by Lloyed Lobo

    Deconstructing Data to Reduce Cost per Barrell

    Big data has become something of a buzzword. For the uninitiated, big data is information that is so large, complex, and fast moving that it’s difficult to handle using everyday data management tools; however, within it lies useful, actionable intelligence that could lead to enhanced decision making, insight discovery, optimized processes, improved efficiencies, reduced costs, higher profits and so on.

    The concept is certainly not new to the Oil and Gas (O&G) industry where finding and producing hydrocarbons is technically challenging and economically risky creating massive amounts of data in the process. According to research by global market intelligence firm IDC, each productive well generates 1 terabyte of data everyday, equating to the full text data of Wikipedia every week!

    Unfortunately, the data comes in various and increasingly complex forms – from traditional sources, such as equipment monitoring and maintenance records to relatively untapped sources, such as seismic input, weather patterns or social media – making it difficult to interpret and leverage.

    However, by implementing solutions that could combine and analyze these disparate sources of data, not only will O&G companies gain better visibility and control, but also optimize production and significantly reduce energy consumption, operating costs, and downtime. An article in The Wall Street Journal states that the result could be an additional 125 billion barrels worldwide, which is “almost equivalent to the current estimate of reserves in Iraq,”

    With the prevalence of Cloud-based software, the freedom to throw large amounts of data against very powerful servers that remain behind the scene will enable O&G companies to explore new ways to extract value from their data without disrupting daily workflow. The flexibility and seamless nature of web-based client interfaces means updates without IT support, and live analysis of user workflows – allowing software to be continuously tuned.

    Analyzing these massive data sets for insights has ushered in a host of new innovations right in our backyard. Osprey helps you monitor your remote sites at any time of the day from any device via a web-based application. Data Scavenger provides a suite of products for data sharing, collaboration and analysis. PetroFeed is creating a new way to monitor and research industry activity by sending you automatic notifications on activities like well licenses, drilling and other asset related events based on your interests. Also making strides in the Alberta market is Silicon Valley’s Nebula, founded by the former CTO of NASA and Co-founder of OpenStack, which enables companies to easily, securely, and inexpensively build and manage their own private cloud to power big data.

    In a 2012 study of Canadian Oil & Gas businesses with revenue of $100 million+ that regularly use analytics to inform their decision making, 47% of respondents identified operations as one of the top three analytic users, 71% use offline tools such as spreadsheets and only 21% have continuous real-time monitoring and analysis.

    Venture Capitalists are also accelerating investments in the big data space with nearly $5 billion of funding over the past five years according to the VC database CB Insights. And a recent Gartner report states big data will drive $232 billion in IT spending through 2016.

    The bottom line is big data is inherent and imperative to the continued success of O&G and the industry is ripe for data-driven solutions. As more and more O&G companies awaken to its potential, many jobs will be created for data scientists, opening a portal for new applications and ideas to enter the industry.

    The opportunities and capital are plenty – Alberta’s hi-tech entrepreneurs take note!

    Short bio: Lloyed Lobo is a partner at Boast Capital, a technology focused firm with offices in Calgary, Vancouver and Silicon Valley specializing in R&D Tax Credits, early-stage investing, and tech events management.

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