| Abstract Title: | Harnessing Big Data Approaches and AI in the Hydrocarbon Processing Industry |
| Abstract Type: | Oral |
| Session Choice: | Other |
| Presenter Name: | Dr Brian Rohrback |
| Company/Organisation: | Infometrix |
| Country: | United States |
Abstract Information :
The term Big Data implies a systematic approach to extracting the information content from multiple, byte-dense raw and meta data sources. Effective extraction of this information leads to improvements in decision making at all levels of the petroleum and petrochemical industries. To accomplish anything in the Big Data space, we need to combine traditional approaches in statistics, database organization, pattern recognition, and chemometrics with some newer concepts tied to better understanding of data mining, neurocomputing, and machine learning. In order for industry to release the improvements that this form of AI promises, we need to address the issues of data silos, security concerns, and the danger that we might be only partly-right in the answers we attain. Guidance from our knowledge of process systems and the underlying chemistry is critical to success in the Big Data world.
