Instrumented Interconnecteds Intelligent

By Ulisses Mello
Director, Natural Resources
IBM Research

Last week, Brazil’s Petrobras made yet another major discovery in a giant offshore oil region that could contain as much as 10 billion barrels of oil. That would be enough to meet the needs of the United States, the world’s biggest oil consumer, for one year.

That’s the good news. The not-so-good news is that prospecting for oil, drilling, and moving the oil to the shore in this region off Brazil’s coast is very expensive, technically challenging and perceived as risky to the environment. That’s primarily because of the extreme depth of the ocean floor in the area, more than 2,000 meters, and the difficult geological conditions, including a 2,000-meter-thick layer of salt.

The complications swirling around Brazil’s offshore oil bonanza illustrate the challenges facing the world’s natural resources industries—including oil, natural gas and mining. A lot is going on all at once. Demand is expected to soar when global economic growth resumes, especially in emerging markets. Yet, in many cases, new discoveries are expensive and harder to extract. At the same time, environmental concerns put restrictions on the whole range of natural resource business activities—from production to refining to distribution. And, in the near future, alternative energy sources could radically alter the business landscape.  To cap it off, politics adds extra risks and uncertainties.

I believe that natural resources companies will be able to better handle these complex forces if they take advantage of a new generation of data analytics technologies and adopt a more holistic view of their key business imperatives. Today, too many companies see efficiency, effectiveness and environmental sustainability as three separate requirements. They keep them in silos. New data management and analytics technologies make it easier to understand the interdependencies between these imperatives and to manage them better.

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At IBM, we’re addressing the challenges facing our clients in several ways. Scientists at IBM Research labs worldwide collaborate to develop new technologies addressing the needs of the industry. In fact, IBM Research – Brazil, which opened in 2010, has made natural resources one of its primary focuses.  (I returned to my native Brazil after many years in the United States to work in the new lab.) In addition, IBM’s software group has established a global network of natural resources industry solutions labs—which turn technologies into products. The newest of the solutions labs, announced today, is in Sao Paulo.

The natural resources industries are a sweet spot for IBM Research. That’s because, increasingly, the exploratory work we do in mathematics, analytics and system optimization has important new uses in these industries.

One example is our work in petroleum exploration with Repsol, the Spanish oil giant, in the Gulf of Mexico. To locate new oil deposits far offshore, companies use advanced seismic imaging technologies to get as detailed a picture as possible of the subsurface landscape. Using sophisticated algorithms, they translate large amounts of seismic data into 3D images that their experts can interpret. We helped Repsol develop a new computational method for running its seismic algorithms that resulted in an 85 percent reduction in the time required to run the algorithms, substantially lower power and cooling costs and hopefully fewer dry holes. It achieved efficiency, effectiveness and sustainability all rolled into one project.

It’s in the interest of the major oil companies to cooperate to come up with technologies the entire industry can use to improve operations—and their environmental stewardship. We’re pleased to be involved in a research project involving three Norwegian oil companies whose goal is to develop the world’s first integrated environmental monitoring system aimed at understanding and minimizing the environmental impact of undersea operations. By collecting information about the flora and fauna even before a platform is put in place one can fully measure the changes in the evironment caused by the operations. In addition, using advanced modeling techniques, the system we’re developing will be able to do more than simply monitor conditions. It will predict and prevent problems before they occur. The system can also be used to monitor and manage all aspects of a company’s undersea operations. Once again, it’s a holistic approach.

Our work extends to the mining industry, as well. We’re helping an Australian mining company improve the way it manages its trucks and excavating equipment.  Using advanced modeling and analytical techniques, the company will be able to improve the efficiency of its maintenance program, minimize down time for equipment and drive increased production at a lower cost.

As we engage with the oil industry in Brazil, we’re bringing technologies that were first deployed elsewhere in the world for a wide variety of industries and uses, and we adapt them to the needs of Brazil. In this way, we’re becoming part of a sophisticated, technology-centric ecosystem that’s emerging to address the discovery and extraction of oil. However, given the richness of the ecosystem in Brazil, I believe it will produce innovations that make Brazil’s industry a model for the rest of the world in efficiency, effectiveness and environmental sustainability. As I learned during my years of working in the United States, “What goes around comes around.”

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Here’s a white paper about how analytics and optimization can help the oil and gas industries.

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1 Comment
 
August 22, 2012
7:44 am

This is a very interesting article on the logistics of oil extraction and how data analytics can help. As you point out I believe that by using data analysis techniques these obstacles can be overcome and this much needed supply can be obtained.


Posted by: Tom @ Whitehall
 
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August 23, 2012
5:26 pm

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