Data Analytics-Enhanced Cloud-Native Computational Reservoir Simulation forAccelerated Oil Prospecting

Abstract

The rise of cloud-native technologies alongside data analytics have revolutionized many fields, notably in how we discover oil and gas. This study unveils an innovative approach leveraging these technological progressions to significantly refine the oil exploration process, dubbed the Enhanced Data Analytics Cloud-Native Computational Reservoir Simulation. My method combines the scalability of cloud-native platforms with sophisticated data analytics for forecasting and modeling subterranean reservoirs. It begins with an exposition on the creation and implementation of my cloud-native computational framework, allowing the dynamic allocation of resources as per the computational needs of reservoir simulation efforts. I demonstrated uses to showcase various interpretations
that can be analyzed. The document elaborates on extensive use scenarios to demonstrate how the discoveries in the article might be applied across different sectors