Digital Petroleum: Perspectives of Industry Big Data Integration and Automation - Managing Non-renewable and Renewable Energy Sources

In oil and gas industries, operational digital solutions are challenging because of spatially extended large-size installations and the criticality of implementation solutions in business contexts, where rising global demand for energy needs is stirring. Other challenges include using obsolete tools and technology, time-consuming digital makeovers, inflexible data systems for decision support, low levels of digital maturity, and interoperable supply chain articulations between petroleum companies. To meet the demands of digital petroleum, we construct five-layer digital data models for better integration and automation in energy industries. The research aims to develop five primary platforms, a uniform transmission network, even repository systems, sensor technology, ontology interchange language (OIL) and application layer in the digital petroleum field model. An Industrial Ethernet is proposed based on a network transmission platform for the exploration industry. The network platform is an information superhighway to gather and integrate the existing automation sub-systems, di information and provide standard interfaces for future sub-systems. Sensor technology is dependable for data acquisition qualities. The OIL layer supports the digital petroleum to interchange the petroleum Big Data and their ontology descriptions into executable computing languages. Each layer gathers information, integrates ontology-driven data in a warehouse environment, and transmits data to different petroleum industry units. Uniform hardware and software platforms of distributed networks and their data structures improve petroleum resource management. Cloud-based onshore and offshore digital petroleum entities can connect petroleum-bearing basins, including sub-basins and share information in industrial automation projects. Data geoscience emerges as a digital analytics tool, irrespective of conventional or unconventional energy sources. Future energy relies on renewable sources in pollution-free environments, and the digital model is extendable in industries where industry integration and automation are required. We conceptualise the five-layer digital energy model as a digital solution development in unconventional energy industries, extending its articulations in green energy automation.
Open-Access Online Publication: May 22, 2023