Operator and Service Provider Collaborate to Successfully Introduce an Automated Advisory System in a Wildcat Exploration Well Offshore Mexico
Authors: Batruny Peter , Paimin M Razali , Allauddin M Arriffuddin , Lyra Felipe , Doria Linda , Castro Boris 
Published: March 2022

Abstract
Subsurface uncertainty, inadequate offset wells correlation, and high investment cost are some of the biggest drilling challenges in any frontier environment or wild cat exploration wells. These challenges comes with inherent risk on people, environment, assets, and reputation. Mitigating these risks through contingency in the detailed well planning phase as well maximizing operational uptime and efficiency during the well delivery phase, greatly impact the outcome of the well. Digital tools and automation have been a cornerstone in the industry's latest tools to reduce personnel on the rig, as well as minimize downtime and inefficiency.
A collaboration of experts between an Operator and Service company was formed during the well planning phase to evaluate the feasibility of an automation platform for a holistic drilling advisory platform that facilitates real time decision making based on downhole and surface data. An offset well study in the area showed that nearby wells experienced recurrence incidents of wellbore instability and downhole pore pressure uncertainty. Modeling iterations for dynamic and static drilling were simulated during pre-planning phase and optimized in real time based on actual downhole and surface data information. Real time models were compared against dynamic models such as Torque and Drag, Hole Cleaning, Pore pressure, ECD (Equivalent Circulating Density), ESD (Equivalent Static Density), and tripping speed (Swab, Surge, etc.). An automated directional drilling tool was run and compared to decisions made by the directional driller to improve the tool's decision-making process for predictive well trajectory parameters. Based on the resultant models, proactive advice was given to the rig in real-time to optimize the input parameters and reduce negative impact to well operation.
For example, the practical, real-time visualization helped quickly identify a decreasing pore pressure trend and avoided resultant high overbalance while drilling the 17.5 in. × 22 in. section. The early warning alert allowed swift real time reaction sent to the rig, with mud weight subsequently decreased to 9.2 ppg, avoiding a potential risk of differential sticking stuck pipe incident due to high mud overbalance. Torque and Drag monitoring throughout the well accurately identified few instances of deviation from the trend and models, which detected an early sign of deteriorating wellbore condition which eventually led to a temporary stuck pipe event. Nevertheless, the pipe was freed, which demonstrate that the real time advisory helps in minimizing and avoiding the severe impact of the stuck pipe on the drilling operation. Automated advisory effectively delivered alerts on tight spots while drilling and casing running resulting in a faster 9-5/8 in. liner running in the deviated section. Tripping advisory mode and Real-time modelling of the swab-surge limits successfully allowed the team to avoid critical areas or swabbing events, which increased tripping speed where an opportunity was available and reduced tripping speed when risk of swab/surge was high avoiding well control/well loss events. The automated directional drilling tool increases in accuracy as the dogleg increased. The intelligent advice from the model got closest to the decisions taken by the directional driller, the closer the well got to the planned trajectory. These resulted in improvement and feedback for the pre-planning model such as target radius allowance, formation properties, and optimum drilling parameters.
This work takes the first steps towards drilling automation and digital integration of insights and operation. The collaboration between operator and service company resulted in a successful deployment of an automation platform as a solution to manage and mitigate risks as well as optimize drilling operations in exploration wells.