Enriching Field Real-Time Data Reliability via the Implementation of Lean Six Sigma Concept

Abstract

Abstract Nowadays, with the advanced technology, there is a large quantity of real time data that flows from the equipment in the field to the engineers’ desktop. The quality of data is, in most cases, questionable. A high quality data is required to be utilized in production workflows and technical studies. Failure to acquire reliable data will affect the calculations of production parameters, hence impacting the overall understanding of well performance. Therefore, monitoring data reliability and quality is essential. A project was initiated to tackle all various reliability issues for eight fields where a focus team was formulated. The team assessed the current data reliability and facilitated developing the action plans with the use of Lean Six Sigma concept which follows five phases; define, measure, analyze, improve and control. Multiple tools such as fishbone diagram and 5-WHY were used to identify the root causes for having reliability issues along with a correspondent solution (s) which aided developing a detailed implementation plan. The project goal is targeting an increase in overall data reliability in a six-month period. An anticipated increase of 5% to overall data reliability is to be achieved post to the tags deletion and re-mapping campaign. It is worth mentioning that the utilization of production workflows through effective monitoring of wells rate compliance and ESP is associated with remarkable cost saving. Securing high data reliability from various equipment will enable engineers to track the wells’ rates and status at their desktops. Moreover, effective monitoring of ESP performance will help preventing the occurrence of trips and optimize ESP operations in the field. Last but not least, effective data monitoring will ensure the upkeep of the Intelligent Field equipment.