Paper SPE 181076, presented at the SPE Intelligent Energy International Conference and Exhibition, Aberdeen, Scotland, UK, September 6–8, 2016.
Multiple literature studies have indicated that a significant amount of data collected during drilling operations is unreliable. To move towards better data quality, two critical hurdles need to be overcome. First, the case for the value of good data needs to be made, so that resources can be allocated towards improving data quality. Second, a process needs to be established within the operator company to measure and improve the quality of data. This paper is a case study in addressing these challengesMultiple literature studies have indicated that significant amounts of data collected during drilling operations is unreliable. To move towards better data quality, the economic case for the value of good data needs to be made and a process established within operating companies to measure and improve the quality of data. In this work, we focus on eight core surface sensor measurements essential to drilling operations and attempt to assess and improve their quality. The goal is to establish a data quality improvement loop that continually accesses data, identifies issues, and implements corrective actions. This paper explains this process and how it has been applied to improve the quality of drilling data.