The sheer amount of data in energy companies slows down their digital transformation.
Managing large data sets is complicated, and few industries have larger and more complex data sets than the energy industry.
Data complexity and large investments in on-premises storage solutions and multitudes of computer systems prevent transition to cloud-based sub-surface data management. A single company can have tens of petabytes of structured and unstructured data, which if not quality-assured, can lead to an increase in cost if it goes wrong.
Solutions from RoQC, a Norway based software company, clean up structured data for energy companies. This makes data management more efficient from a time and cost perspective, but also decision-making more reliable.
Through machine learning, our software gives energy companies complete control of their data and assets. When the amounts of data are reduced, we eliminate uncertainty, duplication and optimize the quality of the data sets, explains Bjørn Thorsen, CEO of RoQC.
New possibilities through cooperation
RoQC is a certified independent software vendor with Microsoft. The cooperation has been of great help for RoQC to expand their technology internationally.
Through our new RoQC machine learning solutions, our customers get access to new possibilities on Microsoft’s existing Azure platform. By cooperating with one of the largest platform providers in the world, we gain access to technology, competency, and markets it would otherwise be hard to access, Thorsen explains.
Partner development manager in Microsoft Norway, Ole Christian Smerud, assures the cooperation is mutually beneficial.
As a platform provider, we depend on strong partners to give our customers the best solutions. While we provide a platform, cloud competency and access to an ecosystem for RoQC, they bring domain knowledge and relevance to their industry, says Smerud.
RoQC believes that the energy industry struggles to take the step into the cloud, simply because of the data complexity and that most companies lack control over their data. By qualifying and quantifying data sets, identifying and deleting duplicates, RoQC Tools can reduce the data set size with commensurate dramatic savings in storage costs.
By reducing the amount of data by 10-30 percent, we are talking of millions of dollars in savings. The bigger the organization, the bigger the effect.
RoQC Tools are primarily designed so that data managers can perform tasks that are usually time consuming as efficiently as possible. Very often they can complete a task that usually takes months, in a minute or two. Sometimes, the tasks would not be possible at all without the tools.
There is an obvious and well documented correlation between increasing the quality of your data and reducing the risk on decisions based on that data. Geoscientists and project leaders in this field make decisions worth millions, maybe billions. You don’t want to make a decision of that magnitude based on weak data.
RoQC believes the energy companies’ data is the key to the shift away from fossil resources. In the data sets, subsea energy companies have knowledge of “everything” about the ocean floor and sub-sea.
RoQC provides both tools and consultants to enable a client to prepare their data prior to migrating the data to Azure. This preparation can include everything from simply identifying and removing duplicates to developing and implementing standards then cleaning the data to comply with the standards. These preparations can be done directly in the clients’ normal (eg. Halliburton/Schlumberger ) interpretation platforms.
Furthermore, RoQC’ LogQA provides extremely powerful native, ML based QA and cleanup tools for log data once the data has been migrated to Microsoft’s Oak OSDU environment on Azure.
LogQA is a native Azure, OSDU SaaS that monitors the quality of the well log data that a client has stored in OSDU. LogQA was partially developed in collaboration with Microsoft as part of project Oak Forest. In tight cooperation with project Oak Forest, LogQA is maintained on the latest OSDU API’s and version/schema.
As LogQA is native to the Azure infrastructure there is no customer deployment required before a customer can utilize LogQA to monitor, identify data quality issues and rapidly rectify the data quality issues. LogQA is designed to work with typically Oil Industry client datasets – potentially millions of well logs.
"...traditionally a Petrophysicist might spend a day or two cleaning up the logs for one well before they can be used for detailed analysis... with RoQC LogQA the same Petrophysicist can clean hundreds of thousands of logs in the same timeframe."