A lot of media attention has been given to “big data” in the past few years, but little of this attention has filtered down to the bulk of small and medium-sized companies in oil and gas.
You might think it's a topic just for the C-suite or IT departments, but everyone in the industry has a lot to gain from the big data mindset, if they can start to make better use of the information that matters to them.
Today we’ll take a closer look at why big data matters, and how all oil and gas companies can shift their thinking and apply the lessons to their business.
It's about answers and awareness
Data has always been the most sought-after asset in the oil and gas industry. That’s because it has the power to reduce the uncertainties associated with the relatively high-risk investments that make the industry tick.
In the early days, drillers were concerned primarily with the underlying geology of a region and used hand-collected data to answer questions such as: “how thick and extensive are the oil bearing layers?” and “What is the thermal maturity of the source rock?” As the “easy” hydrocarbons were depleted, it became necessary to delve into increasingly robust data repositories to figure out how to profitably extract oil. At the same time, an increasing emphasis on safety, liability, and environmental responsibility forced companies to keep a closer eye on their operations.
With the advent of computers and associated proliferation of sensors, telemetry equipment, and networked data repositories, the oil and gas industry entered a new era – the era of so-called “big data”.
Big data is a mindset, not just a technological system
Big data in oil and gas rests on a myriad array of sensors, ranging from the data collection systems integrated into a $250,000 MWD kit to relatively simple and cheap sensors used to measure temperature, pressure, or hydrogen sulfide concentrations. Even smaller companies are finding it relatively easy to collect increasing amounts of data during operations. Critically, modern software and systems are making it increasingly affordable and manageable to store, examine, and analyze all that data.
It's clear that big data wouldn’t work without the marvels of modern technology. But what every company should understand is that big data isn’t just a technology system – it’s a mindset. It’s a way of scientifically managing operations and capturing the information that matters, to maximize efficiency and minimize risk. And contrary to what you might think, operations of all sizes can benefit in their own ways by approaching problems with a big-data mindset.
For example, models developed by geologists can be calibrated to collected data and made more realistic. As more data comes in, adaptive management can be used to continually optimize operations. Adaptive management powered by big data is also effective during stimulation and production.
Big data can also reduce technical risks. For example, automated pattern recognition systems can alert operators when a piece of equipment is near failure or conditions in the borehole are problematic.
Defining the path to big data opportunities
While big data shows great promise, successful implementation can prove difficult.
A brief published by Bain in 2014 made this fact clear:
We often find that senior executives understand the concepts around Big Data and advanced analytics, but their teams have difficulty defining the path to value creation and the implications for technology strategy, operating model and organization.
To overcome these challenges, the best starting point for companies large and small is to change the way they think about the role of data. In particular, as highlighted in the Bain report, the acquisition and analysis of data should be central to a company’s business plan, not just a compliance-centric task handled exclusively by IT.
The Bain report should be required reading for anyone hoping to learn more, or successfully integrate big data into their company’s decision-making. By first thinking of big data as a mindset, oil and gas companies of all sizes can start to focus on the information that matters most to them, and start taking steps to capture and leverage that data.