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Informative Article | Data & Knowledge Engineering | India | Volume 12 Issue 11, November 2023 | Rating: 5 / 10
A Data Mesh-Driven Data Lake Architecture for Oil Field Data Consolidation
Abstract: The proliferation of distributed data sources and specialized applications across different oil field operations has led to data silos and integration challenges. This hamper discovering insights across disconnected datasets. To consolidate the vast data landscape, traditional centralized approaches prove inadequate. I propose a decentralized data lake architecture aligned with data mesh principles for oil data consolidation. Self-service data infrastructure is provisioned through reusable data products that encapsulate domain-specific datasets with relevant policies and tooling. This encapsulation aids discoverability and access. Standardized interfaces between the data products using a domain ontology and catalog facilitate consolidation at scale while distributing data governance. My reference architecture deploys on AWS leveraging analytics services like Redshift, Athena, and SageMaker. The mesh of domain data products provides scalable data consolidation and governance while accelerating analytics velocity through easier findability, accessibility, and understandability of datasets. I demonstrate applicability across key use cases like production optimization, drilling plan analysis, and equipment failure prediction for an oil field. This decentralized governance approach unlocks value from distributed data while retaining organizational flexibility and autonomy.
Keywords: Data mesh, data lake, data consolidation, data governance, decentralized architecture, domain-oriented design, self-service analytics, data discoverability, data accessibility, data understandability, oil and gas industry, exploration and production data, seismic data, well logs, sensor data, data interoperability, data silos, knowledge graphs, ontologies, reference architecture, AWS cloud, Amazon Redshift, Amazon Athena, Amazon SageMaker
Edition: Volume 12 Issue 11, November 2023,
Pages: 2151 - 2157