Abstract The well construction process entails collaboration among stakeholders to optimize diverse design elements for an optimal drilling program. Execution of the drilling program demands meticulous operational compliance and critical real time decision making to deliver the well safely and on or even beyond the target. This paper explores the deployment and adoption of automated analytics solution that delivers autonomous intelligent insights on operations throughout a three-wells drilling campaign offshore Malaysia. By leveraging machine learning and advanced engineering algorithms, the system established new benchmarks in operational excellence. In this project, well planning activities were transitioned to a cloud environment encompassing all contextual information such as trajectory planning, wellbore geometry setup, pressure windows, operational parameters, etc. The finalized and approved drilling program is then provisioned into an intelligent automated real-time solution, which automatically configures all contextual data within the system. High-frequency sensors data is streamed to a smart edge solution, ensuring real-time transmission that enables the engineering computation on cloud. The solution utilizes hybrid algorithm that combines machine learning and physics models to eliminate the need for the application to learn from offset well, enabling the operator to adopt from the first well. This advance system autonomously monitors and interprets drilling conditions real-time such as abnormal standpipe pressure, pack off, shock & vibration, hydraulics, torque and drag with automated calibration, wellbore balance, abnormal MSE for drilling efficiency etc., issuing alerts and notifications whenever anomalies are encountered throughout the drilling process. On top of drilling conditions, the solution tracks drilling performance vs. plan and invisible lost time allowing operator to make quick and optimal decisions on performance. After about 4 months of operations, over 4,000 meters were successfully drilled with the automated analytics solutions. A very high level of adoption has been a catalyst for continuous improvements in procedural adherence and operational efficiency in the project. Throughout the execution of the operation, stakeholder alignment was significantly enhanced through data-driven interpretation rather than experience-based interpretation. This shift in approach led to a reduction in errors, accelerated decision-making turnaround times, and successfully prevented costly events. The operator concluded that advanced workflows, including hole cleaning, drilling efficiency, and torque & drag with automated calibration significantly contributed to improved operational performance. These innovations improved drilling operation efficiency by eliminating the need for time-consuming processes like wiper trips and backreaming as previously practiced, while effectively mitigating shock and vibration, resulting in an increase in drilling performance, achieving high ROP with an impressive 1300 meters drilled per day, and instantaneous ROP up to 110m/hr. Additionally, there were no losses recorded throughout drilling and cementing operation despite dealing with depleted reservoir, as equivalent circulating density (ECD) was well-managed. With the aid of high-frequency performance measurements and data intelligence tools, the solution saves 52 hours of operation timing and its corresponding potential costs by providing real-time event alerts and smart analytics. Ultimately, real-time monitoring in drilling operations enables the lean team to make timely and informed decisions, enhancing operational efficiency and minimizing non-productive time (NPT).
Razak et al. (Mon,) studied this question.
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