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Using Big Data Analytics for Oil & Gas

While the concept of “big data” has been in the public consciousness for several years now, far too few companies actually take advantage of what it offers. They’re convinced that it doesn’t apply to them, that it costs too much, or that it’s just not right for them right now. In reality, big data analytics can help every industry, and we especially think that oil and gas companies should seriously consider what this technology has to offer.

This article will help you understand:

  • What big data is
  • How people use data science
  • How companies use big data analytics in the oil and gas industry
  • Why oil and gas companies need big data

As production increases and margins shrink, data analytics might provide the edge your company needs to find real success.

What Do We Mean By ‘Big Data Analytics?’

Big data is the idea that some aspect (or every aspect) of your business operations generates large amounts of information, and you need to figure out what to do with it.

Before the time of computers, companies either had to analyze everything manually or decide what would be analyzed and what will be ignored. To be clear, that still remains an important business decision to make, because not every piece of data needs to be analyzed by an actual person. Big data allows a smart computer program to dig into all of that information on your behalf.

Hence, big data analytics gives your company the power to first absorb every possible bit of information possible — both generated by your business operations and your customers — and then create actionable intelligence for you, thanks to machine learning. It’s the ability to make business decisions as efficiently as possible because the tiny details have been examined with a fine-tooth comb by a computer.

What’s the Difference Between Big Data and Data Science?

Depending upon what you read, it can seem common to lump these two ideas together as synonyms. But while that approach isn’t totally wrong, we feel they are more complementary than identical.

  • Big Data = the collection of the information
  • Data Science = the investigation of the information

Put another way, a company’s big data program isn’t worth anything if it doesn’t actually analyze the data in a productive fashion. Big data helps a business only if it makes use of the information being collected.

Common Applications for Big Data Analytics

Luckily, there’s a long list of ways big data analytics has been effectively implemented to change corporate and consumer behaviors in pursuit of increased growth and success.

  • User experience research in e-commerce website and apps
  • Workflow analysis in warehouses
  • Machine efficiency and maintenance on assembly lines
  • Predictive analysis and forecasting for online trading
  • Biomechanics and performance in athletics

And that’s just the tip of the iceberg, as more and more companies collect more and more data. But what really matters is what they do with the information.

How Can the Oil and Gas Industry Benefit from Big Data Analytics?

Anyone who’s ever been involved in the oil and gas industry knows how much raw information is available for analysis. Whether you’re involved upstream, midstream, downstream, administration, or the commodities market, you are surrounded by data. The problem has always been knowing what to do with it so your company can make an informed decision.

By engaging in substantive data science efforts with regard to the eight applications below, any oil and gas business can make a marked improvement in its bottom line and overall success.

Data Crunching

From wells, digs, and extraction to transportation and refining, there are ample opportunities to collect data on every single aspect of your business operations. But you also need to process that unstructured data effectively. Investing in machine learning will help a company absorb petabytes of sensor data from drills faster than a whole fleet of workers on the actual job site. This frees up the people to make better, more informed decisions.

Predictive Analysis / Forecasting

As we discuss in our machine learning article, algorithms can use historical data and experience to make better and more enlightened predictions about future operations. Companies in possession of this level of enhanced analysis can use it to make very educated guesses about future trends, prices, production, and actions in the market. The more you understand what could happen with your industry, the better prepared you will be for any contingency.

Decision-Making / Risk Reduction

Oilfield work at every level has its risks, so mitigating those concerns is important to all stakeholders. With predictive analysis, you can make the move from educated guesses to confirmed, real-time decisions with ease and confidence. In essence, data analytics doesn’t remove the human element from making decisions — it helps humans make better decisions, thanks to insights and perspectives that were previously unavailable.

Productivity / Cost-Effectiveness

When you have access to game-changing information about your operations, it becomes easier to increase the efficiency and efficacy of your projects. This increase in productivity can be experienced at every level of the oil and gas industry:

  • Effective oil exploration
  • Accurate drilling in oil reservoirs
  • Improved extraction processes
  • Efficient shipping routes
  • Optimized processing workflows
  • Enhanced pricing models
  • Increased sales opportunities

And once you’ve helped your people and processes work smarter, it can reduce costs and maximize your investments.

Maintenance / Resource Allocation

Everyday operations in the oil and gas industry depend upon a substantial amount of machinery. Thus, it’s essential for a business to keep tabs on the condition and fitness of its equipment so it can address problems before a shutdown occurs — or worse. Advanced analytics can compare the age of a given machine with its rate of past and future usage to determine when it’s most likely to need maintenance and replacing.

Advanced knowledge of when a company might need to invest money into fixing older machines and buying new ones allows for more effective budgeting. This then gives a company increased insight into how it can spend money with the greatest long-term impact.

The Oil and Gas Industry Needs Big Data

No matter how entrenched in the “old ways” a company might be, now is the time for the entire oil and gas industry to embrace the benefits of big data analytics. Between increased production, increased technology, and shrinking demand, profit margins are tighter than ever. Digging deeper into the data can help your company locate a new possible advantage or efficiency that makes a big difference.

When a company leverages big data, it doesn’t mean everyone has to become a data scientist and reject traditional instincts. It does mean that people need to be willing to accept help from machines. Since oil and gas companies create lots of information, it makes sense to find new and improved ways to put that information to the best possible use.

Data science can help oil and gas businesses improve operations, profits, and safety — all of which are goals that benefit the entire industry and move it forward.