Drilling hard stringers that are erratically distributed in an underlying rather soft formation is challenging from different perspectives. An unforeseen change of the drilled formation from soft to hard and dense rock can cause impact damage to the bit, deflect the bottom-hole assembly (BHA), result in high bending loads, increase vibration, and cause wear/tear on BHA components. If not properly managed, this leads to non-productive time (NPT) and increased maintenance costs. Further, a deflection caused by a stringer away from the planned well path that is detected late results in high local doglegs (HLD) and requires time-consuming correction through reaming with invisible lost time (ILT). Recently, a stringer detection method based on vibrations, namely high-frequency torsional oscillations (HFTO), has been presented. A case study with 21 sections in the North Sea based on this solution is shown that demonstrates a reduction in ILT by 80%. The system is based on a timely and reliable detection of stringers, an optimized mud pulse telemetry scheme, and an automated advisory system. The downhole algorithm embedded in a measurement while drilling tool is consistently interpreting HFTO based on tangential acceleration and dynamic torsional torque measurement. By defining thresholds for the amplitude and the localization with respect to frequency content of HFTO, the algorithm results are translated into a binary value with 1 – stringer currently drilled or 0 - no stringer is drilled. The low bandwidth consuming 1-bit value and downhole measured bending moment are sent in 10 to 15 second intervals to the surface by mud pulse telemetry. Once the stringer is detected, the bending moment data is closely monitored to react correctly and efficiently to a stringer in different scenarios. This solution is discussed in a case study in Norway covering 21 sections with and without the system deployed. The offshore application is challenged by frequently occurring stringer layers and nodules of different geometry. Based on the stringer content, the reaming time has been typically high in this application. The system, however, enabled a timely detection of the stringers and an optimal stringer drilling enabled by the frequently sent bending moment information. Therefore, stringer drilling was done without having to pull off-bottom frequently and ream the transition area between soft and hard formation thereby saving time and reducing wear on the BHA and drill pipe, ultimately ending up with a smoother/straighter wellbore. By using the system, a faster reaction to any stringer and the use of appropriate parameters to avoid costly HLDs are achieved. The case study demonstrates a significant and consistent improvement in ILT. The reaming hours per 1000 m as a benchmark have been reduced from 2-5 hours without to 0.3-0.6 hours with the system resulting in an average saving of 12 hours per reservoir section.

Tripping operations can take up a significant portion of well construction time and the associated cost. In the last decade, there has been extensive development and deployment of real-time tripping applications to optimize tripping parameters while maintaining formation integrity. This paper presents a system that utilizes transient modeling of tripping behavior to determine the optimum parameters that safeguard the integrity of the formation and the mechanical equipment at the rig site. The system delivers tripping boundaries to automated drilling control systems (ADCS) for every stand. A digital twin of the wellbore, equipped with physics-based transient models, estimates the permissible axial velocities and accelerations developed when running drillstring in and out the wellbore. These motions develop pressure waves which travel along the wellbore and which can compromise formation integrity. The digital twin, prepared in the planning phase and deployed in the real-time drilling environment, uses smart triggering algorithms to automatically update the models and refine simulation results. Automation systems consume the predicted limits via an aggregation layer to refine fit-for-purpose tripping applications. The automation system finds optimum proposals of tripping limits and updates them directly in the rig control system in real-time. The trip monitoring system automatically and continuously publishes optimum velocity and acceleration tripping limits per stand and transmits them as set points to the ADCS to define a safe operating envelope (SOE). This approach can greatly reduce the overall tripping time in comparison to non-automated deployments. Furthermore, the reduction of invisible lost time (ILT) takes place while maintaining the integrity of the formation, and the integrity of the surface equipment. Finally, reduction of the energy required to perform the tripping process consequently decreases the amount of carbon emissions involved in the process. A set of case studies confirm the effectiveness of the approach and illustrate its benefits. A case study addresses the topic of adoption of drilling automation applications such as the tripping advisor. Another case presents the concept of interoperability using as example a deployment on a rig simulator setup in Europe to perform closed-loop control using the tripping application to write velocity and acceleration limits continuously to the ADCS.