, temperature sensors, and likewise have the ability to gather data that is needed by the companies for improving reservoir production. For instance, with the help of big data analytics, gas and oil companies can develop their reservoir management applications for attaining actionable and timely information regarding changes in temperature, pressure, etc. This helps in increasing their control and insight over their operations in order to drive reservoir profitability and performance.
The Midstream Sector
When it comes to the petroleum industry, logistics is an incredibly complex issue. Their main concern is to safely transport the gas and oil without causing any risk whatsoever. Companies take the help of sensor analytics for ensuring the safe logistics of the energy products. Through big data analytics, companies analyze the sensor data from tankers and pipelines for detecting abnormalities like stress corrosion, fatigue cracks, seismic ground movements, and more that helps in preventing accidents.
The Downstream Sector
Most petroleum enterprises employ big data services for reducing maintenance costs and down times of the refinement equipment to improve further asset management. Here, the equipment’s performance is analyzed first by comparing its current operating data with its historical data. Depending on the failure conditions and end-of-life criteria of the device, the performance prediction gets tuned. Lastly, the equipment’s estimated performance is visualized as well as presented to the maintenance specialists to let them take further decisions like replacing the assets, and likewise.
Big Data Analytics: A Real-life example
One of the supermajors in the oil and gas industry, the Royal Dutch Shell PLC leveraged upon big data potential in order to survey as well as monitor various oil exploration areas. To indicate whether a particular area contains gas and oil deposits, the company had employed a seismic analysis for surveying the area. The more sophisticated and comprehensive big data analytics allowed the company to understand the nuances of the drilling site before they decided to drill.
Furthermore, for measuring seismic data, the company even installed optical fiber cables along with sensors inside the wells. The seismic data is analyzed further with the help of artificial intelligence technologies to create 4D and 3D maps of the reservoirs. This helps in finding out the number of remaining resources in the reservoir.
Through big data analytics, Shell has generated enormous amounts of sensory data and they analyze that data to improve the performance of drilling machinery. This helps in stimulating longer drilling periods with lesser maintenance stops. Hence, the lifespan of the equipment was extended easily. By following these tactics, Shell has saved over one million dollars solely in Nigeria.
Moreover, big data analytics has also helped the Royal Dutch Shell PLC to cut the carbon footprint of the environment. The company’s latest sustainability report states, “supports the vision of a transition towards a net-zero emissions energy system.” They also plan to use specific big data analytics features like storage technology and carbon capture for reducing emissions.
Unleash the potential of Big Data Analytics
With the help of big data analytics, petroleum companies can now transform huge datasets into full-proof gas and oil exploration decisions, lower environmental impact, extend equipment lifetime, and reduce operational costs.
An oil and gas company can hugely benefit from hiring a big data agency as they can advance the company’s key operations through customized big data solutions.