Vibration measurements have traditionally targeted the improvement of downhole tool reliability. This paper targets the effects of vibration on the complete drillstring. Failures associated with drillstring vibration continue to happen in spite of the sophistication of today’s measurements. These failures represent a very significant amount of lost time which we target to improve. The industry has a limited knowledge database or tools for managing and quantifying the risk of vibration to the complete drillstring. Operators are faced with an unknown quantification of the risk severity when attempting to mitigate vibration. By quantifying the risk, this work demonstrates how the prevention of incidents can be achieved. These incidents include, but are not limited to, twistoffs, backoffs, and bottomhole assembly (BHA) component failures. The proposed solution is based on real-time measurements of drillstring vibration to estimate an ongoing drillstring integrity risk which is used as a guideline to improve decisions while drilling the well. This solution has been developed using advanced vibration sensors to discriminate between different types of vibration. This was critical to estimating realistic cumulative damage to the drillstring, which is highly dependent on the type of vibration suffered by the assembly and the onset of vibration modes coupling. This paper shows that approximately 80% of drillstring integrity failures analysed can be identified and prevented using the proposed risk quantification solution. This result has been obtained despite the fact that fatigue or wear of drillstring components prior to a run is unknown and vibration sensors were located at a single position in the drillstring. This indicates that the primary contributor to drillstring failures is the drilling conditions for any given run.

Summary Vibration measurements have traditionally targeted the improvement of downhole-tool reliability. This paper targets the effects of vibration on the complete drillstring. Failures associated with drillstring vibration continue to happen despite the sophistication of today's measurements. These failures represent a very significant amount of lost time, which we target to improve. The industry has a very limited database for evaluating indices to manage or quantify risks of vibration to the complete drillstring. This fact makes the use of the methods in the field heavily depend on the past experience of the drillers and on the rig types. Operators are faced with an unknown quantification of the risk severity when attempting to mitigate vibration. By quantifying the risk, this work demonstrates how the prevention of incidents can be achieved. These incidents include but are not limited to, twistoffs, backoffs, and bottomhole-assembly (BHA) component failures. The proposed solution is based on real-time measurements of drillstring vibration to estimate an ongoing drillstring-integrity risk, which is used as a guideline to improve decisions while drilling the well. This solution has been developed through use of advanced vibration sensors to discriminate between different types of vibration. This was critical to estimating realistic cumulative damage to the drillstring, which is highly dependent on the type of vibration suffered by the assembly and the onset of vibration-mode coupling. This paper shows that approximately 80% of drillstring-integrity failures analyzed can be identified and prevented through use of the proposed risk-quantification solution. This result has been obtained despite unknown fatigue or wear of drillstring components before a run, and vibration sensors were located at a single position in the drillstring. This indicates that the primary contributor to drillstring failures is the drilling conditions for any given run.

In recent years, our ability to record and share information about risks and events affecting rig operations has improved significantly. An important enabler in this has been the development, and broad adoption, of the risk object within the WITSML standard. However, the ability to effectively share data on a broader scale between wells, fields, and blocks has been a challenge. This is particularly important during the planning phase of a well, when access to all available offset risk information is crucial for a successful safe well design.This workflow, developed within a drilling engineering center, aims to better address this challenge through an integrated 3D approach, using functionality already available on the drilling engineer's desktop. The introduction of a WITSML-based workflow enables efficient and complete data transfer of risk and event data between different users and software applications with the result that the right data is available to the right people, at the right time. In recent years, our ability to record and share information about risks and events affecting rig operations has improved significantly. An important enabler in this has been the development, and broad adoption, of the risk object within the WITSML standard. However, the ability to effectively share data on a broader scale between wells, fields, and blocks has been a challenge. This is particularly important during the planning phase of a well, when access to all available offset risk information is crucial for a successful safe well design. This workflow, developed within a drilling engineering center, aims to better address this challenge through an integrated 3D approach, using functionality already available on the drilling engineer's desktop. The introduction of a WITSML-based workflow enables efficient and complete data transfer of risk and event data between different users and software applications with the result that the right data is available to the right people, at the right time. Drilling risks and events are defined throughout the planning and execution of a well, for example, during surveillance operations within an operations support center or at the rig. Although risk data is generated in predominantly well-centric software, a WITSML server is used to aggregate the data and populate a regional, 3D master risk project. In this project, intelligent filtering and 3D visualization tools are used to target offset data relevant to the current operation. Relevant risks are integrated into a 3D evaluation of the proposed well design, incorporating the geological model of the current prospect. As the well is drilled, the 3D evaluation is used to alert the rig and remote support teams of potential issues ahead of the bit. This approach streamlines the evaluation of risks in the planning stage of wells and enables more effective collaboration between the drilling and geological and geophysical team during execution.

The use of drilling dynamics measurements has traditionally focused on improving downhole tool reliability. This, however, is a limited scope and in recognition of this, drilling dynamics is approached as a process that starts early in the planning stage of a project and targets the performance of the complete drillstring. Failures or inefficiencies associated with drillstring dynamics continue to occur in spite of the sophistication of today's measurements, particularly in exploratory projects that extend the present drilling envelope. Several methodologies were integrated to address the challenges of drilling dynamics and overcome frequent failures observed on the initial exploratory work on the Browse Basin. A steep learning curve was achieved by accelerating the improvement cycle using advanced modelling techniques and obtaining optimum designs without the need of multiple trial and error cycles. This extended abstract also describes the use of real-time dynamics measurements to quantify the risks related to drillstring vibration, a critical need for the drilling environment observed in the basin that ties planning work into the execution stage. Finally, the project cycle is closed with the evaluation of drilling performance using data-handling tools that allow the effective use of large amounts of drilling data generated during the execution and feedback into a new planning cycle. The extended abstract describes the implementation of drilling dynamics modelling to assist performance improvement, but more importantly, the methodology to incorporate it into a real-time decision-making process that maximises the value of technology implementation.