Big Data Analytics in Petrochem

Over the last two decades, this technology has, for a number of reasons, gained rapid popularity in business and industry. Not only does data analytics provide companies with valuable insights into existing processes, but - when combined with things like machine learning - it helps them to make predictions about future performance and even suggests opportunities for market expansion and the elimination of inefficiencies. 

Given how much data companies in the oil and gas industry collect, it is only natural that big data analytics have become an essential component of the petrochemical IT toolbox. By focussing on data, industry players are discovering new opportunities to generate revenue, grow their businesses, and bypass previously insurmountable obstacles. 

Fundamentally, digital transformation for this industry exists at the intersection of Big Data and ML. In today's blog post, we would like to spend just a little time exploring what this means. 

Data-Driven Approaches to Oil and Gas
AI- and ML- powered analytics strategies have been enabling companies in the oil and gas industry to discover and interpret powerful patterns and insights from data since even before the start of this century. Over the course of these last two decades, a number of promising use cases for the technology have been developed and have had time to reach operational maturity. Some have even reached near-universal adoption.

Streamlined exploration 
Most of the big players in oil and gas, including Chevron, BP, and Shell, have launched pilot projects using big data analytics to aid in the exploration phase. Historical drilling data, as well as seismic and geospatial records, for example, can be analysed by geologists to verify their assumptions. This saves companies both time and money, as they do not need to invest in any kind of initial drilling operations or bureaucratic complexities in areas under the jurisdiction of environmental protection authorities.

Improved drilling 
During the drilling process, telematics and IoT devices can be installed to collect information relating to a wide range of data points. This data can be delivered to companies in real time and analysed in order to optimise the drilling procedure, as well as to anticipate issues that could arise. Through this kind of big data analytics, companies can increase productivity while enhancing drilling accuracy and reducing risk of technical or equipment failure. This strategy also helps to enhance worker safety.

Reservoir management
Data collection and analytics ensure the better identification of oil reserves and increase the chances of success for turning a reservoir into a production well. Like with the earlier phases of exploration, subsurface and historical data can be analysed and predictions can be made about how the oil can be best extracted. 

Pipelines and logistics
The process by which oil and gas is transported is extremely complex and requires that companies determine the transportation method that involves the least possible risk. Data collected using sensors in pipelines, holding tanks, rail tank cars, tank trucks, and pumping stations, provides an opportunity to apply analytics algorithms and determine the safest possible means by which to move resources long distances. 

Predictive maintenance
Data collected from sensors installed in any piece of equipment along the oil and gas value chain can be analysed to detect possible issues with material integrity and readiness to changing weather conditions. Based on this information, maintenance teams can be deployed to repair any abnormality before disaster ever arises. 

Refinery optimisation 
Predictive can also be used by companies that operate downstream to improve pricing, reduce financial risk, and comply with environmental and safety regulations. In order to control expenses, companies can use data to become aware of predicted changes in oil prices and control the level of output. They can monitor their equipment in real time to ensure that accidents do not occur. 

Staying Up to Date
Big data analytics is a field that is constantly changing. Major technologies, like Apache Hadoop, MongoDB, and Cassandra are constantly being updated and new innovations come along on a regular basis. Languages and processing tools like R, Datameer, and BigSheets are essential to the process, and require a high degree of expertise. 

Buxill IT LTD is a company that specialises in providing digital technology and IT excellence to the oil and gas industry. Our big data team has not only mastered all of the above technologies, but is highly skilled at building analytics solutions that fit the particular needs of all sectors of petrochem. We have a strong devotion to digital transformation and futureproofing: Not only can we optimise your company's existing systems, but we can help ensure that your business stays ahead of the competition through regular technological updates.

We would be glad to schedule a free consultation to discuss your company's next steps towards digital transformation. Please feel free to contact us. We will get back to you as soon as possible.