What Role Does Data Analytics Play in the Oil and Gas Industry?

Oil and gas are two of the most critical fuel sources that power the world. However, data is an essential asset that enables that global energy.

In any business, data-driven decisions and operational intelligence are becoming standard practices. Oil and gas companies are no different, but the fuel industry has a unique set of challenges. For example, as oil prices rise and fall every week, operations must make fast decisions that rely heavily on data analytics.

If you want fuel demand intelligence to power your business decisions, look no further than Refined Fuels Demand. We use our knowledge from processing nearly 85% of refined fuel lifts in the United States to provide meaningful, location-specific operating statistics and an unparalleled, analytical look at demand activity.

This article will discuss the benefits of data analytics and how big data is impacting the oil and gas industry at each level: upstream, midstream, and downstream. It will also demonstrate how information is not enough and what kind of data analytics leads to success.


The benefits of data analytics

Data volume in the oil industry changes rapidly, and keeping up with the sheer volume of data produced can be overwhelming. The use of data analytics keeps that information organized in a cost-effective way with real-time alerts and updates.

Reducing risk is one of the most significant benefits of using data analytics in terms of money and time saved. Oil companies can make confident investment decisions based on facts by monitoring real-time data rather than gut feelings or anecdotal information.

The value in big data is realized at each step in the journey from crude oil to a refined product. Let’s consider each step in the supply chain, and how data analytics can improve that process.

Pipeline with data in the sky

Data analytics in upstream sector

Upstream oil companies are always looking for new efficiencies and processes to automate. For example, they might use data analytics to optimize exploration processes or predictive models to forecast and get ahead of equipment failures. It can also be used to improve reservoir engineering and manage seismic data.


Data analytics in the midstream sector

Shipping and transportation logistics in the oil and gas industry are incredibly complex. As a result, companies in the midstream sector face the challenge of transporting oil and gas with as little risk as possible. Using data analytics to schedule maintenance will prevent costly pipeline incidents.

Data analytics employs sensor input to guarantee the safe delivery of energy products. For example, predictive maintenance software interprets sensor data from pipelines and tankers to identify fatigue cracks and stress corrosion to prevent accidents. And accurate weather and ocean conditions data helps fleet managers know where and when to send their tankers.


Fuel truck driver smiling

Data analytics in the downstream sector

As in upstream energy, using analytics in the downstream sector can forecast issues with equipment, allowing companies to perform maintenance or make repairs before a more expensive problem arises.

The downstream sector focuses on refining fuel, which is where data analytics can be used most effectively. Using automated systems, companies can produce more fuel with less labor and energy usage over time.


Fuel demand intelligence

Fuel demand intelligence is a hot topic in the oil and fuel industry. It is defined as when oil and gas companies use the data they have collected to design and deliver products that will meet their customers’ actual needs rather than what they assume those needs might be.

Companies must be able to forecast how much fuel will need to be produced daily, which can present challenges when it comes to systems with long lead times or weather unpredictability.

Having the correct data with the right analytical power means maximizing profits and taking advantage of opportunities in real-time. For example, when operations managers are provided with daily market-level demand numbers, adjusting the timing and location of products throughout seasonal formula changes will be a lot simpler.

The same information may help determine when to release a product for sale or keep it in storage for a more advantageous time.


Not all data is created equal

When determining your position relative to the market, you need enough data to create a big picture allowing for more meaningful insights. For example, how are you performing compared to the rest of the market?

As well, when looking at your position in the market, you’ll want to look at various service areas. Without overall market demand data, you cannot know if your market share is growing. However, with demand data segmented by market, you can easily compare your volume data against specific energy markets.

With any dataset, the other danger is too much information. The phrase “paralysis by analysis” means no decision is made while ein a constant chase for more data to support one position over another. It can be overwhelming to try to sift through the relevant and irrelevant information. 

Fortunately, as technology improves, our ability to capture and analyze more data types becomes more manageable – from fuel usage to weather patterns.

Hands on laptop with data

Adding context to your fuel demand intelligence data

In 2006, marketing commentator Michael Palmer made the following statement, “Data is like crude. It’s valuable, but if unrefined it cannot really be used.”

Industry experts recognize the need not just for data, but for the ability to analyze that data and communicate clear, actionable insights.

This need for insight is why fuel demand intelligence, or fuel-demand forecasting as it’s sometimes referred to, has become so popular in the oil and gas industry. Fuel-demand forecasters can use past patterns of consumption behavior along with current information about fuel price fluctuations, infrastructure changes, and geopolitical events to predict future fuel demands.

Refined Fuels Demand offers fuel demand intelligence at the PADD and rack city levels. By using volumetric market intelligence from nearly 85 percent of all downstream energy transactions in the United States, you can have a competitive edge in the decisions that you make every day. 

Data analytics is the future of the oil and gas industry. Simply put, it is a better way to do things. Contact us today to learn more about how Refined Fuels Demand can streamline your operations and improve your bottom line.