Improving Drilling Performance by Applying Advanced Dynamics Models
- M.W. Dykstra (Hughes Christensen) | M. Neubert (Baker Hughes INTEQ) | J.M. Hanson (Consultant) | M.J. Meiners (Hughes Christensen)
- Document ID
- Society of Petroleum Engineers
- SPE/IADC Drilling Conference, 27 February-1 March, Amsterdam, Netherlands
- Publication Date
- Document Type
- Conference Paper
- 2001. SPE/IADC Drilling Conference
- 1.4.4 Drill string dynamics, 4.3.4 Scale, 5.3.4 Integration of geomechanics in models, 1.6.6 Directional Drilling, 1.6.2 Technical Limit Drilling, 1.10 Drilling Equipment, 1.10.1 Drill string components and drilling tools (tubulars, jars, subs, stabilisers, reamers, etc), 1.4.1 BHA Design, 1.6.3 Drilling Optimisation, 1.12.1 Measurement While Drilling, 7.1.9 Project Economic Analysis, 1.2.5 Drilling vibration management, 7.1.10 Field Economic Analysis, 1.5 Drill Bits, 1.6.1 Drilling Operation Management, 1.6.7 Geosteering / Reservoir Navigation, 1.6 Drilling Operations, 1.5.1 Bit Design
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Drilling dynamics models play an important role in drilling performance optimization. These models can be classified as engineering tools or research tools, depending on functionality. Engineering tools are designed for everyday use; they provide estimates of important parameters for planning purposes, such as natural frequencies and buckling loads. Research tools describe the physics of the problem more completely, and thus are more powerful. They allow complex phenomena to be studied in great detail, but require a greater investment of time and effort. Both types of models require validation, either through laboratory testing or controlled field tests. Once confidence in the models is established they can be used in a number of ways, including component design, bottom hole assembly (BHA) design, and investigation of component contributions to overall drilling system performance.
Application of advanced dynamics models within one major service company has provided some valuable lessons. Examples include: (1) polycrystalline diamond compact (PDC) bit designs can be adjusted to minimize impact damage to cutters; (2) roller cone designs can be adjusted to reduce off-center running tendencies; (3) BHA stabilization can be optimized to protect sensitive downhole equipment; (4) BHA designs that are unstable can cause rapid bit destruction; (5) operating parameters can be adjusted to improve performance of sub-optimal drilling systems.
Case studies from disparate drilling applications around the world have demonstrated that performance can be improved by applying lessons learned from advanced dynamics models. Operators have experienced significant savings in rig time stemming from reduced tool failure frequency and increased drilling efficiency. Greater tool longevity and reduced maintenance costs have also benefited the service company.
The study of drilling system dynamics arose from a desire to improve drilling efficiency and protect expensive downhole components.1-5 These goals are achieved most readily through an integrated strategy comprising planning, real-time monitoring and detailed post-well analysis.6-9
The planning phase begins with identification of dynamic dysfunctions most likely to occur during a bit run. The most significant of these include bottom hole assembly (BHA) buckling, bit bounce, bit and BHA whirl, and stick-slip. Mathematical models are then used to design BHAs that accomplish directional needs, provide adequate rates of penetration, and resist the targeted dysfunctions (by avoiding critical speeds, for instance). Vibrations can be monitored during the drilling phase using surface10-13 and downhole14-19 sensors. Based on these measurements, past experience and model results, operating parameters may be adjusted so that rate of penetration (ROP) and vibration severity remain at acceptable levels. Once the drilling program is completed the performance during each run is evaluated in detail. Expectations based on offsets and model predictions are compared with field observations to capture valuable lessons and improve the planning process for future wells.
The procedure described above relies on mathematical models in two ways: (1) prediction of weight/speed combinations likely to trigger the onset of dynamic dysfunctions, and (2) fundamental understanding of methods for decreasing vibration magnitudes when they become problematic. The models used for these purposes can be broadly classified as engineering tools and research tools, depending on functionality.
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