Big Data has been described in the past as sharing similarities with unrefined crude oil, as it possesses raw wealth but requires refining to really unlock its immense value.
Given the nature of the industry itself, vast amounts of raw data have been captured throughout the extraction and production processes, so it is just a matter of manipulating these assets in an intelligent way. Without actually using this data while carrying out exploration duties, personnel performance visibility, increased detection of oil reservoirs, accurate 3D models of deep-sea structures, and machine and equipment health are just a few benefits that have already been begun to take shape.
Wells below the surface can be modeled with high accuracy with all the geological data that has been collected, illustrating the behaviors being displayed such as pressure and flow rates, and temperatures. This data needs to be manipulated in quicker and more intelligent ways.
Low oil prices and external forces such as electric vehicles happen to be speeding up the need to implement new advancing technologies for the oil and gas industry. Without generating more revenue from production, this leaves little room to make profitable gains, so companies must look elsewhere, and that is by making the product with less by increasing operational efficiency and making production more cost-effective.
Many O&G assets could gain huge benefits from optimization through data use. For example, the performance of drilling techniques and practices can be monitored and automatically enhanced with an AI system being fed captured real-time data from the sensors. The supply-chain manager for an onshore facility will receive instantaneous notifications when their deliveries of much-needed parts arrive. Logistical teams can make better, quicker decisions using high-quality and highly accurate data when informing offshore plants of the estimated time of arrival for the replacement drill components.
With increasing volumes of captured data, many industry operators are seizing the opportunity and investing widely in numerous data-driven solutions, primarily with the aim of processing and refining unstructured and structured data, while removing the barriers between different silos that store this information.
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