Future of Seismic Data Management with an Innovative Approach #Seismic, #Cloud
Date & Time
Tuesday, November 10, 2020, 1:30 PM - 2:00 PM
Hilal Mentes

The amount of seismic data that a major oil & gas company acquires or generates grows exponentially every year. New technologies bring to play more advanced datasets such as 4D seismic and OBN. These add value but also data management complexities. Handling massive amounts of unstructured seismic data requires a lot of effort on both the business and the technical side. TOTAL has been using a robust and reliable master database, which helps data admins and users create well-structured seismic data. Mastering seismic data involves creating ready-to-use/synchronized databases which guarantee a centralized and shared reference. This tool also organizes data in Master projects and qualifies the seismic data in order to filter and retrieve it instantaneously on multiple projects. Setting up such a seismic master database enables data admins and IT people to improve data storage strategies as it optimizes disk space and eliminates unnecessary duplicates in various projects. However, the data is still managed on conventional local area network IT systems; cloud-based systems are not employed. That being said, challenges exist with this innovative approach. Big oil & gas operators including TOTAL have already started working on evaluating external initiatives, particularly one which is Open Subsurface Data Platform (OSDU). This cloud solution encompasses all subsurface data and enables users to collaborate and accelerate the implementation of new digital solutions. This may even contribute to data management by developing unsupervised tools using automation and accelerate digital transformation. A big question that needs an answer is if this standardized cloud system would be able to handle a significant amount of seismic data and how would the performance be compared to current systems? Lastly, the oil&gas industry will need to promote new initiatives and evolutions that make use of cloud environments that encompass AI and machine learning solutions to remain competitive.