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Huawei's Intelligent Exploration and Production (E&P) Cloud solution integrates End-to-End (E2E) cloud data centers through big data and Artificial Intelligence (AI) technologies, providing oil and gas customers with full-stack, intelligent, and dedicated cloud services, plus on-demand subscription to elastic high-performance computing, storage, and deep learning resources. These services and resources enable more efficient seismic processing and interpretation, as well as reservoir simulation, improving refined reservoir research levels.
The solution also allows customers to establish a comprehensive underground cognition and research decision-making system, which accelerates digital transformation while also improving the quality and efficiency of oil and gas enterprises, in turn allowing them to pass on lower oil prices to their customers.
One cloud centrally manages multiple resource pools of different types to provide powerful cloud computing power, improving underground depiction service efficiency by up to 14 times.
The solution enables faster delivery of optimal E&P services, with payment by capacity, lowering both the Total Cost of Ownership (TCO) and Operating Expenditure (OPEX).
The platform fully unleashes the power of data to explore potential associations between reservoir, wellbore, and production parameters, and adopts automatic learning and inference models to enable more efficient and accurate decision-making on reservoir development.
Huawei provides both mature, traditional Information Technology cloud-based migration solutions and diversified, advanced cloud services for enterprises. These solutions and services help customers quickly deploy E&P services on the cloud with effective Operations and Maintenance (O&M).
Powerful cloud computing provides adequate computing power and multiple business data services for seismic processing and reservoir numerical simulation. This significantly improves efficiency of underground solution analogy, and assists decision-making regarding development solutions.