By Emmanuel Udeh, Subsurface Data Analyst at Shell.
The question in 2016 for every oil industry expert is: how soon will oil prices rebound from their current level? The factors that have contributed to the current supply glut and a bleak market outlook are expected to remain the norm for some time. For example, the US Energy Information Administration is forecasting prices of still below $50 in 2017 (see: https://www.eia.gov/forecasts/steo/report/prices.cfm). How will the industry manage the crisis?
Upstream operators are responding by streamlining their portfolios and operations, seeking resilience in every aspect of their business. Although Exploration & Production (E&P) data is referred to as an asset, it is not yet leveraged as well as data in other industries, such as Finance and Healthcare. Data management can be an opportunity to help a company survive the downturn and even thrive.
As oil prices plunge to new lows, the industry needs to improve the efficiency of its operations and reach ever higher levels of productivity. Data management can help in making business processes more efficient by implementing a range of activities.
1. Measure the impact of data management on productivity
Many E&P organizations are currently focused on containing and reducing costs. One simple way data management can show the business how much value it adds in terms of man hour opportunity cost is by using surveys to gauge the efficacy and value of supporting business processes. For example, over time surveys can measure how much staff productivity has improved by asking end users targeted questions such as, “how much time do you spend looking for data?”.
Surveys have shown that the effective implementation of a data management strategy in an upstream business can improve staff productivity by as much as 80%. This is achieved by simply reducing the time required by staff to search and rework their data to 20%. Translated into tangible man-hour cost savings, this can be used to make a case to the management for continued investment in data management initiatives.
2. Identify how data management can help with the challenges faced by the business
Another way to demonstrate value is by identifying the business’s key performance indicators (KPIs) and help to tackle them from a data management perspective.
As already discussed above, improving the productivity of petroleum engineers by reducing the time they spend accessing data is one way of adding value to business processes. In the current bid to drive down costs while maintaining operating efficiency, adopting a smart data management strategy together with analytics can be beneficial. Many oil and gas companies can address specific challenges, such as production optimization, by implementing a clear data acquisition plan. Or they can drive down costs by the application of predictive maintenance on facilities and equipment, thereby reducing downtime and its associated losses.
A study by the US Department of Energy shows that predictive maintenance can reduce costs by up to 30% and eliminate breakdowns by up to 70%. This huge cost saving shows how data management and analytics can add value in a low oil price regime.
3. Improve the way we manage data: What do we keep doing, what do we change?
Every business strategy needs to be constantly reviewed to properly assess what works and what needs to be changed. As part of an effective plan to achieve operational efficiency and present a clear vision for data management, initiating a comprehensive review will help to:
Incorporate data standardization and integration, thereby identifying, managing and ultimately reducing the issue of data silos. Data silos are especially inherent in the oil and gas business, leading to a proliferation of data types and proprietary applications to manage them. Standardization and integration are value drivers which help to increase business intelligence, reduce costs and improve productivity.
Create value by enhancing data visualization and analytical capabilities. Recent progress in technology has made data visualization a key enabler in unlocking the value of the data acquired across the business. Data visualization and analytics can solve the problem of integration by turning those sheer volumes of disparate data into information that will enable the business to make faster and more accurate decisions. Booz Allen Hamilton believes that big data analytics can aid a 6-8% boost in production from data driven oilfields. They also calculate a 13% increase in facility uptime in offshore environments. Potentially, E&P companies can save up to US$1bn annually.
To conclude, a big issue facing the industry currently is the impact of lower prices over an extended period of time on workforce headcount. As core talent are being rightsized or downsized across the industry, companies will have to ensure that data management is kept in the hands of data managers not geoscientists. This is because the man-hour costs associated with using geoscientists to manage data will not only affect productivity, but also erode any cost efficiencies gained from reductions in headcount.
An effective data management program will create an integrated working ecosystem. All units will function as one, having trusted data at their fingertips at all times. And they will also work as if all data exists in a central repository, improving productivity and operational efficiency.
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