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Downhole high frequency sensors are heralding the era of big data in drilling and have already shown potential to significantly push the limits of drilling performance. Downhole data transmitted in real time can be used to optimally select parameters during drilling and optimize off-bottom operations. The wealth of information from retrieved memory data gives immediate insights in well specific performance limiters. Nevertheless, downhole data is not yet used to its full potential, as the industry is only just beginning to make sense out of the many gigabytes of recorded data. Often, measurements cannot be unambiguously linked to specific downhole dynamics and their respective dysfunction. Most valuable information is lost directly at the sensor when processing (e.g. averaging) is not done appropriately. In other cases, huge amounts of high frequency data are transmitted and stored without providing much useful information. Large data volumes quickly reach the limits of transmission broadband and memory capacities of downhole tools and pose huge challenges to drilling data analysis and data integration. As a solution to handling the rapidly increasing amounts of drilling data, this paper proposes a value of information based approach to downhole sensors, data processing and analysis. An extensive set of field data from multiple operations is used to demonstrate the interrelation of dynamic effects and their impact on downhole sensor measurements. Different requirements on sensor type and collection frequency apply to identify different types of drilling performance limiting dysfunction, such as vibrations, well tortuosity or cutting accumulations due to poor hole cleaning. It is shown that the analysis of frequencies is key to separate multiple downhole effects wrapped into one measurement. For each prominent type of dysfunction, minimum data collection frequencies are specified which allows for the differentiation of unimportant noise from valuable drilling performance limiters. These insights are used to describe more effective methods of data processing, by cross-linking information from multiple sensors.
Downhole high frequency sensors are heralding the era of big data in drilling and have already shown potential to significantly push the limits of drilling performance. Downhole data transmitted in real time can be used to optimally select parameters during drilling and optimize off-bottom operations. The wealth of information from retrieved memory data gives immediate insights in well specific performance limiters. Nevertheless, downhole data is not yet used to its full potential, as the industry is only just beginning to make sense out of the many gigabytes of recorded data. Often, measurements cannot be unambiguously linked to specific downhole dynamics and their respective dysfunction. Most valuable information is lost directly at the sensor when processing (e.g. averaging) is not done appropriately. In other cases, huge amounts of high frequency data are transmitted and stored without providing much useful information. Large data volumes quickly reach the limits of transmission broadband and memory capacities of downhole tools and pose huge challenges to drilling data analysis and data integration. As a solution to handling the rapidly increasing amounts of drilling data, this paper proposes a value of information based approach to downhole sensors, data processing and analysis. An extensive set of field data from multiple operations is used to demonstrate the interrelation of dynamic effects and their impact on downhole sensor measurements. Different requirements on sensor type and collection frequency apply to identify different types of drilling performance limiting dysfunction, such as vibrations, well tortuosity or cutting accumulations due to poor hole cleaning. It is shown that the analysis of frequencies is key to separate multiple downhole effects wrapped into one measurement. For each prominent type of dysfunction, minimum data collection frequencies are specified which allows for the differentiation of unimportant noise from valuable drilling performance limiters. These insights are used to describe more effective methods of data processing, by cross-linking information from multiple sensors.
Moving into the next decade, wells in the Middle East are becoming more challenging as the deeper and more complex plays are exploited. This environment will be challenging from a torsional and tensile loading standpoint, and will be dynamically very active. This type of environment combined with high levels of H2S calls for a new high grade of sour service pipe. The Middle East is also opening up to the idea of high speed telemetry and wired pipe economics that call for a long lasting pipe product. When using sour service pipe that is traditionally limited to 105 KSI grades, even with an optimized string design, drillers sometimes have no other option than to sacrifice the margin of overpull, risking losing the well if fishing is unsuccessful. Alternatively, they can elect to use drill pipe, which is not suited for use in this corrosive environment, generally using API S135, with a risk of parting the string due to H2S embrittlement. To address these operational limitations, the pipe body, which is the drill pipe limiting member in tension, has to come with higher material strength and at the same time exhibit improved Sulfide Stress Cracking (SSC) resistance compared to API S135 grade. A novel grade of drill pipe was developed over a period of two years that is the strongest sour service drill pipe the industry has to offer to date and gives drillers an extra 19% of tensile capacity with its 125 KSI material yield strength. This new grade has been ordered for use in various regions of the world and for numerous applications. At this time, it is being used for intervention and stimulation operations in the Gulf of Mexico (GOM), and drilling long, extended reach (ER) wells with wired telemetry drill pipe in the Middle East. This paper presents the phases of the grade development and discusses testing requirements for the crossover between strength and SSC resistance. It also includes statistical data on the first full scale manufacturing tests. Finally, it outlines the products expectations for field applications.
This paper documents some of the key findings on the data required and methods used to detect and correct issues with drilling control systems such as auto drillers, top drive active torsional damping systems, and heave compensation systems. It has been found that the rig control systems and how they are tuned can have a significant impact on drilling dynamics. Issues related to drilling dynamics have varied widely among rigs, even among those that are in the same field and that have the same equipment and specifications. The standard answer has been that drilling is different on the ‘other side of the road, river, or anticline', or that one rig crew is better than the other. While there are significant differences in the drilling environment and between crews, recognition of the effects of the control systems employed can explain many of these differences and expand the tools and techniques available to improve drilling performance and reduce dysfunctions. Once the fundamental elements of a control system are understood, the performance limiters identified can often be applied to other rigs in the fleet with different systems via effective documentation of the changes made and their results. Opportunities abound for improvement in oilfield drilling control systems, their basic design, and documentation on how they should be tuned and best used. There are also opportunities in crew training catered to different audiences: Drilling Engineers, Rig Supervisors, Drillers, Directional Drillers, and Rig Electricians. Lastly, there is often a knowledge and communication gap between the software/control/user experience and engineers designing the control systems. Since rig control systems are not usually identified as the source of drilling dysfunction, requests for software or interface redesign have not often been initiated in the past. Not surprisingly, the best progress has been made when four way work groups were formed with all key stakeholders involved: the operator's drill team, internal technical experts, rig contractor and crew, and OEM control systems experts. Investing the time and personnel in this process and establishing group trust has helped prevent gaps in understanding of overall system performance. It also allows each stakeholder to contribute their expertise, raise concerns, and get buy in from their extended teams. This process takes commitment from all parties to change the way work is done, but the performance improvements are immediate and can be clearly seen. Challenges for the future are to continue to upgrade rig site manuals, arrange for more crew training, upgrade the control system design, and to incorporate the control system response as part of the topside boundary condition for future drilling dynamics models.
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