Publications by Program Areas

Publications by Program Areas

2022

  1. Caceres, Veronica Alejandra Torres. (2022). Well-Log Database and Automation of Well Log Depth Matching by Using Analytical Methods and Deep Learning. Doctoral theses at NTNU;2022:104. Please contact Veronica Torres Caceres for the PhD Thesis.
  2. Chawshin, Kurdistan; Berg, Carl Fredrik; Varagnolo, Damiano; Lopez, Olivier. (2022). Automated Porosity Estimation using CT-scans of Extracted Core Data. Computational Geosciences. 2022, 26 595-612. PDF

  3. Torres Caceres, V. A., Duffaut, K., Westad, F. O., Stovas, A., Johansen, Y. B., & Jenssen, A. (2022). Automated Log Data Analytics Workflow – The Value of Data Access and Management to Reduced Turnaround Time for Log Analysis. Petrophysics - The SPWLA Journal of Formation Evaluation and Reservoir Description, 63(01), 35-60. PDF

  4. Torres Caceres, Veronica Alejandra; Duffaut, Kenneth; Yazidi, Anis; Westad, Frank Ove; Johansen, Yngve Bolstad. (2022). Automated well log depth matching: Late fusion multimodal deep learning. Geophysical Prospecting. 2022, 1-28. PDF

2021

  1. Chawshin, K., Berg, C. F., Varagnolo, D., & Lopez, O. (2021a). A Deep-Learning Approach for Lithological Classification Using 3D Whole Core CT-Scan Images. SPWLA 62nd Annual Logging Symposium. PDF

  2. Chawshin, Kurdistan. (2021). Automated Lithology Classification Employing Whole Core CT-Scans. Doctoral theses at NTNU;2021:316. PDF

  3. Chawshin, Kurdistan; Berg, Carl Fredrik; Varagnolo, Damiano; Lopez, Olivier. (2021). A Deep-Learning Approach for Lithological Classification Using 3D Whole Core CT-Scan Images. I: SPWLA 62nd Annual Logging Symposium. Please contact Chawshin Kurdistan for the article.

  4. Chawshin, Kurdistan; Berg, Carl Fredrik; Varagnolo, Damiano; Lopez, Olivier. (2021). Lithology classification of whole core CT scans using convolutional neural networks. SN Applied Sciences 2021; Volume 3.(6) s. 1-21. PDF

  5. Chawshin, Kurdistan; Gonzalez, Andres; Berg, Carl Fredrik; Varagnolo, Damiano; Heidari, Zoya; Lopez, Olivier.(2021). Classifying Lithofacies from Textural Features in Whole Core CT-Scan Images. SPE Reservoir Evaluation and Engineering 2021; Volume 24.(02) s. 341-357. PDF

2020

  1. Alberts, L., Duffaut, K., & Rannem, T. (2020). Automatic Detection and Classification of Unconformities on Seismic Data Using Machine Learning. 2020(1), 1-5. 

  2. Torres, V., Duffaut, K., Stovas, A., Westad, F. O., & Johansen, Y. B. (2020). Automation of depth matching using a structured well-log database: Prototype well example in the North Sea. In SEG Technical Program Expanded Abstracts 2020 (pp. 440-444). 

2024

  1. Fedorov, S.; Hagspiel-Janssen, V.; Rogstad, R. W. H.; Haseldonckx, S.; Haugsgjerd, J. H; Rønning, A. (2024). Evaluation of tieback developments for marginal oil fields with timing flexibility. Energy Economics 2024; Volume 131. PDF

2023

  1. Abritta, R.; Pavlov, A.; Varagnolo, D.; Børresen, B. T. (2023). Inter-array cabling optimization in offshore wind power plants, a new reliability indicator for radial grids. Open Research Europe 2023; Volume 3.(214). 

  2. Abritta, R.; Pavlov, A.; Varagnolo, D.; Børresen, B. T. (2023). Probabilistic Economic Assessment of an Offshore Energy Hub Supplying Electrical Power to a Floating Production Storage and Offloading Unit. I: ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering. Volume 8: Ocean Renewable Energy. The American Society of Mechanical Engineers (ASME) 2023 ISBN 978-0-7918-8690-8. PDF

  3. de Oliveira, L. M.; da Silva Junior, I. C.; Abritta, R. (2023). A Space Reduction Heuristic for Thermal Unit Commitment Considering Ramp Constraints and Large-Scale Generation Systems. Energies 2023; Volume 16.(14). PDF

2022

  1. Fedorov, S.; Amar, M. N.; Hagspiel, V.; Lerdahl, T. (2022). Sequential production of two oil fields with an option to switch. Journal of Petroleum Science and Engineering 2022; Volume 218. PDF

  2. Fedorov, S.; Lavrutich, M.; Hagspiel, V.; Lerdahl, T. (2022). Risk and benefit sharing schemes in oil exploration and production. Energy Economics 2022; Volume 116. PDF

  3. Fedorov, Semyon. (2022). Cost-effective development of small discoveries on the Norwegian continental shelf. Doctoral theses at NTNU;2022:79. Please contact Semyon Fedorov for the PhD Thesis.

  4. Lei, Guowen. (2022). Automated Methodologies for Decision Support in Field Development. Doctoral theses at NTNU;2022:182. Please contact Guowen Lei for the PhD Thesis.

  5. Lei, Guowen; Hagspiel, Verena; Stanko, Milan. (2022). Price stress testing in offshore oil field development planning. Energy. 2022, 263 (D). PDF

  6. Lei, Guowen; Stanko, Milan; Silva, Thiago Lima. (2022). Formulations for automatic optimization of decommissioning timing in offshore oil and gas field development planning. Computers & Chemical Engineering. Volume 165, September 2022, 107910. PDF

2021

  1. Fedorov, S., Hagspiel, V., & Lerdahl, T. (2021). Real options approach for a staged field development with optional wells. Journal of Petroleum Science and Engineering, 205, 108837. PDF

  2. Lei, G., Silva, T. L., & Stanko, M. (2021b). A Mathematical Programming Approach to Determine Optimal Tieback Development Concepts of Two Offshore Oil Fields in the Barents Sea. The 31st International Ocean and Polar Engineering Conference. 

  3. Lei, G., Stanko, M., Silva, T. L., Widerøe, T., & Skogvang, A. (2021). The Use of Mathematical Programming to Determine Optimal Production and Drilling Schedule in an Offshore Oil Field, A Case Study From the Barents Sea. ASME 2021 40th International Conference on Ocean, Offshore and Arctic Engineering. PDF

  4. Lei, Guowen; Silva, Thiago Lima; Stanko, Milan. (2021). Compact Formulations for Efficient Early-Phase Field Development Optimization of Multi-Reservoir Fields. Computers and Chemical Engineering. 2021, 150. PDF

  5. Moon, S. K.; Stanko, M. (2021). Early-Phase Offshore Hydrocarbon Field Planning Considering Environmental Factors and Using Integrated Asset Modeling. I: ASME 2021 40th International Conference on Ocean, Offshore and Arctic Engineering Volume 10: Petroleum Technology. The American Society of Mechanical Engineers (ASME) 2021 ISBN 978-0-7918-8520-8. 

2020

  1. Fedorov, S., Hagspiel, V., Lerdahl, T., Idris, A., & Ghahfarokhi, A. J. (2020). Staged Development of a Marginal Oil Field Under Technical and Market Uncertainty: The Olympus Case. SPE Annual Technical Conference and Exhibition.

  2. Fedorov, Semyon and Hagspiel, Verena and Lerdahl, Thomas. (2020). Real Options Approach for a Staged Field Development With Optional Wells. PDF

2023

  1. Behzad Elahifar B., Hosseini E. (2023). Digitalization: Python Application for Drilling & Geoscience Engineer. 

  2. Elahifar, B.; Gomar, M. (2023). REAL-TIME AUTOMATIC PREDICTION, DETECTION, AND MITIGATION OF FLUID LOSS DURING DRILLING OPERATION EMPLOYING ALONG STRING MEASUREMENT (ASM) DATA ALONG WIRED DRILL PIPES BY USING DIGITAL TWIN IN NORWEGIAN CONTINENTAL. I: ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering: Volume 9: Offshore Geotechnics; Petroleum Technology. The American Society of Mechanical Engineers (ASME) 2023 ISBN 978-0-7918-8691-5. 

  3. Elahifar, B.; Gomar, M. (2023). Real-Time Prediction and Detection of Drilling Bit Issues Based on Along-String Measurements (ASM) Along Wired Pipes - A Case Study. Society Petroleum Engineers; 2023-03-07 - 2023-03-10.

  4. Gomar, M.; Elahifar, B. (2023). Real time prediction and detection of drilling bit issues during drilling with the focus on bit status evaluation using along string measurement (ASM). Geoenergy Science and Engineering 2023; Volume 224. 

  5. Nystad, Magnus. (2023). Real-Time Data-Driven Drilling Optimization. Doctoral theses at NTNU;2021;348. PDF

  6. Semwogerere, D.; Pavlov, A.; Sangesland, S. (2023). Well Integrity Operations Experience Transfer Using Long Short-Term Memory (LSTM) Recurrent Neural Network. I: ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2023): Volume 3 : Materials Technology; Pipelines, Risers, and Subsea Systems. The American Society of Mechanical Engineers (ASME) 2023 ISBN 978-0-7918-8685-4. 

2022

  1. Elahifar, B.; Gomar, M. (2022). Application of Digitalization in Real-Time Analysis of Drilling Dynamics Using Along-String Measurement (ASM) Data along Wired Pipes. Energies 2022; Volume 15.(23) PDF

  2. Gomar, M., & Elahifar, B. (2022). Real-Time Drilling Bit Fault and Symptom Diagnosis During Operation Based on Cutter Force Modeling of PDC Polycrystalline Diamond Compact Bits. IADC/SPE International Drilling Conference and Exhibition.

  3. Teigland, Andreas. (2022). A digital approach to modeling tubular wear and its effects on well integrity. Doctoral theses at NTNU;2022:122. Please contact Andreas Teigland for the PhD Thesis.

2021

  1. Kristoffersen, Brage Strand. (2021). Machine learning procedures for automatic well planning in reservoir simulation models. Doctoral theses at NTNU;2021:404. Please contact Brage Strand Kristoffersen for the PhD Thesis.

  2. Maksimov, D., Pavlov, A., & Sangesland, S. (2021). Prediction and Early Detection of Karsts—An Overview of Methods and Technologies for Safer Drilling in Carbonates. Energies, 14(20), 6517. PDF

  3. Nystad, M., Aadnøy, B. S., & Pavlov, A. (2021). Real-Time Minimization of Mechanical Specific Energy with Multivariable Extremum Seeking. Energies, 14(5), 1298. PDF

  4. Nystad, Magnus; Aadnøy, Bernt Sigve; Pavlov, Alexey.(2021). Micro-Testing While Drilling for Rate of Penetration Optimization: Experiments and Simulations. ASME Journal of Offshore Mechanics and Arctic Engineering, OMAE-21-1039. Please contact Magnus Nystad for the article.

2020

  1. Brechan, B., Teigland, A., Dale, S., Sangesland, S., & Kornberg, E. (2020). Collapse prediction of pipe subjected to combined loads. Journal of Petroleum Science and Engineering, 191, 107158. PDF

  2. Maksimov, D., Pavlov, A., & Sangesland, S. (2020). Drilling in Karstified Carbonates: Early Risk Detection Technique. ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering. PDF

  3. Nystad, Magnus, Pavlov, Alexey. (2020). Micro-Testing While Drilling for Rate of Penetration Optimization. The American Society of Mechanical Engineers (ASME) 2020, 39th International Conference on Ocean, Offshore and Arctic Engineering. Volume 11: Petroleum Technology. OMAE 2020-18838. PDF

2019

  1. Arnø, M. L., Thuve, A., Knoop, S., Handeland, A.S., Turøy, P.Ø., Hovda, S., Pavlov, A. (2019). Design and implementation of a miniature autonomous drilling rig. SPE/IADC International Drilling Conference and Exhibition. SPE-194226-MS.

  2. Arnø, M. L., Thuve, A., Knoop, S., Handeland, A.S., Turøy, P.Ø., Hovda, S., Pavlov, A. (2019). Design and implementation of a miniature autonomous drilling rig. VIII Oil and Gas Production Optimization Workshop, 29-30 April 2019, Rio de Janeiro, Brazil.

  3. Hovda, S. (2019). Multi-dimensional semi-analytical model for axial stick-slip of a rod sliding on a surface with Coulomb friction. Advances in Mechanical Engineering 2019, Volume 11(3), pp. 1-12. PDF

  4. Hovda, S. (2019). Optimal procedures for lowering and applying weight on the bit when starting to drill. Journal of Petroleum Science and Engineering 2019, pp. 872-879. PDF

2023

  1. Andersen, Joakim Rostrup. (2023). Contributions to optimizing control – Inspired by challenges in oil and gas production. Doctoral theses at NTNU; 2023:127. PDF

  2. Andersen, Joakim Rostrup; Imsland, Lars Struen; Pavlov, Alexey. (2023).  Data-driven derivative-free trust-region model-based method for resource allocation problems. Computers and Chemical Engineering 2023; Volume 176. s. PDF

  3. Diaa-Eldeen, T.; Hovd, M.; Berg, C. F. (2023). Polynomial Chaos Expansion for Uncertainty Quantification in Closed-Loop Reservoir Management. I: Proceedings of the 2023 IEEE Conference on Control Technology and Applications (CCTA). IEEE conference proceedings 2023 ISBN 979-8-3503-3544-6. p. 612-619.

  4. Diaa-Eldeen, T.; Hovd, M.; Berg, C. F. (2023). Spectral Methods for Stochastic Surrogate Modeling of Subsurface Flow Dynamics. The 22nd annual conference of the IAMG; 2023-08-05 - 2023-08-12.

  5. Hannanu, M. I.; Lima Silva, T.; Camponogara, E.; Hovd, M. (2023). Well Control Optimization with Output Constraint Handling by Means of a Derivative-Free Trust Region Algorithm. I: Abu Dhabi International Petroleum Exhibition & Conference 2023. Society of Petroleum Engineers 2023 ISBN 978-1-959025-07-8.  

  6. Ng, Cuthbert Shang Wui. (2023). Data-Driven Reservoir Modeling: Application of Proxy Models in Reservoir Management. Doctoral theses at NTNU; 2023:183. PDF

2022

  1. Andersen, Joakim Rostrup; Imsland, Lars Struen. (2022). Bilevel programming as a means of infinite weighting in regression problems. IFAC-PapersOnLine 2022; Volume 55.(7) s. 851-856. PDF

  2. Diaa-Eldeen, T.; Berg, C. F.; Hovd, M. (2022). Observability-Aware Ensemble Kalman Filter for Reservoir Model Updating. I: Proceedings of the European Control Conference 2022 (ECC 2022). IEEE conference proceedings 2022 ISBN 9781665497336. p. 1714-1721.

  3. Diaa-Eldeen, T.; Berg, C. F.; Hovd, M. (2022). System-Theoretic Ensemble Generation in Ensemble-Based History Matching. I: Proceedings of the European Conference on the Mathematics of Geological Reservoirs (ECMOR 2022). European Association of Geoscientists and Engineers (EAGE) 2022 ISBN 0-000-00001-9. p. 1-11.

  4. Fonseca Ivo, O.; Imsland, L. S. (2022). Economic and environmental impact of fouling in produced water re-injection. Computer-aided chemical engineering 2022; Volume 49. p. 1057-1062.  

  5. Fonseca Ivo, O.; Imsland, L. S. (2022). Framework for produced water discharge management with flow-weighted mean concentration based economic model predictive control. Computers and Chemical Engineering 2022; Volume 157. PDF

  6. Haring, Mark A. M.; Fossøy, Synne; Silva, Thiago Lima; Pavlov, Alexey. (2022). Nondisturbing extremum seeking control for multi-agent industrial systems. IEEE Transactions on Automatic Control. PDF

  7. Hotvedt, M., Grimstad, B., Ljungquist, D., & Imsland, L. (2022). On gray-box modeling for virtual flow metering. Control Engineering Practice, 118, 104974. PDF

  8. Hotvedt, Mathilde. (2022). On a hybrid approach to model learning applied to virtual flow metering. Doctoral theses at NTNU;2022:165. PDF

  9. Hotvedt, Mathilde; Grimstad, Bjarne Andre; Imsland, Lars Struen. (2022). Passive learning to address nonstationarity in virtual flow metering applications. Expert Systems with Applications. Volume 210, 30 December 2022, 118382. PDF

  10. Hotvedt, Mathilde; Grimstad, Bjarne Andre; Ljungquist, Dag; Imsland, Lars Struen. (2022). When is gray-box modeling advantageous for virtual flow metering? IFAC-PapersOnLine.Volume 55, Issue 7, 2022, Pages 520-525. PDF

  11. Ivo, O. F., & Imsland, L. S. (2022). Framework for produced water discharge management with flow-weighted mean concentration based economic model predictive control. Computers & Chemical Engineering, 157, 107604. PDF

  12. Kristoffersen, B. S., Bellout, M. C., Silva, T. L., & Berg, C. F. (2022). Reduced well path parameterization for optimization problems through machine learning. Journal of Petroleum Science and Engineering, 208, 109523. PDF

  13. Ng, C. S. W., Jahanbani Ghahfarokhi, A., & Nait Amar, M. (2022a). Production optimization under waterflooding with Long Short-Term Memory and metaheuristic algorithm. Petroleum. PDF

  14. Ng, C. S. W., Jahanbani Ghahfarokhi, A., & Nait Amar, M. (2022b). Well production forecast in Volve field: Application of rigorous machine learning techniques and metaheuristic algorithm. Journal of Petroleum Science and Engineering, 208, 109468. PDF

  15. Silva, Thiago Lima; Bellout, Mathias; Giuliani, Caio M.; Camponogara, Eduardo; Pavlov, Alexey. (2022). Derivative-free trust region optimization for robust well control under geological uncertainty. Computational Geosciences. 2022, 26 329-349. PDF 

2021

  1. Andersen, Joakim Rostrup; Imsland, Lars Struen. (2021). Application of Data-Driven Economic NMPC on a Gas Lifted Well Network. IFAC-PapersOnLine 2021; Volume 54.(3) s. 275-280. PDF

  2. Grimstad, Bjarne Andre; Hotvedt, Mathilde; Sandnes, Anders Thoresen; Kolbjørnsen, Odd; Imsland, Lars Struen. (2021). Bayesian neural networks for virtual flow metering: An empirical study. Applied Soft Computing 2021; Volume 112. PDF

  3. Hotvedt, Mathilde; Grimstad, Bjarne Andre; Imsland, Lars Struen. (2021). Identifiability and physical interpretability of hybrid, gray-box models - a case study. IFAC-PapersOnLine 2021; Volume 54.(3) s. 389-394. PDF

  4. Hotvedt, Mathilde; Grimstad, Bjarne Andre; Ljungquist, Dag; Imsland, Lars Struen. (2021). On gray-box modeling for virtual flow metering. Control Engineering Practice 2021 ;Volume 118. PDF

  5. Ivo, O. F., & Imsland, L. S. (2021). Analysis of Optimal Control Strategies for Efficient Operation of a Produced Water Reinjection Facility for Mature Fields. IFAC-PapersOnLine, 54(3), 115-121. PDF

  6. Kristoffersen, B. S., Bellout, M. C., Silva, T. L., & Berg, C. F. (2021). An Automatic Well Planner for Complex Well Trajectories. Mathematical Geosciences, 53(8), 1881-1905. PDF

  7. Kristoffersen, Brage Strand; Bellout, Mathias; Silva, Thiago Lima; Berg, Carl Fredrik. (2021). Reduced well path parameterization for optimization problems through machine learning. Journal of Petroleum Science and Engineering. 2021, 208. PDF

  8. Kristoffersen, Brage Strand; Silva, Thiago Lima; Bellout, Mathias; Berg, Carl Fredrik. (2021). Efficient well placement optimization under uncertainty using a virtual drilling procedure. Computational Geosciences. Volume 26, pages 739–756. PDF

  9. Ng, C. S. W., Jahanbani Ghahfarokhi, A., & Nait Amar, M. (2021). Application of nature-inspired algorithms and artificial neural network in waterflooding well control optimization. Journal of Petroleum Exploration and Production Technology, 11(7), 3103-3127. PDF

  10. Ng, C. S. W., Jahanbani Ghahfarokhi, A., Nait Amar, M., & Torsæter, O. (2021). Smart Proxy Modeling of a Fractured Reservoir Model for Production Optimization: Implementation of Metaheuristic Algorithm and Probabilistic Application. Natural Resources Research, 30(3), 2431-2462. PDF

  11. Silva, Thiago Lima; Pavlov, Alexey. (2021). Dither signals optimization in constrained multi-agent extremum seeking control. IFAC-PapersOnLine. 2021, 53 (2), 1633-1639. PDF 

2020

  1. Andersen, Joakim Rostrup; Silva, Thiago Lima; Imsland, Lars Struen; Pavlov, Alexey. (2020). Real time optimization of systems with fast and slow dynamics using a lookahead strategy. IEEE. PDF

  2. Hotvedt, M., Grimstad, B., & Imsland, L. (2020). Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter - a Case Study. IFAC-PapersOnLine, 53(2), 11692-11697. PDF

  3. Hulse, Eduardo O.; Silva, Thiago Lima; Camponogara, Eduardo; Rosa, Vinicius R.; Vieira, Bruno F.; Furtado, Alex Teixeira. (2020). Introducing Approximate Well Dynamics into Production Optimization for Operations Scheduling. Computers & Chemical Engineering. Volume 136, 8 May 2020, 106773. PDF

  4. J. R. Andersen, T. Lima Silva, L. Imsland and A. Pavlov. (2020). Real time optimization of systems with fast and slow dynamics using a lookahead strategy. 59th IEEE Conference on Decision and Control (CDC), pp. 2342-2349. PDF

  5. Kristoffersen, B. S., Silva, T., Bellout, M., & Berg, C. F. (2020). An Automatic Well Planner for Efficient Well Placement Optimization Under Geological Uncertainty. 2020(1), 1-16. PDF

  6. Silva, T. L., & Pavlov, A. (2020). Dither signals optimization in constrained multi-agent extremum seeking control. IFAC-PapersOnLine, 53(2), 1633-1639. PDF

  7. Silva, T., Bellout, M., Giuliani, C., Camponogara, E., & Pavlov, A. (2020). A Derivative-Free Trust-Region Algorithm for Well Control Optimization. 2020(1), 1-20. PDF

  8. Thiago Lima Silva, Alexey Pavlov. (2020). Dither signal optimization for multi-agent extremum seeking control. European Control Conference (ECC). PDF

2019

  1. Bellout, M., Baumann, E., Kristoffersen, B.S., Silva, T.L. (2019). FieldOpt platform for field development optimization. VII Oil and Gas Production Optimization Workshop, 29-30 April 2019, Rio de Janeiro, Brazil

  2. Silva, T.L., Bellout, M., Giuliani, C. M., Camponogara, E. (2019). Derivative-free algorithms and applications for production optimization. VIII Oil and Gas Production Optimization Workshop; 2019-04-29 - 2019-04-30

  3. Silva, T.L., Codas, A., Stanko, M., Camponogara, E., Foss, B.A. (2019). Network-Constrained Production Optimization by Means of Multiple Shooting. SPE Reservoir Evaluation and Engineering 2019, Volume 22(02), pp. 709-733. PDF

2024

  1. Tabella, G.; Ciuonzo, D.; Paltrinieri, N.; Salvo Rossi, P. (2024). Bayesian Fault Detection and Localization Through Wireless Sensor Networks in Industrial Plants. IEEE Internet of Things Journal 2024. PDF

  2. Teglasy, B. Z.; Wengle, J. E. H.; Potter, J. R.; Katsikas, S. (2024). Authentication of underwater assets. Computer Networks 2024; Volume 241. PDF

2023

  1. Islam, A. M. A.; Vatn, J. (2023). Condition-based multi-component maintenance decision support under degradation uncertainties. International Journal of System Assurance Engineering and Management 2023; Volume 14. p. 961-979. PDF 

  2. Machado, Mario; Lima Silva, Thiago; Camponogara, Eduardo; de Arruda, Edilson; Ferreira Filho, Virgílio. (2023). Optimal preventive policies for parallel systems using Markov decision process: application to an offshore power plant. EURO Journal on Decision Processes. 2023, 11: 100034. PDF

  3. Pedersen, Tom Ivar; Liu, Xingheng; Vatn, Jørn. (2023). Maintenance optimization of a system subject to two stage degradation, hard failure, and imperfect repair. Reliability Engineering & System Safety. Volume 237, September 2023, 109313. PDF

  4. Sølvsberg, E.; Arena, S.; Sgarbossa, F.; Schjølberg, P. (2023). Identifying Customer Returns in a Printed Circuit Board Production Line Using the Mahalanobis Distance. I: Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures IFIP WG 5.7 International Conference, APMS 2023, Trondheim, Norway, September 17–21, 2023, Proceedings, Part IV. Springer 2023 ISBN 978-3-031-43688-8. p. 426-438. 

  5. Spahic, R. (2023). Assessing the Influence of EU’s Upcoming Acts and Regulations on High-Risk AI System. An Analysis of Design, Implementation, Approval Processes and Usage. Trial lecture; 2023-08-29 - 2023-08-29. PDF

  6. Spahic, R. (2023). Risk-Informed Artificial Intelligence for Autonomous Subsea Pipeline Inspection. PhD Defense; 2023-08-29 - 2023-08-29. PDF

  7. Spahic, R.; Lundteigen, M. A.; Hepsø, V. (2023). Context-based and image-based subsea pipeline degradation monitoring. Discover Artificial Intelligence 2023; Volume 3. PDF

  8. Spahic, R.; Poolla, K.; Hepsø, V.; Lundteigen, M. A. (2023). A Novel Warning Identification Framework for Risk-Informed Anomaly Detection. Journal of Intelligent and Robotic Systems 2023; Volume 108. PDF

  9. Spahic, R.; Poolla, K.; Hepsø, V.; Lundteigen, M. A. (2023). Image-based and risk-informed detection of Subsea Pipeline damage. Discover Artificial Intelligence 2023; Volume 3. PDF

  10. Spahic, Rialda. (2023). Risk-Informed Artificial Intelligence for Autonomous Inspection on Subsea Pipelines. Doctoral theses at NTNU; 2023:245. PDF

  11. Tabella, G.; Ciuonzo, D.; Yilmaz, Y.; Wang, X.; Salvo Rossi, P. (2023). Time-Aware Distributed Sequential Detection of Gas Dispersion via Wireless Sensor Networks. IEEE Transactions on Signal and Information Processing over Networks 2023; Volume 9. p. 721-735. PDF

  12. Wan, P. K.; Sølvsberg, E.; Eleftheriadis, R.; Fragapane, G. (2023). The Effect of Digitalization and Human-Centric on Companies’ Production Performances. I: Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems: Proceedings of FAIM 2023, June 18–22, 2023, Porto, Portugal, Volume 2: Industrial Management. Springer 2023 ISBN 978-3-031-38165-2. p. 753-760.

2022

  1. de Oliveira, L. M.; da Silva Junior, I. C.; Santos, R. A. A. (2022). Search Space Reduction for the Thermal Unit Commitment Problem through a Relevance Matrix. Energies 2022; Volume 15.(19). PDF

  2. Islam, A. M. A.; Vatn, J. (2022). A Survey of Multi-Component Maintenance Optimization Subject to Condition-Based Maintenance. I: Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022). Research Publishing Services 2022 ISBN 978-981-18-5183-4.

  3. Pedersen, Tom Ivar. (2022). Use and development of quantitative models for maintenance decisions in the oil and gas industry on the Norwegian Continental Shelf. Doctoral theses at NTNU;2022:388. PDF

  4. Pedersen, Tom Ivar; Vatn, Jørn. (2022). Optimizing a condition-based maintenance policy by taking the preferences of a risk-averse decision maker into account. Reliability Engineering & System Safety 2022; Volume 228. PDF

  5. Petrovic, B.; Teglasy, B. Z.; Katsikas, S. (2022). Authenticated Encryption for Janus-Based Acoustic Underwater Communication. I: Proceedings, XVII reunión española sobre criptología y seguridad de la información (RECSI 2022). : Ediciones Universidad Cantabria 2022 ISBN 978-84-19024-14-5. p. 180-185. PDF

  6. Spahic, R.; Hepsø, V.; Lundteigen, M. A. (2022). Using Risk Analysis for Anomaly Detection for Enhanced Reliability of Unmanned Autonomous Systems. I: Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022). Research Publishing Services 2022 ISBN 978-981-18-5183-4. p. 273-280. PDF

  7. Spahic, R.; Lundteigen, M. A. (2022). Manually or Autonomously Operated Drones: Impact on Sensor Data towards Machine Learning. I: 2022 IEEE 9th International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA). IEEE conference proceedings 2022 ISBN 978-1-6654-3445-4. PDF

  8. Spahic, R.; Lundteigen, M. A.; Hepsø, V. (2022). Enhancing Autonomous Systems’ Awareness: Conceptual Categorization of Anomalies by Temporal Change During Real-Time Operations. I: The Eighteenth International Conference on Autonomic and Autonomous Systems. International Academy, Research and Industry Association (IARIA) 2022 ISBN 9781612089669. p. 25-30. PDF

  9. Tabella, G.; Di Martino, Y.; Ciuonzo, D.; Paltrinieri, N.; Wang, X.; Salvo Rossi, P. (2022). Decision Fusion for Carbon Dioxide Release Detection from Pressure Relief Devices. Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop 2022 p. 46-50. PDF

  10. Tabella, G.; Di Martino, Y.; Ciuonzo, D.; Paltrinieri, N.; Wang, X.; Salvo Rossi, P. (2022). Sensor Fusion for Detection and Localization of Carbon Dioxide Releases for Industry 4.0. I: 2022 25th International Conference on Information Fusion - FUSION. IEEE (Institute of Electrical and Electronics Engineers) 2022 ISBN 978-1-7377497-2-1. PDF

  11. Teglasy, B. Z.; Katsikas, S.; Lundteigen, M. A. (2022). Standardized Cyber Security Risk Assessment for Unmanned Offshore Facilities. I: Proceedings, 3rd International Workshop on Engineering and Cybersecurity of Critical Systems (ENCYCRIS 2022). Association for Computing Machinery (ACM) 2022 ISBN 978-1-6654-6225-9. p. 33-40.

2021

  1. G. Tabella, N. Paltrinieri, V. Cozzani and P. S. Rossi. (2021). Wireless Sensor Networks for Detection and Localization of Subsea Oil Leakages. IEEE Sensors Journal, vol. 21, no. 9, pp. 10890-10904. PDF

  2. Pedersen, Tom Ivar & Haskins, Cecilia. (2021). Framework for the Implementation of Smart Maintenance. 1347-1354. Conference: Proceedings of the 31st European Safety and Reliability Conference. PDF

  3. Pedersen, Tom Ivar; Størdal, Håkon Grøtt; Bjørnebekk, Håvard Holm; Vatn, Jørn. (2021).  A Survey on the Use of Digital Twins for Maintenance and Safety in the Offshore Oil and Gas Industry. I: Proceedings of the 31st European Safety and Reliability Conference. Research Publishing Services 2021 ISBN 978-981-18-2016-8. PDF

  4. R. Spahić, V. Hepsø and M. A. Lundteigen. (2021). Reliable Unmanned Autonomous Systems: Conceptual Framework for Warning Identification during Remote Operations. IEEE International Symposium on Systems Engineering (ISSE), pp. 1-8. PDF

  5. Rødseth H., Sølvsberg E., Steine A., Schjølberg P., Henriksen-Polanscak E. (2021) A Holistic Approach to PLI in Smart Maintenance Towards Sustainable Manufacturing. In: Dolgui A., Bernard A., Lemoine D., von Cieminski G., Romero D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 633. Springer, Cham. 

  6. Tabella, Gianluca & Ciuonzo, Domenico & Paltrinieri, Nicola & Salvo Rossi, Pierluigi. (2021). Spatio-Temporal Decision Fusion for Quickest Fault Detection Within Industrial Plants: The Oil and Gas Scenario. Institute of Electrical and Electronics Engineers (IEEE). PDF

2020

  1. Ewa Maria Laskowska, Jørn Vatn. (2020). Degradation modelling using a Phase Type Distribution (PHD). 30th European Safety and Reliability Conference (ESREL 2020 PSAM15). PDF

  2. G. Tabella, N. Paltrinieri, V. Cozzani and P. S. Rossi. (2020). Data Fusion for Subsea Oil Spill Detection Through Wireless Sensor Networks. IEEE SENSORS, 2020, pp. 1-4. PDF

  3. Islam, Abu Md Ariful; Vatn, Jørn. (2020). Condition-based maintenance model for a single component subject to long preparation time and limited maintenance opportunities. E-proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15). PDF

  4. Islam, Abu Md Ariful; Vatn, Jørn. (2020). Data Analysis to Facilitate Offshore Seawater Ultrafiltration Membrane Replacement Decision and Scheduling of Chemical Wash. E-proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15). PDF

  5. Pedersen, Tom Ivar; Schjølberg, Per. (2020). The Economic Dimension of Implementing Industry 4.0 in Maintenance and Asset Management. I: Advanced manufacturing and automation IX. Springer 2020 ISBN 9789811523410. s. 299-306 Kingdom: Springer, Singapore; 2020. p. 299-306.  This paper is not included due to copyright restrictions. Please contact Tom Ivar Pedersen for the conference paper.

  6. Pedersen, Tom Ivar; Vatn, Jørn; Jørgensen, Kim. (2020). Degradation Modelling of Centrifugal Pumps as Input to Predictive Maintenance. I: e-proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15). Research Publishing Services 2020 ISBN 9789811485930. PDF

  7. Tabella, Gianluca & Paltrinieri, Nicola & Cozzani, Valerio & Salvo Rossi, Pierluigi. (2020). Subsea Oil Spill Risk Management Based on Sensor Networks. Chemical Engineering Transactions. 82. 199-204. PDF

  8. Teglasy, Balint & Gran, Bjørn & Katsikas, Sokratis & Gkioulos, Vasileios & Lundteigen, Mary. (2020). Clarification of the Cybersecurity and Functional Safety Interrelationship in Industrial Control Systems: Barrier Concepts and Essential Functions. 1980-1987.

2019

  1. Ewa Maria Laskowska, Jørn Vatn. State modelling and prognostics of safety valves used in the oil and gas industry. Proceedings of the 29th European Safety and Reliability Conference (ESREL 2019) Hannover, Germany. PDF

  2. Islam, Abu Md Ariful; Srivastav, Himanshu; Vatn, Jørn; Barros, Anne; Lundteigen, Mary Ann. (2019). Time-dependent Unavailability Assessment of Final Element of Safety Instrumented Systems- an Application of Multiphase Markov Process. Proceedings of the 29th European Safety and Reliability Conference(ESREL). 22 – 26 September 2019 Hannover, Germany.

  3. Schulze, F. S., Dalle A.G; Imsland, L.S., Harjunkoski, I. (2019). Optimal Maintenance Scheduling for Washing of Compressors to Increase Operational Efficiency. Computer-aided chemical engineering, Volume 46. pp.1321-1326.

2024

  1. Korotkova, N.; Lilliesköld, J.; Hetemi, E. (2024). Pursuing openness in the digital age: Insights from client–contractor knowledge collaboration at the project front end. International Journal of Project Management 2024; Volume 42.(1). PDF

2023

  1. Korotkova, N.; Benders, J. G.; Mikalef, P.; Cameron, D. (2023). Maneuvering between skepticism and optimism about hyped technologies: Building trust in digital twins. Information & Management 2023; Volume 60.(4). PDF

  2. Korotkova, N.; Lilliesköld, J.; Hetemi, E. (2023). Chasing the Openness Ghost in the Digital Age: Insights from Client–Contractor Knowledge Collaboration at the Project Front End. the European Academy of Management Conference (EURAM 2023); 2023-06-14 - 2023-06-16.

2022

  1. Joyce, E.; Yan, T.; Qi, J.; Korotkova, N.; Khalil, S. (2022). Bourdieu’s Practice Theory as Framework for Grasping Organizational Change: A Case Study in China. Academy of Management Proceedings 2022. PDF

  2. Monteiro E. (2022). Digital Oil: Machineries of Knowing.

  3. Spahic, R.; Hepsø, V.; Lundteigen, M. A. (2022). Using Risk Analysis for Anomaly Detection for Enhanced Reliability of Unmanned Autonomous Systems. I: Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022). Research Publishing Services 2022 ISBN 978-981-18-5183-4. p. 273-280. PDF

  4. Spahic, R.; Lundteigen, M. A. (2022). Manually or Autonomously Operated Drones: Impact on Sensor Data towards Machine Learning. I: 2022 IEEE 9th International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA). IEEE conference proceedings 2022 ISBN 978-1-6654-3445-4. PDF

  5. Spahic, R.; Lundteigen, M. A.; Hepsø, V. (2022). Enhancing Autonomous Systems’ Awareness: Conceptual Categorization of Anomalies by Temporal Change During Real-Time Operations. I: The Eighteenth International Conference on Autonomic and Autonomous Systems. International Academy, Research and Industry Association (IARIA) 2022 ISBN 9781612089669. p. 25-30. PDF

  6. Yan, T.; Qi, J.; Khalil, S.; Korotkova, N.; Joyce, E. (2022). Untangling Organizational Change in a Chinese State-Owned Company: A Grounded Theory Case Study. Academy of Management Proceedings 2022. PDF

2021

  1. Emmanuel Monod, Alan Eisner, Elisabeth Joyce, Antonia Koester, Nataliia Korotkova, Deli Kong (2021). Digital transformation consulting: Toward a model of Human-Digital Competitiveness for digital transformation: Evidence from companies in China. Network and Information Security Journal. Issue 11, p.34-41.

  2. Hepsø, Vidar & Monteiro, Eric (2021). From Integrated Operations to Remote Operations: Socio-technical Challenge for the Oil and Gas Business. In Black, Nancy; Neumann, Patrick & Noy, Ian (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021). Springer Nature. ISSN 978-3-030-74601-8. p. 169–176.

  3. Khalil, S., Monod, E., Joyce, E., Bonnet, M., Korotkova, N., & Köster, A. (2021). THE RETURN ON DIGITAL TRANSFORMATION: A HOLISTIC PERFORMANCE SYSTEM BASED ON HIDDEN COST THEORY FOR BRINGING VALUE BACK TO DIGITAL TRANSFORMATION CONSULTING. PDF

  4. Monod, E., Koester, A., Joyce, E., Korotkova, N. & Khalil, K. (2021). The Return on Digital Transformation: A holistic performance system based on hidden cost theory. 10th International conference and doctoral consortium AOM Division MC/ ISODC/ Le CNAM / ISEOR, online, 9 & 10 June, 2021. PDF

  5. Monod, E.; Köster, A.; Joyce, E.; Korotkova, N.. (2021). Digital Transformation Consulting: Toward a Human-Technology Performance Model. Academy of Management Proceedings 2021. PDF

  6. Schiefloe P. M. (2021). Organisasjonsanalyse.

  7. Xing, Y.; Mohallick, I.; Gulla, J. A.; Özgöbek, Ö.; Zhang, L. (2021). An Educational News Dataset for Recommender Systems. Communications in Computer and Information Science (CCIS) 2021; Volume 1323. p. 562-570. PDF

2020

  1. Xing, Y., Mohallick, I., Gulla, J. A., Özgöbek, Ö., & Zhang, L. (2020). An Educational News Dataset for Recommender Systems. In I. Koprinska et al. (Eds.): ECML PKDD 2020 Workshops, CCIS 1323, pp. 562–570. PDF

2019

  1. Korotkova, N., Horn, M. (2019). Betydningen av tillit 4.0 og kommunikasjon 4.0 i tidsalderen for digitale organisasjoner. NEON-konferansen, 26-28 November 2019, Lillehammer, Norway.

  2. Korotkova, N., Horn, M. (2019). What does the concept of trust mean in the age of digital organizations?. Production of Participation in the Digital World Workshop, 12-13 December 2019, Trondheim, Norway.

  3. Korotkova, N., Mohallick, I., Schiefloe, P.M. (2019). OASIS, the IFIP Working Group 8.2 Research Workshop. 14 December 2019, Munich, Germany.

  4. Monteiro, E. (2019). Digital oil. Distinguished scholar lecture, Warwich Business School, March 2019.

  5. Monteiro,E., Parmiggiani, E. (2019). Synthetic Knowing: The Politics of the Internet of Things. MIS Quarterly Volume 43(1), pp. 167-184. PDF