The Intelligent Data Quality Improver


Industries are facing challenges in the handling of ever-increasing quantities of data; the upstream Oil and Gas sector in particular is severely affected by this “data deluge” challenge and is at risk of failing to extract enough information from the most potentially valuable assets they actually own, namely exploration and production data.

So far, numerical data cleaning and curation have been considered as synonyms for numerical data quality improvement, but the latter is much more than simply addressing gaps, outliers, noise and bias in numerical datasets typically composed of time series of some kind.

HyperDap has launched the IDQI project as a joint funding initiative between the Company, OGIC and The Data Lab to addresses the issue of digital exploration and production data quality in the Oil and Gas industry. IDQI builds on top of novel data quality improvement knowledge and technologies devised by Hyperdap.

The guidance and expertise of project investigators from Computing Science at University of Aberdeen (UK) in AI, data science and numerical data analysis and interpretation brings a high technical and academic research standard to the project.


Our project sponsors



Supports and funds innovation in the Oil&Gas industry


The Data Lab

Scotland’s innovation centre for data and AI


Our project collaborator

University of Aberdeen (UK)


Prof. Wamberto Vasconcelos, Computing Science

Academic investigators

Dr. Ernesto Compatangelo, Computing Science