The global oil and gas industry is constantly facing strategic challenges to prevail in an uncertain and volatile environment. The most significant of these challenges are optimal pre-construction and project planning; and building elaborate pipeline systems based on a blueprint, engineering skills, and vendor relationships.
Although predictive analytics has only emerged over the last decade, its ability to leverage data to forecast or predict outcomes based on several factors is quickly evolving as the “next big thing” in the oil and gas industry. With rising costs and diminishing natural resources, it is crucial that crude oil drilling must take place in geographical locations that can provide the most significant rewards. Major oil and gas companies are now collecting data that allows them to predict the anticipated size of natural resources by monitoring low-frequency seismic waves below the surface, thereby reducing unnecessary costs and eliminate inefficiencies. With the ability to optimally capture, monitor, store, and interpret large volumes of data, Quantzig’s predictive analytics solutions help identify natural reserves and optimize both upstream and downstream activities.
Leading oil and gas enterprises are using predictive analytics to drive better outcomes using data-driven insights. Now it is your turn to leverage advanced predictive analytics to improve business efficiency and drive better results in the oil and gas sector. Request a free proposal today.
The client is a petroleum company headquartered in UAE and engages in both upstream and downstream activities like exploration, production, refining, transportation, and storage. The client’s operations are directly linked with state planning agencies, regulatory authorities, and policy-making bodies. It is one of the largest oil ad gas companies in the world.
The Business Challenge
Even though pipeline designs rely on pre-existing data, supply prices, and other market factors, while building, they often cross assigned budgets. The client wanted to create a more accurate, predictive analytics-driven budgeting process.
Predictive modeling in the energy sector assists in streamlining operations, such as exploration, drilling, filtration, and delivery. Request for a complimentary pilot to learn how we can help you achieve the strategic objectives most important to your organization.
To ensure safety in transporting oil, the client wanted to create a safe logistics system that detects faults in pipelines and tankers, such as fatigue cracks, stress corrosion, and seismic ground movements, and reduces risks and hazards.
Operating in downstream and upstream sectors, the client generated a significant amount of data from unstructured sensors. The client identified the need to gain actionable insights from these unstructured data sets. They approached Quantzg to leverage its predictive analytics solutions to gain insights from data for faster and better decision-making.
Speak with our predictive analytics experts to learn how we help oil and gas companies to predict demand fluctuations, gauge the impact of ill-performing assets, and determine the cost of maintenance using decision science and data-driven insights.
Quantzig’s subject matter experts (SMEs) leveraged predictive analytics to empower the client with powerful insights that combined performance optimization and dynamic simulation capabilities that enabled them to enhance decision making and drive better outcomes.
Quantzig’s SMEs also helped the client derive a forecast system capable of delivering accurate outcomes to allot accurate budgets for all their processes. No longer reliant on pre-existing data and supply prices, the client was able to use historical and existing project utilization data to forecast the budget accurately.
Through advanced data and predictive analytics techniques, the client analyzed sensor data from tankers and pipelines for detecting anomalies with stress corrosion, fatigue cracks, seismic ground movements, and more, which helped prevent the client massive accidents and avoid risks and hazards.
The use of predictive analytics enabled the client to create transparent, interlinked processes and systems that seamlessly communicated and exchanged data with one another. This enabled them to make more accurate, data-driven decisions, pre-empt bottlenecks, optimize processes, and eliminate costly inefficiencies with ease.
The key business outcomes of this collaboration were –
- Better risk management through accelerated decision-making
- Accurate budget forecasting for upcoming projects
- 15% reduction in operational costs in three months
- Improved logistics processes and reduced oil spiling accidents
- Standardization of operations data and enhanced organizational data security
Wondering how to leverage predictive analytics for your complex business problem? Request for more information today.