Introducing new control functionality on the drilling rig has an effect on handling of machinery and controls and on the overlying work process both on the rig and for off-site support. New operational procedures taking these factors into account are therefore required to ensure safe and efficient application of such new technology.This paper presents a new method for developing operational procedures for the driller when applying a system for automatic safeguarding and optimization of pump and pipe control in drilling operations. This method has been developed and subsequently applied through a lengthy study. A laboratory test environment has been used for this purpose, containing an advanced drilling simulator with the safeguarding and optimization functionality integrated.The method applied consists of three phases, all performed in the laboratory test environment. Initially, the measurable effect of use of the system on the driller's performance was evaluated in detail, using a set of test cases and a series of test-personnel from a drilling contractor. Subsequently the ability to drill a well section with incorporated incidents and exceptions was studied. Finally, operational procedures were developed in cooperation with the test-personnel, again using the test environment for testing and checking of procedures.In this development process the focus has been on varying system modes and on handling of system and drilling process exceptions, while taking into account the effect of human factors and the wider organizational context of work conduct.The authors believe that the method described is a suitable way to develop procedures for application of new control functionality on the drilling rig, and would recommend that such studies should be performed for new technologies to be applied in control of drilling operations.
Automation consists of the use of control systems to control processes, reducing the need for human intervention. There has been considerable progress made in automating key tasks on the drill floor (i.e. mechanization), and in providing control of the weight on bit and bit rotation, etc. (e.g. Dupriest, 2005) to optimize the rate of penetration. In this paper we look at a stepwise implementation of adaptive drilling automation that responds to changing conditions in the wellbore. Within well construction, one specific process that may be well suited to this adaptive automation is the tripping of drillpipe or casing into or out of the well. Tripping operations today are guided by pre-drill analysis to determine safe tripping speeds and require the driller to react to changing downhole conditions to avoid problems such as swab, surge, or hole collapse. In this paper we describe a stepwise approach to partial adaptive automation of the tripping operation. The stepwise approach consists of continuously performing engineering-while drilling calculations to determine the dynamic hydraulic pressure profile variations within the wellbore at all depths for any driller-induced string motions or pump rates. Next we use these calculations to determine safe operational envelopes for the drilling machinery (accelerations, decelerations, rates and velocities), helping the driller to trip pipe in or out of the well while ensuring that the full wellbore hydraulic pressure profile always stays within the prescribed safe geopressure window based on current conditions. Finally, we reach the automation step where the operational envelopes guide the automated control of the drilling equipment.
Objectives/Scope The world's first deployment of an automated drilling control system on a Statoil rig in the North Sea helped the rig in saving up to 10% rig time per well through safeguarding and optimizing manual operations and through automating repetitive drilling activities such as tripping, pipe filling, connections and pump start up. Advanced modelling of well conditions, combined with closed loop control of the drilling control system provided safeguards for pressure, rotary and hoisting velocity. Methods, Procedures, Process The drilling instrumentation, surface- and downhole sensors are coupled with robust real-time and fully transient hydraulic, mechanical and thermodynamic models that continuously evaluate the current downhole conditions. These models determine all possible combinations of drillers' actions (string accelerations, velocities, rotation, pump start-ups and flow rates) that will cause the dynamic downhole pressure to reach or exceed upper and lower well stability- and geo-pressure prognosis. These results are actively used to safeguard both manual and automated sequences. For example should the driller attempt to pull the drill string at a velocity that would cause the downhole pressure to fall below the Pore Pressure or Collapse Pressure at any depth in the open hole section, the drilling control system will intervene and limit the upward velocity to a safe value based on the dynamic model. Results, Observations, Conclusions The models effectively calculated and communicated current limits to the drilling control system, allowing the control system to safeguard the well against human error during manual operations and to automate various repetitive operations. Statistics after 3 wells proved an overall time saving of 4% per well through automated repetitive sequences (such as pump start-ups and friction tests) while another 2–8% time savings per well were realized through optimized manual operations (active safeguards and safety triggers) and other improvement initiatives by the rig. Although the system was originally developed to eliminate human errors and avoid major incidents (including technical side-tracks), the daily efficiency gains indicate that the system also avoids minor issues that otherwise would have slowed down the operation without being seen as downtime or Invisible Lost Time. This indicates that the system works as intended and that the system should be able to avoid major incidents when the relevant conditions arise. Novel/Additive Information This paper demonstrates how automation reduces invisible lost time and allows drillers to focus on other activities while repetitive tasks are controlled by software. Furthermore, rig safety is significantly enhanced since the closed loop drilling control system prevents users from exceeding the dynamic limits calculated by the drilling control system.
The ability to predict the response of a drill bit to the topside axial and rotational velocities of the drill-string is a prerequisite for any system aimed at automatically controlling the drilling parameters to optimize the rate of penetration and the overall quality of the well construction process. When drilling with a Polycrystalline Diamond Compact (PDC) bit, even the steady-state response can exhibit complex behavior, characterized by the presence of (at least) three different regimes whose range and parameters depend upon the bit characteristics and the mechanical properties of the formations being drilled. Transient effects significantly complicate the situation, especially when vibrations (axial, rotational or lateral) disturb the drilling process. Often, the root cause of these vibrations lies in the bit-rock interaction itself, while the drill string, through its elasticity and interaction with the borehole wall, may amplify or attenuate these vibrations. Therefore, continuous calibration of the drill string and bit-rock parameters from available surface and downhole measurements is critical for any automated control system relying on dynamic models of the drilling process. We present a calibration procedure whose goal is two-fold: first, to identify the time-varying parameters involved in the bit-rock interaction, and second, to provide a low-order, transfer function model approximation of the drill string axial and rotational dynamics. Our approach is based on particle filter techniques and a refined instrumental variable method for transfer function model estimation, and allows for real-time estimation of the various model parameters. We illustrate its behavior against recorded drilling data, where the proposed methods are shown to capture the different dynamics in place. We explain, in addition, how the calibrated drill string and bit-rock interaction models can be integrated in a framework to identify drilling parameter regions prone to axial or rotational vibrations.
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