1887

Abstract

Summary

The upstream oil and gas industry is accelerating digital transformation with the creation of a cross-discipline cloud-based platform that will break down existing data silos. This wil make it possible to capitalize on the full potential of analytics, AI and ML to improve the quality of decisions based on a broader use of data. However, the process to migrate, vet and correctly reference the vast amounts of existing and new data is not receiving the same attention. Without standardized data and the resolution of multiple versions of data that currently abound across organizations into a single version of truth, automated processes will not perform reliably, which will impact the validity of analytics and other technologies in pursuit of reliable decisions.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202011760
2020-12-08
2022-05-18
Loading full text...

Full text loading...

References

  1. Gidh, Y., Deeks, N., Grovik, L. O., Johnson, D., Arumugam, S., Schey, J., & Hollingsworth, J.
    [2016] WITSML v2.0: Paving the Way for Big Data Analytics Through Improved Data Assurance and Data Organization.2016 SPE Annual Technical Conference and Exhibition Paper. SPE-181096-MS
    [Google Scholar]
  2. Morandini, F., Rainaud, J.-F., Poudret, M., Perrin, M., Verney, P., Basier, F., Ursem, R., Hollingsworth, J., Marcotte, D.
    [2017] RESQML Version 2.0.1 Makes it Easier to Update a Reservoir Model. 2017SPE Annual Technical Conference and Exhibition Paper. SPE-185761-MS
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.202011760
Loading
/content/papers/10.3997/2214-4609.202011760
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error