The oil and gas industry is important to the global economy. As per OPEC, Oil demand is expected to rise by an average of 1.4 p% per year, and to make up around 36.5% of the world energy mix by 2030. 

The oil and gas industry have lacked capabilities to operate assets in maximum capacity and lacked analytics tools. Part of their operations is collecting data, storage, data analysis, interpretation, or utilizing data. The Oil and Gas industry utilizes data not only for operational activities but to assess core resources and derive value out of them. The importance of data capturing and analysis will steer enhanced efforts, better oil recovery, drilling precision, project delivery, and timely maintenance of machines. Efficient data analytics can establish real-time analytics to support and improve operations in the oil and gas industry.

Oil and Gas has a $200 billion performance gap

The continuous falling prices of oil have initiated a rush to improve the O&G process effectiveness. Investment in  data analytics and analytics technologies help to capture information to improve operations. Operators were able to strengthen process efficiencies and enhance production rates. But this is not enough to hit the production potential of their resources. As per the McKinsey report that there is a shortfall of 10 barrels per day or US$200 billion in annual earnings. Analytics have the potential to improve this in a large way as the conventional methods have shortfalls.

Conventional control systems, tools, and training fall short

The operational complications in production and processing facilities are key sources of O&G efficiency gaps. Control room operators working at huge data centers and around 30,000 sensors continuously feed data into this hub from the subsea, bottom hole, and top sea apparatus. Analytics tools and technologies can help optimize and streamline processes.

Advanced data analytics can bridge the performance gap

Advanced data analytics will help to increase performance rates. Current robust tools use modern engineering, data science, and computing solutions to optimize complex production issues. These methods will not uproot conventional working models but will complement a better understanding of O&G asset operations to improve performance gaps. 

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Advanced data analytics work efficiently and use machine learning, statistical data analysis, computing power to manage different variables continuously and are key to advanced analytics. The analyzed pattern is crucial to establish algorithms, improved production, quality, and productivity. 

Advanced data analytics help to analyze critical production parameters, efficiency, and quality, and alert operators to future conditions. These help for faster and effective responses. It helps to identify issues and recommend prescriptive actions for optimal operations. Let us look at some examples of analytics used for offshore work.

Advanced data analytics at work offshore

Advanced data analytics is still in a nascent stage in the O&G industry. Some insights below.

• Companies steered advance data analytics on a developed, semi-submersible, production deck. We have examples of a production deck running at 95 percent production capacity. Advance data analytics helped to optimize the production output. 
• Data scientists handled three years of hundreds of gigabyte data sourced from 5,000 sensors and controls to understand the factors to improve production. Machine learning algorithm was used to scan data for connections and revenue loss. 
• Analytics helped to identify the human shortcoming to increase production as out of 200 available controls only 50 controls were found to be useful. 
• Analytics also helped to tackle high water content in the oil for environmental reasons by formulating efficient actions. Developed algorithm deferred such events before providing operators enough time to avert those to enhance production. 
• Advanced data analytics algorithms helped to develop predictive maintenance of critical equipment used in production during downtime. Downtime generates huge revenue loss and advanced analytics increased production by 0.2 to 0.5 percent in a few cases.  

We can see a lot of benefits by using advanced data analytics at offshore. However, we need to keep a few aspects in mind to derive maximum benefits.

Five requisites for exploiting advanced data analytics

Five elements essential to O&G companies to discover increased production are 

• Data availability: Data is key for advanced data analytics. Studies suggest that most of the O&G companies use only 1 % of the available informal data. 
• Analytics infrastructure: The availability of efficient computational tools and power provides solutions for predictive maintenance for O&G companies. 
• Analytics skills and capabilities: Developing an internal data capacity is one of the initial works of any O&G company to utilize Advance data Analytics. Then a trained data scientist would help to set up a center of excellence to develop, train, and implement advance data analytics for others to utilize. Secondly, companies would convert business challenges to analytic problems and derive an actionable solution to overcome production issues. 
• Redesigned work and governance: To improve efficiency O&G companies must redesign the work process to take full advantage of data analytics.  There should reconsider the interaction between production optimization and resources located at the deck. Analytics would identify bottlenecks to enhance production and reduce inefficiencies. 
• Business-driven agility: O&G companies should initiate brief, short projects to establish production gains. Using these short projects as pointers, companies can devise analytics to transform the operating process for better business values. 

Oil and gas organization of the future

In the coming few years advanced data analytics can help to establish fully functional independent systems developed for complex production facilities. In the next 10 years, processing facilities will function differently. Industry experts realized that data analytics will work better if the companies considerably change the way they operate their resources and assets. Centralized controlling of production facilities and running of daily operations through machine learning system would bring a definite change in production rates. The front-runner company that will implement these methods and processes will lead the O&G companies in the future. 

What is the role of Data Analysis

Data analysis is a component of data analytics that is significant for this industry. Data analysis in simple terms is a process of a reorganising data – cleaning, analysing, evaluating and interpreting data to present in a manner that helps understand what is going on. Data analysis leads to smarter decision making as management is now likely to understand the occurring events. 

Considering the scope of the operations of this industry, data analysis is a key component in determining actions taken based on smart decisions that will lead to eventual success.

Diamond Professional consultants have immense experience in implementing Advance data analytics in the Oil & Gas industry.

Talk to us on how we can help your organization with latest analytics tools and technologies.

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