Data is fuel for operational efficiency. Either you manage it properly to help propel your company forward, or you let it flood the engine. Unmanaged data, especially data at the scale generated by Oil & Gas companies, will become an expensive hinderance to progress and innovation. But manage data properly and it can significantly improve operations and lower costs.
Big Data has moved beyond the database to find purpose in upstream, midstream, and downstream Oil & Gas Industry applications. Data and analytics help to advance and refine exploration, environmental assessments, drilling, reservoir engineering, production engineering, refining, transportation, health & safety – along with general marketing and business applications.
As an industry, Oil & Gas faces several challenges including:
- a lack of visibility into complicated operational and supply chain processes
- the management of equipment through its life span
- monitoring and minimizing environmental impact
- meeting compliance and safety regulations
- a dynamic commercial environment created by oil price levels
Data helps tackle each of these challenges. But the sheer amount of data created is in itself a problem for many companies.
Barrels of crude data
The technological evolution in the Oil & Gas Industry, especially with information systems, means petabytes of data are created from all areas of the business. That volume of data can be a nuisance or liability if not treated properly. However, if data is effectively managed, enterprises can transform gigantic datasets into optimal Oil & Gas operations – lowering operating costs, improving productivity, increasing efficiency, advancing innovation, and decreasing risk.
Productivity and precision rule in an industry where a single well can cost tens of millions of dollars, making the cost of error and waste astronomical. Even incremental improvements in efficiency and accuracy can have a substantial economic impact on a company. As the World Economic Forum (WEF) reports, “digitalization has the potential to create around $1 trillion [worth] of value for Oil & Gas firms.”1
Refining with data and analytics
“Bringing analytics to bear on the complexities of shale geology, geophysics, stimulation, and operations to optimize the production process would potentially double the number of effective stages, thereby doubling output per well and cutting the cost of oil in half.”Mark P. Mills, Senior Fellow, Manhattan Institute2
When applied properly, “advanced analytics can yield returns as high as 30-50 times investment within a few months of implementation.” Moreover, they can positively transform fundamental operating models of Oil & Gas production systems.3
For example, by incorporating the Internet of Things (IoT) into offshore equipment, personnel can monitor the life span of machinery, detect and deter equipment breakdown through predictive maintenance, and track elements that can affect production, such as wave heights, temperature, and moisture. This improves operational productivity and the bottom line.
Advanced analytics are driven by machine learning (ML), which uses computing power to identify patterns among thousands of variables in continual conditions. The patterns detect bottlenecks or potential outcomes and recommend action to safeguard optimum operating conditions.
The first step in taking advantage of analytics is to have data that is available, unified, and easily searchable.
Data is fuel for operational efficiency
“Data is the fuel for advanced analytics. The good news is that most Oil & Gas companies have vast volumes of semi-structured data on hand, [but] they are using less than 1% of it.”4 That’s due to the fact that much of that data is siloed – dispersed across devices, employee desktops, and data centers.
To date, industry data has been collected and analyzed principally to improve health & safety and unlock minimal operational efficiencies, such as improving a project’s performance within a defined portfolio for a limited period. As WEF states, “over the decades, concepts such as the digital oilfield have matured, and the ability of piecemeal applications of digital technology to drive a step change in operational performance is approaching its limit.”
How do you break through those limits? With a new cohesive data management approach that takes into consideration the entire life cycle of data, from concept to closeout.
Manage your data from concept to closeout
Early on, Freeport LNG, a future-minded liquified natural gas receiving and regasification terminal, foresaw a need to properly manage and govern the business-critical information it would amass. Project information, engineering drawings, construction documentation, and compliance information – all of it would need to be properly governed from the beginning.
They worked with Shinydocs to create a data management infrastructure using OpenText Content Suite and OpenText Shinydrive for Content Server. The solution keeps their data safe and searchable whether a project is active or closed out.
The Freeport team understood that just because a project ends doesn’t mean the management of that data ends, nor that the value of that data diminishes.
A single capital-intensive project can have thousands of documents. According to one study, project handover can cost $100,000 or more and the effort of 30 full-time employees for one year.4 The costs are even greater when the job is not done effectively.
A gas company spent billions of dollars (yes, billions) to dig up 500 miles of natural gas pipeline, just to measure it and bury it again, so that engineers could re-document information they should have already had access to. Project closeout and handover is just as important as the treatment of data during exploration. The mismanagement of data, no matter where you are on a project, can be costly.
We’ve created an eBook on project closeout in Oil & Gas. It contains a solid strategy to improve data handover, highlights ways to further improve operational efficiency using data, and shows you how to turn your document chaos into a highly valuable asset.
1 World Economic Forum, “Digital Transformation Initiative Oil and Gas Industry.” https://reports.weforum.org/digital-transformation/wp-content/blogs.dir/94/mp/files/pages/files/dti-oil-and-gas-industry-white-paper.pdf
2 Towards Data Science, “Role of Data Analytics in the Oil Industry.” https://towardsdatascience.com/here-is-how-big-data-is-changing-the-oil-industry-13c752e58a5a
3 McKinsey, “Why oil and gas companies must act on analytics.” https://www.mckinsey.com/industries/oil-and-gas/our-insights/why-oil-and-gas-companies-must-act-on-analytics
4 McKinsey, “Why oil and gas companies must act on analytics.” https://www.mckinsey.com/industries/oil-and-gas/our-insights/why-oil-and-gas-companies-must-act-on-analytics