Such was a major takeaway from a reader survey conducted by the Oil & Gas Journal (OGJ) on behalf of IT outsourcing firm Wipro back in 2011. OGJ researchers attribute the difficulties to several factors, which live on today.
First, analytics are hard to produce given the first-state condition of data coming into exploration and production organizations, the study found. More than half (56 percent) of survey respondents said they felt that most of their companies' "high-end" consumers of upstream data spend 21 percent or more of their time looking for, accessing, cleaning, or preparing data. That's roughly every employee's use of one work week out of every four each month prepping data.
Second, virtually none of the respondents indicated that their data needs were being met entirely within their functional area or discipline. This, researchers said, indicates that confidence (or lack thereof!) could be a concern for those wanting to pin big changes to a set of analytics. In fact, three fourths of the 190 respondents said that a lack of overall data quality and trust in data has a high or medium impact on their organization. And, two thirds said the inability to integrate "important" data effectively had a high or medium impact as well.
Researchers concluded that the upstream oil-and-gas industry needs to embrace data governance. With data governance should come the adoption of industry data standards and processes; the ability to communicate the benefits of data standards across the organization; the appointment of data stewards to improve data quality and reliability; the momentum that can be created throughout an organization with sound data management.
Other industry watchers have come to the same conclusion.
For example, IBM business analysts Sunil Soares and Arik Kristensen delivered a presentation at a September 2011 conference in Norway that emphasized the impacts of bad data on an exploration and production (upstream) business. Bad underground data -- like incorrect geospatial coordinates -- might affect the driller's ability to drill at an exact location of an abandoned well, they said. Companies might be able to prevent production losses, or even catastrophic spills and accidents, if equipment is appropriately and preventively maintained according to a scheduled regime informed by data governance and analytics, they asserted. On the positive side, Soares said initiatives to analyze geospatial and seismic data can discover new reserves, extend the life of existing reservoirs, and maximize production.
The promise of fixing their data problems, and boosting the computing power that can address other energy sector challenges, is not lost on the major oil producers.
A few years back, BP Exploration and Production's COO Doug Suttle boasted in an IDC Energy Insights whitepaper that the company increased the recovery factor from 40 percent to 60 percent in the Prudhoe Bay Field by integrating real-time field performance data with predictive tools.
The Wall Street Journal recently reported how Royal Dutch Schell created the Technical and Competitive Information Technology (TaCIT) group within its organization to revamp its infrastructure for the advent of big-data. The TaCIT team is deploying a wide range of new technologies that revolve around the fundamental belief that better data analytics can address oil industry problems.
For example, the article noted that the TaCIT team is deploying new seismic sensors linked to new interpretative software and visual applications, with the goal of making the information more widely available throughout the organization. The one million new seismic sensors create datasets that size up to 10 petabytes, 100 times larger than those currently in use. The algorithms and interpretive software that's analyzing the data has already found 150 million barrels of oil located under subsurface structures. For a company that lives and dies by calculations of its reserves, the search for new resources using all data and analytical means possible is an existential proposition, the WSJ reported.
With the supermajors lead, the oil-and-gas exploration industry will likely be paying much more attention to data governance and the analytics they can produce.
Does your organization have a data governance strategy in place? If so, what best-practices might you pass along to the oil-and-gas industry?