Reengineering of geological and production databases for optimized data analytics performance

Data-driven applications that are used as the main tool for data analysis and visualization as well as monitoring, optimizing and improving of wells working regime, faces significant issues related to the theirs overall performance. The architecture of database influence on the performance of data-driven application and on user experience. The authors of the work encountered this problem when developing “Digital Sand Control platform“ (Di.S.Co.) (Naugolnov, Nikolić, 2023) Initial assessments pointed to prolonged data retrieval times, often between 30 and 150 seconds, low data quality, and scalability issues as the primary culprits hindering user experience. Users faced delays when applying basic filters, which led to slow rendering of charts and analytical results. Furthermore, a significant increase in downtime was noted. In response to significant performance issues in the developed application, characterized by excessive refresh and computing times, a comprehensive overhaul of database infrastructure was embarked upon. This paper outlines the steps that were taken to address these issues, the methodologies employed, and the resulting improvements in database performance and data integrity.