With the current format of SIDs being completely different each project and manually typed in every rigs, improving operational performance based on lessons learned can be quite complicated. The digitalization of Standing Instruction to Driller (SID) can help to overcome this pain point by standardizing and synchronizing SIDs throughout company's operations globally. The paper approaches the subject by introducing a much leaner and seamless method in registering an SID. This can be achieved by having relevant drilling personnel to pick and choose from a common database of SIDs which is frequently updated and verified via web-based platform. The dropdown will be automatically filtered by the application according to the BHA and/or other relevant filter categories chosen. Digital SID drafting process will begin after Notice of Operations (NOOP) has been completed. Information from the NOOP will be populated in the Digital SID platform with all the required associated details including but not limited to BHA designs, hole sections, depths, procedures and lessons learned. These SIDs will have to be agreed and approved by assigned personnel prior to the execution of the operation. Since the solution is capable to create a high quality SID which is readable by both human and machine, it can be integrated with real-time sensors to provide automatic detection for every operation in the SIDs. Therefore, implementation of this Digital SID solution can sustain SIDs consistency across different projects and capable to embed insights in context for future reference. Direct business value created from Digital SID improves process cycle efficiency in a project well life cycle.

Stuck pipe incidents remain as one of the major problems in the drilling industry. The incidents will lead to expensive loss time in daily spread cost, bottom hole assembly cost, sidetracking cost as well as fishing cost. The Wells Augmented Stuck Pipe (WASP) Indicator, a state-of-the-art machine learning technology that seamlessly integrates with PETRONAS existing technologies, is introduced as the stuck pipe prevention detection system for the company. Historical real-time drilling data and stuck pipe incidents reports between 2007 and 2019 are used for the development of machine learning models. The models utilize key drilling parameters such as hookload and equivalent circulating density (ECD) to predict and analyze trends to detect any signature pattern anomalies for various stuck pipe events. The prediction and alarm are displayed in real-time monitoring software to trigger the operation team for prompt intervention. The WASP solution has demonstrated proven outcomes using historical and live well with high confidence in detecting stuck pipe incidents due to differential sticking, hole cleaning, and wellbore geometry. The WASP Indicator is envisaged to provide the company with cutting edge advantages in the industry. It is expected that the system will reduce the identification period and improve the reaction time of the monitoring specialists in recognizing the stuck pipe symptoms and highlighting potential incidents. The system is also bringing value to the company via non-productive time (NPT) cost avoidance and identification of early onset of various stuck pipe events based on distinct mechanisms. With the system, the existing portfolio value can be enhanced via setting dynamic trends and models into historical experiences context. The WASP Indicator is aspired to be the forefront innovation that will leap through the norm and lead the region in a greater plan of drilling automation system.