Data is scattered all throughout, but so is value.
Data is at the center of the digital transformation wave in the oil and gas business. Drilling, exploration, maintenance, and production provide a large amount of data, which was too large to process efficiently until recent times. With changing times, this industry is experiencing significant hurdles. Extraction is costlier, and tapping new reserves, is much more challenging.
Successful oil and gas companies have prioritized data management to combine multiple datasets for sophisticated analytics. They’ve evolved into clever businesses, utilizing a wealth of data, sophisticated analytics tools, and dynamic use cases to set themselves apart. Intelligent companies optimize resource allocation, fine-tune processes, create new business models, and predict future demands.
Why Do Businesses Need to Become Data-driven?
According to Forrester, in addition to being profitable, attracting and retaining new consumers, data-driven firms can expect to achieve an approximately 30% yearly growth rate. Most businesses recognize the importance of data in decision-making; nevertheless, getting from knowing to acting isn’t always easy.
Harnessing data foresight advantageously is a crucial facilitator for reinvention in the energy industry. Besides, the industry needs to concentrate on building more flexible operations to deal with ongoing volatility and cyclicality. This entails establishing a lower and more variable cost structure, relying less on on-site physical assets, and utilizing the supply chain network to assist in absorbing market shocks.
Oil and gas firms that utilize data analytics and related tools like AI, cloud, and IoT can increase their return on capital employed (ROCE) by 15%.
Data Application in Oil and Gas Exploration
Discovering Possibilities
During oil and gas exploration, seismic waves monitor a significant quantity of data utilized to discover new oil reserves. Furthermore, enterprises can study weather, soil, and equipment data to anticipate drilling performance and make informed decisions about drilling locations. This directly influences both cost and revenue.
Identify New Oil Fields
Oil field managers must examine well data, seismic data, while following industry news, and social media. They can also use that information to evaluate oil fields and find the best oil drilling sites. To avail of opportunities, the Big Data platform may be used to examine geographical data and secondary reports.
Oil Production
Analyzing seismic, drilling, and production data to boost oil recovery from existing wells is crucial. This information can assist production engineers in determining when to make modifications to the oil reservoir and when to update their oil lifting methods. Oil output from wells can also be forecast using cloud computing and Big Data approaches.
Maintain Equipment
The oil and gas industry cannot afford poorly maintained machinery and devices. Sensor data from equipment and geological data can be studied to forecast equipment failure. The investigation can help understand what works best in which environment to identify and prevent any probable drilling errors or equipment failures.
Ensure Safety
To ensure the safety of the workforce, property, and equipment, oil and gas businesses must spot events or trends that could suggest a security threat or cyber-terrorist attack. Predictive analytics is a critical component of discovering patterns that can aid in the early detection of these risks. The Big Data platform can spot hazards through machine learning and anomaly detection techniques in real-time.
Connect with an expert from MOURI Tech to discover how to do more with your upstream oil and gas data, as well as the critical KPIs and data management best practices that your oil and gas organization should consider.
