Deploying Dynamic Trend-Based Monitoring System to Deliver Real Time Drilling Decision

Abstract

Significant technical challenges are prominent in today's oil and gas drilling operations, especially in remote locations with increasingly difficult geological settings. Stuck pipe incidents have become a major operational challenge, with events typically resulting in substantial amounts of lost time and associated costs. Real-time monitoring has emerged as an important tool to achieve drilling optimization in avoiding downtime, particularly stuck pipe events. With the addition of a predictive monitoring system, this process becomes much more effective and competent. Predictive monitoring is used for advanced real-time monitoring in the remote centre and operational workflows to aid in the drilling execution of complex or critical well sections. The emphasis will be on reducing the complexity of real-time data analysis by exploiting trends and anomalies between modelled and actual data to monitor wellbore conditions. This monitoring system and trend-based predictive capability enable drilling teams to detect borehole changes and take preventive action up to several hours in advance. Predictive monitoring can provide early warning of stuck pipe symptoms, allowing the rig and operations team to take corrective and step-by-step actions. The circumstances that lead to the stuck pipe can be difficult to detect as various factors may indicate potential problems. These are frequently missed until the situation has progressed to the point where the drill string becomes stuck. This system could have provided the rig crew with advance notice of changes in downhole conditions. An example of predictive monitoring adoption in a highly deviated extended reach well (ERD), with a 12,000ft long horizontal section is presented. It is exceptionally challenging in terms of geomechanics perspective as well as the well design. Predictive monitoring was implemented to assist drilling operation for the sidetracked well, and it had been completed successfully with minor hole condition issues. The predictive monitoring system is built around a trio of tightly coupled real-time dynamic models consisting of hydraulic, mechanical, and thermodynamic that simulate the wellbore state and physical processes during drilling operations. These models work simultaneously in a seamless process to assess drilling performance, borehole conditions, and related associated risks. It uses dynamic modelling to accurately model key drilling parameters and variables, allowing better monitoring.