Fault diagnosis in managed pressure drilling using nonlinear adaptive observers

A bank of nonlinear adaptive observers is used for fault diagnosis in oil and gas drilling where managed pressure drilling (MPD) is applied. The particular fault considered is formation of a pack-off, causing increased friction in one part of the annulus. The process model is a simplified hydraulics model with a Newtonian fluid. All states in the model are assumed measurable, an assumption based on planned implementation of the wired drill pipe measurement technology. A fault detection observer is used to detect that a pack-off is being formed somewhere in the annulus. Then a set of fault isolation and approximation observers, one for each possible fault, is used to isolate the location of the pack-off and estimating its magnitude. Isolation is done by using residuals of annular friction estimation. The method for fault diagnosis is illustrated in a simulation study.

[1]  Tor Arne Johansen,et al.  Parameter estimation and compensation in systems with nonlinearly parameterized perturbations , 2010, Autom..

[2]  Marios M. Polycarpou,et al.  A robust detection and isolation scheme for abrupt and incipient faults in nonlinear systems , 2002, IEEE Trans. Autom. Control..

[3]  Michèle Basseville,et al.  Detection of Abrupt Changes: Theory and Applications. , 1995 .

[4]  Cesare Alippi,et al.  Fault Diagnosis Systems , 2014 .

[5]  Bernt S. Aadnøy,et al.  Advanced Drilling and Well Technology , 2009 .

[6]  G. Besançon.  Remarks on nonlinear adaptive observer design , 2000 .

[7]  Qinghua Zhang,et al.  Nonlinear system fault diagnosis based on adaptive estimation , 2004, Autom..

[8]  Youmin Zhang,et al.  Issues On Integration of Fault Diagnosis and Reconfigurable Control in Active Fault-Tolerant Control Systems , 2006 .

[9]  M. V. Iordache,et al.  Diagnosis and Fault-Tolerant Control , 2007, IEEE Transactions on Automatic Control.

[10]  P. Olver.  Nonlinear Systems , 2013 .

[11]  Michèle Basseville,et al.  Detection of abrupt changes: theory and application , 1993 .

[12]  Gildas Besancon,et al.  FURTHER DEVELOPMENTS ON ADAPTIVE OBSERVERS FOR NONLINEAR SYSTEMS WITH APPLICATION IN FAULT DETECTION , 2002 .

[13]  Marios M. Polycarpou,et al.  Fault diagnosis of a class of nonlinear uncertain systems with Lipschitz nonlinearities using adaptive estimation , 2010, Autom..

[14]  Youmin Zhang,et al.  Bibliographical review on reconfigurable fault-tolerant control systems , 2003, Annu. Rev. Control..

[15]  Ole Morten Aamo,et al.  Adaptive Redesign of Nonlinear Observers , 2011, IEEE Transactions on Automatic Control.

[16]  Qinghua Zhang.  A new residual generation and evaluation method for detection and isolation of faults in non‐linear systems , 2000 .

[17]  Ole Morten Aamo,et al.  Simplified Hydraulics Model Used for Intelligent Estimation of Downhole Pressure for a Managed-Pressure-Drilling Control System , 2012 .

[18]  Rolf Johan Lorentzen,et al.  Wired Drill Pipe Telemetry Enables Real-Time Evaluation of Kick During Managed Pressure Drilling , 2010 .

[19]  Jean Gallier,et al.  Geometric Methods and Applications , 2011 .

[20]  Silvio Simani,et al.  Model-Based Fault Diagnosis Techniques , 2003 .

[21]  Steven X. Ding,et al.  Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools , 2008 .

[22]  Paul M. Frank,et al.  Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy: A survey and some new results , 1990, Autom..

[23]  R. N. Claek.  Instrument Fault Detection , 1978 .

[24]  Sigve Hovda,et al.  A Step Change in Total System Approach Through Wired Drillpipe Technology , 2008 .

[25]  R. Clark.  Instrument Fault Detection , 1978, IEEE Transactions on Aerospace and Electronic Systems.