Managing Pressures During Underbalanced Cementing by Choking the Return Flow; 
Innovative Design and Operational Modeling as Well as Operational Lessons

Eck-Olsen, Johan; Pettersen, Per-Johan; Ronneberg, Arnfinn; Bjorkevoll, Knut Steinar; Rommetveit, Rolv

doi:10.2523/92568-ms

Cited by 8 publications

(3 citation statements)

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“…These models are based on distributed parameter models of multiphase flow and are able to reproduce a wide range of drilling-specific events, such as pipe connections, cementing, gelling and multi-fluid scenarios to an impressingly high degree of detail [15], [16]. Real-time versions of the models have also been developed and used with success [3], [16], [4].…”

Section: Introductionmentioning

confidence: 98%

“…Over the last 10 years much research has been devoted to the field offshore MPD and there have been several successful applications, both on the Norwegian continental shelf [3], [4], [5], [6], [7], and in the rest of the world [8], [9], [10]. [1] divides existing MPD technologies into several categories, all of which have their pros and cons.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive estimation of downhole pressure for Managed Pressure Drilling operations

Stamnes

Kaasa

Aamo

2011

2011 IEEE International Symposium on Intelligent Control

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The objective of Managed Pressure Drilling (MPD) is to enable precise control of the downhole pressure during drilling and completion operations. An essential part of an automated MPD control system is the downhole pressure estimator, usually referred to as the hydraulic model, which in most cases is the limiting factor for achievable accuracy of the system. In this paper we present a new design of an adaptive observer for online estimation of the downhole pressure in the well. Unlike conventional hydraulic models, which are based on complex partial differential equations, the adaptive observer is based on a simplified lumped model of ordinary differential equations, combined with online adaptation that tunes uncertain model parameters utilizing topside measurements. We demonstrate that the novell adaptive observer design captures the important hydraulics of MPD operations with high accuracy, and fundamentally improves the convergence rate of the parameter estimaties by using delayed observers. The results are demonstrated on field data from an offshore MPD operation.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Adaptive estimation of downhole pressure for Managed Pressure Drilling operations

Stamnes

Kaasa

Aamo

2011

2011 IEEE International Symposium on Intelligent Control

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“…See e.g. Eck-Olsen et al (2005), Bjørkevoll et al (2008) and Bjørkevoll (2010). For any simulation model, however, the overall accuracy is limited by the least accurate term.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Estimation of Downhole Pressure Using a Simple Hydraulic Model

et al. 2011

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An essential part of an automated MPD control system is the hydraulic model, which in many cases is the limiting factor for achievable accuracy of the system. A lot of effort has therefore been put into developing advanced hydraulic models that capture all aspects of the drilling fluid hydraulics. However, a main drawback is the resulting complexity of these models, which require expert knowledge to set up and calibrate, making it a high-end solution.In practice, much of the complexity does not contribute to improve the overall accuracy of the pressure estimate, simply because conditions in the well changes during MPD operations, and there are not enough measurements to keep all of the parameter of an advanced model calibrated. We will demonstrate that a simplified hydraulic model based on basic fluid dynamics is able to capture the dominating hydraulics of an MPD system. Furthermore, we will demonstrate that by applying algorithms for online parameter estimation, similar to those used in advanced control systems in the automotive and aerospace industry, the model can be calibrated automatically using existing measurements to achieve a level of accuracy comparable to that of an advanced hydraulic model. The results are demonstrated using field data from MPD operations in the North Sea, and dedicated experiments obtained at a full-scale drilling rig in Stavanger.

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Automatic Real-Time Drilling Supervision, Simulation, 3D Visualization and Diagnosis on Ekofisk

Rommetveit

Bjorkevoll

Odegaard

et al. 2008

IADC/SPE Drilling Conference

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eDrilling is a new and innovative system for real time drilling simulation, 3D visualization and control from a remote drilling expert centre. The concept uses all available real time drilling data (surface and downhole) in combination with real time modeling to monitor and optimize the drilling process. This information is used to visualize the wellbore in 3D in real time. eDrilling has been implemented in an Onshore Drilling Center in Norway. The system is composed of the following elements, some of which are unique and ground-breaking:• An advanced and fast Integrated Drilling Simulator which is capable to model the different drilling sub-processes dynamically, and also the interaction between these sub-processes in real time.• Automatic quality check and corrections of drilling data; making them suitable for processing by computer models • Real time supervision methodology for the drilling process using time based drilling data as well as drilling models / the integrated drilling simulator • Methodology for diagnosis of the drilling state and conditions. This is obtained from comparing model predictions with measured data.• Advisory technology for more optimal drilling. • A Virtual Wellbore, with advanced visualization of the downhole process.• Data flow and computer infrastructure eDrilling has been implemented in an Onshore Drilling Center on Ekofisk in Norway. The system has been used on several drilling operations. Experiences from its use will be summarized and presented. This paper has main focus on utilization of an advanced flow model for real time supervision and control of ECD and ECD related effects.

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Managing Pressures During Underbalanced Cementing by Choking the Return Flow; Innovative Design and Operational Modeling as Well as Operational Lessons

Cited by 8 publications

References 0 publications

Adaptive estimation of downhole pressure for Managed Pressure Drilling operations

Adaptive estimation of downhole pressure for Managed Pressure Drilling operations

Intelligent Estimation of Downhole Pressure Using a Simple Hydraulic Model

Automatic Real-Time Drilling Supervision, Simulation, 3D Visualization and Diagnosis on Ekofisk

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