Reducing Human Error Through Automatic Kick Detection, Space Out and Dynamic Well Monitoring

Abstract

Influx detection and well control are critical situations where the traditional human reaction has been the accepted standard for years. This paper discusses the results of the driller stress tests and the implementation of a system to assist the operator in kick detection, space out and preparation for well shut in. The system implements dynamic well monitoring to reduce the risk of false alarms. The objective is to prove how automation helps mitigate human factors. A stress analysis test was conducted on a variety of experienced drillers to identify the specific operations with the highest risk factors influenced by operator stress. Once the target operations were identified, an automation algorithm was designed and tested to mitigate the human factor during these specific instances. The resulting system detects drilling kicks and automatically performs the space out operation. Dynamic trip and active tank monitoring were implemented to reduce false alarms. This provides the driller with an assistant for tripping operations. The package can be adapted to any type of rigs or blow out preventer (BOP) stacks without requiring additional hardware. Testing was conducted in both simulated and real-life situations, during tripping and drilling operations. The system was able to predict tool joint positions in the well with a mean error consistently below 1%. The automation of the space out operation allowed the system to perform the operation in significantly shorter times and with higher accuracy, eliminating the risk of any tool joint being placed across BOP elements. During tripping operations, dynamic tank tracking effectively eliminated risks of kicks helping the driller keep a constant and adequate filling of the well. Finally, a comparison of the operator stress levels with and without the use of the automation package shows the positive impact such a system can have on situational awareness and concentration. The plug and play aspect of the system proved critical for easy and fast implementation, as well as ensuring a quick familiarization of the driller with the different functionalities. The tests also highlighted the importance of accurate and high-resolution sensors to ensure optimal working conditions. Automation in the field of well control is a relatively new subject. This paper showcases the impacts this type of systems can have on operations and proposes an implementation method to profit from automation while minimizing its impact on critical operations. The field implementation showed how different sensor configurations can lead to different degrees of automation and, thus, different impacts on the operations.

Automated Data Quality Control System in Health and Demographic Surveillance System

“…The objective is to determine the proportion of data points whose values fall within the permitted range. The validity of data 𝑉 can be defined by 𝑉 = 𝑙 ≤ 𝑥 ≤ 𝑢 (4) Where 𝑙 is the lowest expected value and 𝑢 the highest expected value with 𝑥 being the actual date value stored in the database.…”

“…Exponential technological advancements have enabled groundbreaking developments in data automation processes [1], [2], [3], fundamentally transforming the way enterprises administer data quality. Automation substantially reduces the likelihood of errors, inconsistencies, and inaccuracies in datasets by mechanizing the conventional labor intensive procedures of data cleansing and validation [4], [5]. With the ongoing adoption of digital transformation by organizations, the incorporation of automation technology improves operational efficiency, but also creates opportunities for development and innovation in many sectors.…”