Data Core

In geotechnical engineering, the challenge is often not a lack of data, but the ability to find, access, and integrate it across workflows. This is particularly evident in offshore projects, where ground models depend on combining seismic data (2D and 3D) with large volumes of in-situ geotechnical measurements and laboratory results.

Field Manager is a cloud-based platform that supports the full lifecycle of geotechnical survey data, from collection and quality assurance to visualization. In this talk, we present recently developed data structures and workflows for linking geotechnical data (0D/1D) with spatial references to seismic data (2D and 3D), enabling these datasets to be explored and interpreted in context. The focus is on the design and implementation of the underlying data model, and on how to balance flexibility and structure when building systems for complex, multi-source data.

Effective subsurface data management plays a critical role in optimizing resources and supporting informed decisionmaking in geoscience operations. This study demonstrates a collaborative effort between Cegal and an upstream SEA NOC's innovation team to enhance data integrity and operational efficiency within the subsurface projects environment through the deployment of Blueback Project Tracker.

The initiative begins with a comprehensive evaluation of the existing data landscape, systematically identifying corrupt datasets, obsolete files, and coordinate reference system (CRS) inconsistencies across an extensive portfolio. During the initial phase, more than 5,000 subsurface projects spanning multiple software versions from 2007 to 2024 were assessed. This thorough inventory established the foundation for targeted data optimization activities.

A key focus involves addressing data duplication across well, interpretation, and seismic datasets. By implementing globally unique identifiers (GUIDs) and MD5 hashcode methodologies, redundant data entries were efficiently detected and eliminated. This systematic approach enhanced data integrity while achieving potential storage reduction of approximately 18 TB, significantly improving operational efficiency.

To sustain ongoing improvements, robust monitoring mechanisms were established to track project performance and data quality over time. A critical outcome of this continuous improvement process is maintaining a clean data environment, which enables the establishment of stronger governance protocols.

The results emphasize the value of modern data management methodologies in rationalizing subsurface data, maximizing operational efficiency, and reducing costs. This initiative demonstrates how structured approaches to data governance, combined with appropriate technological solutions, can transform geoscience data environments and support sustainable knowledge management practices.