Fault diagnosis in managed pressure drilling using nonlinear adaptive observers

Willersrud, Anders; Imsland, Lars

doi:10.23919/ecc.2013.6669354

Cited by 11 publications

(18 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…4. As indicated in the figure, details about design of the adaptive observers are available in [14] and derivation of the GLRT detector for a t-distribution is available in [15].…”

Section: Fault Diagnosis Methodologymentioning

confidence: 99%

“…These changes can appear in residuals, signals that are zero under normal conditions but differ from zero in the presence of faults, or in estimated parameters of the system. One [14] [14]…”

Section: Fault Diagnosis Methodologymentioning

confidence: 99%

“…This paper employs a computationally simple mathematical model of the process in a nonlinear adaptive observer [14] to estimate friction parameters and fluid flow. The estimates were found to follow a t-distribution and a dedicated generalized likelihood ratio test (GLRT) was developed for this particular distribution in [15].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fault diagnosis of downhole drilling incidents using adaptive observers and statistical change detection

Willersrud

Blanke

Imsland

et al. 2015

Journal of Process Control

Self Cite

View full text Add to dashboard Cite

“…4. As indicated in the figure, details about design of the adaptive observers are available in [14] and derivation of the GLRT detector for a t-distribution is available in [15].…”

Section: Fault Diagnosis Methodologymentioning

confidence: 99%

Section: Fault Diagnosis Methodologymentioning

confidence: 99%

See 1 more Smart Citation

Fault diagnosis of downhole drilling incidents using adaptive observers and statistical change detection

Willersrud

Blanke

Imsland

et al. 2015

Journal of Process Control

Self Cite

View full text Add to dashboard Cite

“…The model-based adaptive observer (Willersrud and Imsland, 2013) is presented in this section, which is used to estimate friction parameters and flow rates. First the model itself is presented, then a brief overview of the observer is shown.…”

Section: Modeling and Estimationmentioning

confidence: 99%

“…The states and parameters in (1) are estimated using the adaptive observer in Willersrud and Imsland (2013) …”

Section: Adaptive Observermentioning

confidence: 99%

Early Pack-Off Diagnosis in Drilling Using an Adaptive Observer and Statistical Change Detection

2015

Self Cite

View full text Add to dashboard Cite

An improved intelligent early warning method based on MWSPCA and its application in complex chemical processes

et al. 2019

View full text Add to dashboard Cite

With the development of industrial automation, the requirement of abnormal early warning in the industrial production process is getting higher and higher.Facing complex chemical processes, traditional fault detection and abnormal early warning methods have low detection efficiency and poor real-time performance. Therefore, this paper analyzes and studies fault detection and abnormal early warning methods, and puts forward an improved intelligent early warning method based on the moving window sparse principal component analysis (MWSPCA) suitable for complex chemical processes. The sparse principal component analysis algorithm is used to establish the initial early warning model, and then the moving window is used to update the early warning model, which makes the early warning model more suitable for the characteristics of time-varying data. Furthermore, the proposed method reduces the false alarm rate and missed alarm rate of the early warning, and improves the real-time performance of the early warning model. Finally, the feasibility and the validity of the proposed method are verified by the TE process and the oil drilling process. The experiment results show that the proposed method can reduce the risk of complex chemical processes. K E Y W O R D Scomplex chemical processes, fault detection, intelligent early warning, MWSPCA

show abstract

Fault diagnosis in managed pressure drilling using nonlinear adaptive observers

Cited by 11 publications

References 22 publications

Fault diagnosis of downhole drilling incidents using adaptive observers and statistical change detection

Fault diagnosis of downhole drilling incidents using adaptive observers and statistical change detection

Early Pack-Off Diagnosis in Drilling Using an Adaptive Observer and Statistical Change Detection

An improved intelligent early warning method based on MWSPCA and its application in complex chemical processes

Contact Info

Product

Resources

About