Toward Drilling Automation: On the Necessity of Using Sensors That Relate to Physical Models

Cayeux, Eric; Daireaux, Benoît; Dvergsnes, Erik Wolden; Florence, Fred

doi:10.2118/163440-pa

Cited by 32 publications

(6 citation statements)

References 39 publications

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“…These problems have been addressed in Cayeux et al (2013). However, it is important to understand that it is not only the quality of the data that is affecting pressure control, but also the placement of the sensors and the awareness of what is actually measured.…”

Section: Measurementsmentioning

confidence: 99%

Back-Pressure MPD in Extended-Reach Wells - Limiting Factors for the Ability to Achieve Accurate Pressure Control

2014

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Extended-Reach Drilling (ERD) with narrow pressure margin or uncertain geo-pressure is a challenge with respect to accurate pressure control. The back-pressure Managed Pressure Drilling (MPD) method has been widely used in drilling operations with the aim of controlling annulus pressure within safe bounds, and may also be applicable for ERD wells. However, the ability to control the pressure accurately is limited by several factors. Some of which are related to back-pressure MPD operations in general and some of which are more specific to ERD wells. In this paper a study is presented on how pressure control is affected and sometimes limited by the actual data availability and quality, equipment, hydraulic models, control algorithms, and downhole conditions during an MPD operation in an ERD well. By using a transient well flow model, the theoretically obtainable MPD performance can be simulated. In particular, the benefit by utilizing real-time downhole pressure measurements transmitted by a wired drill pipe is demonstrated by simulations. It is shown quantitatively how variations in sensor delay and bandwidth will influence the ability to control downhole pressure accurately in an ERD well.Benefit by this approach is a more accurate prediction of what is obtainable with MPD and how various factors may influence the ability to control downhole pressure.

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Section: Measurementsmentioning

confidence: 99%

Back-Pressure MPD in Extended-Reach Wells - Limiting Factors for the Ability to Achieve Accurate Pressure Control

2014

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“…To overcome these limitations, researchers have focused on developing coal mine underground drilling robots [5][6][7]. These intelligent robotic systems can autonomously perform drilling tasks [8], utilizing advancements such as automatic attitude adjustment, autonomous navigation, sensing, and control [9][10][11][12][13][14]. Among these advancements, automatic rod feeding is a critical technology for coal mine underground drilling robots.…”

Section: Introductionmentioning

confidence: 99%

Algorithm for Automatic Rod Feeding and Positioning Error Compensation for Underground Drilling Robots in Coal Mines

Lu,

Kong,

Peng

et al. 2023

Sensors

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In the pursuit of automating the entire underground drilling process in coal mines, the automatic rod feeding technology of drilling robots plays a crucial role. However, the current lack of positional accuracy in automatic rod feeding leads to frequent accidents. To address this issue, this paper presents an algorithm for compensating positioning errors in automatic rod feeding. The algorithm is based on a theoretical mathematical model and manual teaching methods. To enhance the positioning accuracy, we first calibrate the pull rope sensor to correct its measurement precision. Subsequently, we establish a theoretical mathematical model for rod feeding positions by employing spatial coordinate system transformations. We determine the target rod feeding position using a manual teaching-based approach. Furthermore, we analyze the relationship between the theoretical rod delivery position and the target rod delivery position and propose an anisotropic spatial difference compensation technique that considers both distance and direction. Finally, we validate the feasibility of our proposed algorithm through automatic rod feeding tests conducted on a coal mine underground drilling robot. The results demonstrate that our algorithm significantly improves the accuracy of rod feeding positions for coal mine underground drilling robots.

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“…However, as pointed out in Gravdal et al (2018), changing conditions in the wellbore due to well geometry, open-hole sections, formation and fluid properties, along with changing temperature profile along the well can limit the PID controller in terms of required re-tuning during the operations. These quantities are in many cases dependent on the movement of the DS, and it is emphasized that the control law should oppose limitations on the mechanical side of the drilling operation (Cayeux et al, 2014). Application of automatic control to obtain reference tracking of the bottom-hole pressure (BHP) with tight pressure margins is commonly referred to as Managed Pressure Drilling (MPD).…”

Section: Introductionmentioning

confidence: 99%

“…The challenges of maintaining a stable wellbore are connected to the reliability of the measurement data and the physical model used for real-time wellbore state prediction (Cayeux et al, 2014). Sensors used for well control are mud-pulse telemetry, wired drillpipe transmitting pressure measurements to the surface, and the gyro in the bottom-hole assembly (BHA).…”

Section: Introductionmentioning

confidence: 99%

Identification and Optimal Control for Surge and Swab Pressure Reduction While Performing Offshore Drilling Operations

Tengesdal¹,

Holden²

2020

MIC

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In this paper, an unscented Kalman filter (UKF) coupled with a nonlinear model-predictive controller (NMPC) for a hydraulic wellbore model with multi-variable control and tracking is presented. In a wellbore, high drill string velocities in operational sequences such as tripping might result in surge and swab pressures in the annular section of the wellbore. To overcome these challenges, a controller incorporating safety and actuator limits should be used. A second-order model is used to predict axial drill string velocity downhole. With a NMPC specifying the block position trajectory, choke flow reference, desired backpressure pump flowrate and stand-pipe pressure, we can automatically supervise and control the pressure in the wellbore. To compensate for unmeasured states, an estimator is designed to predict the frictional pressure forces in the wellbore and filter noisy measurements. A stochastic approach for the hydraulic model is taken, including variance of the average fluctuations for the flow and pressure states. Comparing three NMPC configurations, the result of using an integration of the tracking error in the prediction model gave best offset-free tracking of the bottom-hole pressure. The controller compensates for the unknown fluctuations, and is shown to be robust towards model mismatch. Including the mechanical system in the NMPC prediction model, we can effectively constrain the predicted axial drill string velocity to reduce the pressure oscillations and achieve tracking of bottom hole pressure and choke differential pressure. The outcome is shown through extensive simulations to be an effective control strategy, reducing the pressure spikes while tripping.

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Toward Drilling Automation: On the Necessity of Using Sensors That Relate to Physical Models

Cited by 32 publications

References 39 publications

Back-Pressure MPD in Extended-Reach Wells - Limiting Factors for the Ability to Achieve Accurate Pressure Control

Back-Pressure MPD in Extended-Reach Wells - Limiting Factors for the Ability to Achieve Accurate Pressure Control

Algorithm for Automatic Rod Feeding and Positioning Error Compensation for Underground Drilling Robots in Coal Mines

Identification and Optimal Control for Surge and Swab Pressure Reduction While Performing Offshore Drilling Operations

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