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Petroleum exploration geotechnical disciplines have a documented history of utilizing well managed and curated data to shorten project cycle times, reduce operational risk, and deliver higher quality data driven decisions that optimize asset productivity. Recent initiatives to provide open-source platforms for data visualization and interpretation on the cloud have also made those data sets available to new groups in exploration, as geotechnical experts are re-tasked with exploring for new opportunities in sustainable resources. Recent case studies show that existing optimum industry best practices for cloud ingestion, enrichment and consumption of digital datasets can be applied to support strategic choices in asset selection and development for sustainable energy resources. The lessons learned from applying principles for making cloud data findable, accessible, interoperable and re-usable are enabling embedded data workflow processes and procedures that deliver value in the area of hydrogen exploration and storage, geothermal, and carbon sequestration projects. The value of digital data in reducing decision latency is easier to measure as monitoring of cloud data storage and delivery metrics becomes more visible. Large digital transformation projects have also led to more executive level representation for digital data managers and their support of data driven decision making in the resource sector. Experience with using digital datasets on the cloud for predictive modelling under uncertainty is being used to evaluate the data necessary to execute strategic selection of sustainable assets, and geoengineering data sets from instrumented facilities are available to enable real-time optimization of existing processing workflows to make them more sustainable. The re-usability of cloud-based data visualization code means that existing geotechnical data sets can be effectively managed by current technologies and resources, leading to shorter cycle times for return on investment.
Open-Access Online Publication: May 29, 2023
Energy Transition, Open Data Platforms, Data Management
Energy Transition, Open Data Platforms, Data Management
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