A Review of Subsidence Monitoring Techniques in Offshore Environments
Abstract
:1. Introduction
2. Materials and Methods
Technique | Section | Analyzed References |
---|---|---|
Direct measurement techniques | Section 3.1 | |
Hydrostatic leveling | Section 3.1.1 | [24,25,26,27] |
Casing collar deformation analysis | Section 3.1.2 | [28,29] |
Hydrographic techniques | Section 3.2 | |
Bathymetry | Section 3.2.1 | [30,31,32,33] |
Air gap measurements | Section 3.2.2 | [33,34,35] |
Radar water-level measurements | Section 3.2.3 | [33,36] |
Radioactive marker technique (RMT) | Section 3.3 | [8,37,38,39,40] |
Well logging | Section 3.4 | |
Electric log data | Section 3.4.1 | [41] |
Formation–compaction monitoring tool (FCMT) | Section 3.4.2 | [42] |
Tiltmeters | Section 3.5 | [43,44,45,46,47] |
Fiber optic cables | Section 3.6 | [48] |
Fugro-proposed tools | Section 3.6.1 | [43] |
Fiber Bragg grating (FBG) strain sensor | Section 3.6.2 | [43,49] |
Time-lapse gravimetry and pressure | Section 3.7 | [43,50,51,52,53,54,55,56] |
Agisco compensator | Section 3.8 | [43] |
Microelectromechanical systems (MEMSs) | Section 3.9 | [57,58,59] |
Remote sensing | Section 3.10 | |
InSAR (interferometric synthetic aperture RADAR) | Section 3.10.1 | [20,60,61,62,63,64,65,66,67,68,69] |
GNSS (global navigation satellite system) time series | Section 3.10.2 | [11,20,70,71,72,73,74,75,76,77,78] |
GNSS on an anchored spar buoy | GNSS on an Anchored Spar Buoy | [79] |
Bottom pressure recorder + GNSS (MEDUSA System) | Bottom Pressure Recorder + GNSS (MEDUSA System) | [80,81,82,83] |
3. Offshore Subsidence Monitoring Systems
3.1. Direct Measurement Techniques
3.1.1. Hydrostatic Leveling
3.1.2. Casing Collar Deformation Analysis
3.2. Hydrographic Techniques
3.2.1. Bathymetry
3.2.2. Air Gap Measurements
3.2.3. Radar Water-Level Measurements
3.3. Radioactive Marker Technique (RMT)
3.4. Well Logging
3.4.1. Electric Log Data
3.4.2. Formation–Compaction Monitoring Tool (FCMT)
3.5. Tiltmeters
3.6. Fiber Optic Cables
3.6.1. Fugro-Proposed Tools
- Strain-based cable shape determination: A pivotal facet of subsea cable deployment involves the arrangement of cylindrical cables (Figure 8) within trenches on the seabed. Ensuring the cable’s capacity for torque during installation is essential. Accurate strain measurements are crucial for precisely assessing and documenting this torque phenomenon.
- Cable inclination measurement: In scenarios where specific cable sections undergo vertical displacement, the inclination of contiguous segments immediately preceding and succeeding the affected region experiences corresponding adjustments.
- Pressure measurement: The vertical movement of a cable section engenders modifications in the pressure within the particular segment relative to pressure levels observed in other cable regions.
3.6.2. Fiber Bragg Grating (FBG) Strain Sensor
3.7. Time-Lapse Gravimetry and Pressure
3.8. Agisco Compensator
3.9. Microelectromechanical Systems (MEMSs)
3.10. Remote Sensing
3.10.1. InSAR (Interferometric Synthetic Aperture RADAR)
3.10.2. GNSS (Global Navigation Satellite System) Time Series
GNSS on an Anchored Spar Buoy
Bottom Pressure Recorder + GNSS (MEDUSA System)
4. Case Studies
4.1. Ekofisk Field, Norway
4.2. Anga, Italy
4.3. Valhall Field, Norway
5. Discussion
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Clarke, L.; Wei, Y.M.; De la Vega Navarro, A.; Garg, A.; Hahmann, A.N.; Khennas, S.; Azevedo, I.M.L.; Löschel, A.; Singh, A.K.; Steg, L.; et al. Energy systems. In Climate Change 2022: Mitigation of Climate Change. Working Group III Contribution to the IPCC Sixth Assessment Report; Cambridge University Press: Cambridge, UK, 2022; pp. 613–746. [Google Scholar]
- Harichandan, S.; Kar, S.K.; Bansal, R.; Mishra, S.K.; Balathanigaimani, M.S.; Dash, M. Energy transition research: A bibliometric mapping of current findings and direction for future research. Clean. Prod. Lett. 2022, 3, 100026. [Google Scholar] [CrossRef]
- IEA. The Oil and Gas Industry in Energy Transitions; IEA: Paris, France, 2020; Licence: CC BY 4.0.; Available online: https://www.iea.org/reports/the-oil-and-gas-industry-in-energy-transitions (accessed on 11 November 2023).
- Ozili, P.K.; Ozen, E. Global energy crisis: Impact on the global economy. In Proceedings of the IAC in Budapest 2021; Czech Institute of Academic Education: Prague, Czech Republic, 2021; Volume 1, pp. 85–89. [Google Scholar]
- Litvinenko, V. The role of hydrocarbons in the global energy agenda: The focus on liquefied natural gas. Resources 2020, 9, 59. [Google Scholar] [CrossRef]
- Christie, E. Oil and Gas Dependence of EU-15 Countries (Research Report 343). wiiw Research Report. 2007. Available online: https://www.econstor.eu/handle/10419/204115 (accessed on 28 October 2023).
- Ringrose, P.S. The CCS hub in Norway: Some insights from 22 years of saline aquifer storage. Energy Procedia 2018, 146, 166–172. [Google Scholar] [CrossRef]
- Nagel, N.B. Compaction and subsidence issues within the petroleum industry: From wilmington to ekofisk and beyond. Phys. Chem. Earth Part A Solid Earth Geod. 2001, 26, 3–14. [Google Scholar] [CrossRef]
- Pszonka, J.; Godlewski, P.; Fheed, A.; Dwornik, M.; Schulz, B.; Wendorff, M. Identification and quantification of intergranular volume using SEM automated mineralogy. Mar. Pet. Geol. 2024, 162, 106708. [Google Scholar] [CrossRef]
- Sulak, A.M.; Danielsen, J. Reservoir Aspects of Ekofisk Subsidence. In Proceedings of the Offshore Technology Conference, Houston, TX, USA, 2–5 May 1998. [Google Scholar] [CrossRef]
- Myint, K.C.; Matori, A.N.; Gohari, A. Application of GNSS Methods for Monitoring Offshore Platform Deformation. E3S Web Conf. 2018, 34, 01019. [Google Scholar] [CrossRef]
- Gebara, J.M.; Dolan, D.; Pawsey, S.; Jeanjean, P.; Dahl-Stamnes, K. Assessment of Offshore Platforms Under Subsidence—Part I: Approach. J. Offshore Mech. Arctic Eng. 2000, 122, 260–266. [Google Scholar] [CrossRef]
- Sulak, R.M. Ekofisk field: The first 20 years. J. Pet. Technol. 1991, 43, 1265–1271. [Google Scholar] [CrossRef]
- National Commission on the BP Deepwater Horizon Oil Spill and Offshore Dril. Deep Water: The Gulf Oil Disaster and the Future of Offshore Drilling: Report to the President, January 2011: The Gulf Oil Disaster and the Future of Offshore Drilling; Government Printing Office: Washington, DC, USA, 2011. [Google Scholar]
- Norse, E.A.; Amos, J. Impacts, Perception, and Policy Implications of the Deepwater Horizon Oil and Gas Disaster. Environ. Law Report. News Anal. 2010, 40, 11058–11073. [Google Scholar]
- Keranen, K.M.; Weingarten, M. Induced Seismicity. Annu. Rev. Earth Planet. Sci. 2018, 46, 149–174. [Google Scholar] [CrossRef]
- Li, H.; Son, J.-H.; Hanif, A.; Gu, J.; Dhanasekar, A.; Carlson, K. Colorado Water Watch: Real-Time Groundwater Monitoring for Possible Contamination from Oil and Gas Activities. J. Water Resour. Prot. 2017, 9, 1660–1687. [Google Scholar] [CrossRef]
- Kuzmin, Y.O. Deformation Consequences of the Development of Oil and Gas Field. Izv. Atmos. Ocean. Phys. 2021, 57, 1479–1497. [Google Scholar] [CrossRef]
- Brkić, D.; Praks, P. Probability Analysis and Prevention of Offshore Oil and Gas Accidents: Fire as a Cause and a Consequence. Fire 2021, 4, 71. [Google Scholar] [CrossRef]
- Polcari, M.; Secreti, V.; Anderlini, L.; Albano, M.; Palano, M.; Serpelloni, E.; Stramondo, S.; Trasatti, E.; Pezzo, G. Multi-technique geodetic detection of onshore and offshore subsidence along the Upper Adriatic Sea coasts. Int. J. Appl. Earth Obs. Geoinf. 2022, 108, 102756. [Google Scholar] [CrossRef]
- Setan, H.; Othman, R. Monitoring of Offshore Platform Subsidence Using Permanent GPS Stations. J. Glob. Position. Syst. 2006, 5, 17–21. [Google Scholar] [CrossRef]
- Herwanger, J. Seismic Geomechanics: How to Build and Calibrate Geomechanical Models Using 3D and 4D Seismic Data. cp-439-00001. 2014. Available online: https://www.earthdoc.org/content/papers/10.3997/2214-4609-pdb.439.EET-V_Slides_SeismicGeomechanics_JorgHerwanger_EAGE-Website_ (accessed on 18 October 2023).
- Pierce, R.L. Reducing land subsidence in the wilmington oil field by use of saline waters. Water Resour. Res. 1970, 6, 1505–1514. [Google Scholar] [CrossRef]
- Finol, A.S.; Sancevic, Z.A. Chapter 7 Subsidence in Venezuela. In Developments in Petroleum Science; Chilingarian, G.V., Donaldson, E.C., Yen, T.F., Eds.; Elsevier: Amsterdam, The Netherlands, 1995; Volume 41, pp. 337–372. [Google Scholar] [CrossRef]
- Fokker, P.A.; Van Leijen, F.J.; Orlic, B.; Van der Marel, H.; Hanssen, R.F. Subsidence in the Dutch Wadden Sea. Neth. J. Geosci. 2018, 97, 129–181. [Google Scholar] [CrossRef]
- Fokker, P.A.; Visser, K.; Peters, E.; Kunakbayeva, G.; Muntendam-Bos, A.G. Inversion of surface subsidence data to quantify reservoir compartmentalization: A field study. J. Pet. Sci. Eng. 2012, 96–97, 10–21. [Google Scholar] [CrossRef]
- Vonhögen-Peeters, L.M.; Van Heteren, S.; Wiersma, A.P.; De Kleine, M.P.E.; Marges, V.C. Quantifying sediment dynamics within the Dutch Wadden Sea using bathymetric monitoring series. J. Coast. Res. 2013, 65, 1611–1616. [Google Scholar] [CrossRef]
- Allen, D.R. Physical changes of reservoir properties caused by subsidence and repressuring operations, Wilmington Field, California. In Proceedings of the Annual SPE of AIME Fall Meeting, Houston, TX, USA, 1 October 1967. [Google Scholar]
- Allen, D.R. Developments in Precision Casing Joint and Radioactive Bullet Measurements for Compaction Monitoring; No. CONF-810321; Dept Oil Prop: Long Beach, CA, USA, 1981. [Google Scholar]
- Zaradkiewicz, P.; Eriksson, E.; Christian, P.; Klemm, H.; Hickman, P. Time-Lapse Bathymetry Processing for Seabed Subsidence Monitoring. In Proceedings of the 80th EAGE Conference and Exhibition 2018, Copenhagen, Denmark, 11–14 June 2018. [Google Scholar] [CrossRef]
- Kearns, T.A.; Breman, J. Bathymetry-The Art and Science of Seafloor Modeling for Modern Applications; Ocean Globe: 2010; pp. 1–36.
- Wu, Z.; Yang, F.; Tang, Y.; Wu, Z.; Yang, F.; Tang, Y. Multi-beam Bathymetric Technology. In High-Resolution Seafloor Survey and Applications; Springer: Singapore, 2021; pp. 21–76. [Google Scholar]
- Rentsch, H.C.; Mes, M.J. Measurement of Ekofisk Subsidence. In Proceedings of the Offshore Technology Conference, Houston, TX, USA, 2–5 May 1998. OTC-5619-MS. [Google Scholar] [CrossRef]
- Anokhin, V.; Ewans, K. Estimating Storm Surge and Reservoir Subsidence of Offshore Platforms Using WaveRadar REX SAAB Sensors. In Proceedings of the Offshore Technology Conference Asia, Kuala Lumpur, Malaysia, 20–23 March 2018. [Google Scholar] [CrossRef]
- Ewans, K.; Feld, G.; Jonathan, P. On wave radar measurement. Ocean Dyn. 2014, 64, 1281–1303. [Google Scholar] [CrossRef]
- Fulford, J.M.; Ester, L.W.; Heaton, J.W. Accuracy of radar water level measurements. In Proceedings of the Role of Irrigation and Drainage in a Sustainable Future: USCID Fourth International Conference on Irrigation and Drainage, Sacramento, CA, USA, 3–6 October 2007; p. 1063. [Google Scholar]
- Green, D.E. Subsidence Monitoring in the Gulf Coast. In Proceedings of the SPE Annual Technical Conference and Exhibition, Dallas, TX, USA, 6–9 October 1991. [Google Scholar] [CrossRef]
- Ferronato, M.; Frigo, M.; Gazzola, L.; Teatini, P.; Zoccarato, C. On the radioactive marker technique for in-situ compaction measurements: A critical review. Proc. IAHS 2020, 382, 83–87. [Google Scholar] [CrossRef]
- Banks, J.; Tourny, D.; Shotton, P.; Sampson, T. Radioactive Depth Marker Emplacement and Survey for Early Subsurface Geomechanical Model Calibration: Learnings from a Successful Ultra-HPHT Deployment. SPE Prod. Oper. 2021, 36, 455–467. [Google Scholar] [CrossRef]
- Macini, P.; Mesini, E. Measuring Reservoir Compaction Through Radioactive Marker Technique. J. Energy Resour. Technol. 2002, 124, 269–275. [Google Scholar] [CrossRef]
- Menghini, M.L. Compaction monitoring in the Ekofisk area chalk fields. In Offshore Technology Conference; OnePetro: Richardson, TX, USA, 1988. [Google Scholar]
- De Kook, A.J.; Hagiwara, T.; Zea, H.; Santa, F. A New Approach to Formation Compaction Monitoring in A Giant Deepwater Gom Oil and Gas Field Development. In Proceedings of the SPWLA 38th Annual Logging Symposium, Houston, TX, USA, 15–18 June 1997. [Google Scholar]
- Miandro, R.; Dacome, C.; Mosconi, A.; Roncari, G. Subsidence monitoring system for offshore applications: Technology scouting and feasibility studies. Proc. Int. Assoc. Hydrol. Sci. 2015, 372, 323–330. [Google Scholar] [CrossRef]
- Anderson, G.; Constable, S.; Staudigel, H.; Wyatt, F. A seafloor long-baseline tiltmeter. J. Geophys. Res. 1997, 1022, 20269–20286. [Google Scholar] [CrossRef]
- Fabian, M.; Villinger, H. The Bremen ocean bottom tiltmeter (OBT)—A technical article on a new instrument to monitor deep sea floor deformation and seismicity level. Mar. Geophys. Res. 2007, 28, 13–26. [Google Scholar] [CrossRef]
- Temizel, C.; Kirmaci, H.; Inceisci, T.; Wijaya, Z.; Balaji, K.; Suhag, A.; Ranjith, R.; Tran, M.; Al-Otaibi, B.; AlKouh, A.; et al. An Approach to Mitigate Subsidence in Soft Rocks through Coupling Surface Tiltmeter and Injection/Production Data. In Proceedings of the SPE Heavy Oil Conference and Exhibition, Kuwait City, Kuwait, 6–8 December 2016. [Google Scholar] [CrossRef]
- Wolhart, S.; Davis, E.; Roadarmel, W.; Wright, C. Reservoir deformation monitoring to enhance reservoir characterization and management. In Proceedings of the SEG International Exposition and Annual Meeting, Houston, TX, USA, 6–11 November 2005; p. SEG-2005. [Google Scholar]
- Hornby, B.E.; Barkved, O.I.; Askim, O.J.; Bostick, F.X., III; Williams, B.A. Permanent Fiber-Optic Borehole Seismic Installation and Imaging at Valhall. In Proceedings of the 69th EAGE Conference and Exhibition Incorporating SPE EUROPEC 2007, London, UK, 11–14 June 2007. [Google Scholar] [CrossRef]
- Liu, H.; Zhu, Z.; Zheng, Y.; Liu, B.; Xiao, F. Experimental study on an FBG strain sensor. Opt. Fiber Technol. 2018, 40, 144–151. [Google Scholar] [CrossRef]
- Ruiz, H.; Agersborg, R.; Hille, L.; Lindgård, J.E.; Lien, M.; Vatshelle, M. Monitoring offshore reservoirs using 4D gravity and subsidence with improved tide corrections. In SEG Technical Program Expanded Abstracts; Society of Exploration Geophysicists: Houston, TX, USA, 2016; pp. 2946–2950. [Google Scholar] [CrossRef]
- Alnes, H.; Eiken, O.; Stenvold, T. Monitoring gas production and CO2 injection at the Sleipner field using time-lapse gravimetry. Geophysics 2008, 73, WA155–WA161. [Google Scholar] [CrossRef]
- Barkved, O.; Heavey, P.; Kjelstadli, R.; Kleppan, T.; Kristiansen, T.G. Valhall Field—Still on Plateau after 20 Years of Production. In Proceedings of the SPE Offshore Europe Oil and Gas Exhibition and Conference, Aberdeen, UK, 2–5 September 2003. [Google Scholar] [CrossRef]
- Eiken, O.; Stenvold, T.; Alnes, H. Accurate Measurements of Seabed Subsidence Above Norwegian Gas Fields. First Break 2022, 40, 75–78. [Google Scholar] [CrossRef]
- Ruiz, H.; Lien, M.; Vatshelle, M.; Alnes, H.; Haverl, M.; Sørensen, H. Monitoring the Snøhvit gas field using seabed gravimetry and subsidence. First Break 2022, 40, 93–96. [Google Scholar] [CrossRef]
- Ruiz, H.; Seregin, A.; Skogly, O.P.; Libak, A.; Lien, M. Accurate Measurement of Seabed Subsidence at the Ormen Lange Field. In Proceedings of the EAGE 2020 Annual Conference and Exhibition Online, Online, 8–11 December 2020; pp. 1–5. [Google Scholar] [CrossRef]
- Stenvold, T.; Eiken, O.; Zumberge, M.A.; Sasagawa, G.S.; Nooner, S.L. High-Precision Relative Depth and Subsidence Mapping from Seafloor Water-Pressure Measurements. SPE J. 2006, 11, 380–389. [Google Scholar] [CrossRef]
- Xu, C.; Chen, J.; Zhu, H.; Zhang, P.; Ren, Z.; Zhu, H.; Lin, Y. Design and laboratory testing of a MEMS accelerometer array for subsidence monitoring. Rev. Sci. Instrum. 2018, 89, 085103. [Google Scholar] [CrossRef] [PubMed]
- Ge, Y.Q.; Chen, J.W.; Cao, C.; He, J.M.; Zhou, P.; Gao, F.; Xu, C.Y. Development and Sea Trial of the Terrain Monitoring Device Based on MEMS Sensing Array. IOP Conf. Ser. Earth Environ. Sci. 2021, 861, 072008. [Google Scholar] [CrossRef]
- Chen, J.; Cao, C.; Ge, Y.; Zhu, H.; Xu, C.; Sheng, Y.; Tian, L.; Zhang, H. Experimental Research on Data Synchronous Acquisition Method of Subsidence Monitoring in Submarine Gas Hydrate Mining Area. Sensors 2019, 19, 4319. [Google Scholar] [CrossRef]
- Lu, Z.; Kwoun, O.; Rykhus, R. Interferometric Synthetic Aperture Radar (InSAR): Its Past, Present and Future. Photogramm. Eng. Remote Sens. 2007, 73, 217–221. [Google Scholar]
- Osmanoğlu, B.; Sunar, F.; Wdowinski, S.; Cabral-Cano, E. Time series analysis of InSAR data: Methods and trends. ISPRS J. Photogramm. Remote Sens. 2016, 115, 90–102. [Google Scholar] [CrossRef]
- Ferretti, A.; Prati, C.; Rocca, F. Permanent scatterers in SAR interferometry. IEEE Trans. Geosci. Remote Sens. 2001, 39, 8–20. [Google Scholar] [CrossRef]
- Hooper, A.; Zebker, H.; Segall, P.; Kampes, B. A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers. Geophys. Res. Lett. 2004, 31. [Google Scholar] [CrossRef]
- Berardino, P.; Fornaro, G.; Lanari, R.; Sansosti, E. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Trans. Geosci. Remote Sens. 2002, 40, 2375–2383. [Google Scholar] [CrossRef]
- Lanari, R.; Mora, O.; Manunta, M.; Mallorquí, J.J.; Berardino, P.; Sansosti, E. A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms. IEEE Trans. Geosci. Remote Sens. 2004, 42, 1377–1386. [Google Scholar] [CrossRef]
- Ferretti, A.; Fumagalli, A.; Novali, F.; Prati, C.; Rocca, F.; Rucci, A. A new algorithm for processing interferometric data-stacks: SqueeSAR. IEEE Trans. Geosci. Remote Sens. 2011, 49, 3460–3470. [Google Scholar] [CrossRef]
- Matori, A.N.; Ab Latip, A.S.; Harahap, I.S.H.; Perissin, D. Deformation Monitoring of Offshore Platform Using the Persistent Scatterer Interferometry Technique. Appl. Mech. Mater. 2014, 567, 325–330. [Google Scholar] [CrossRef]
- Ab Latip, A.S.; Matori, A.; Aobpaet, A.; Din, A.H.M. Monitoring of offshore platform deformation with stanford method of Persistent Scatterer (StaMPS). In Proceedings of the 2015 International Conference on Space Science and Communication (IconSpace), Langkawi, Malaysia, 10–12 August 2015; pp. 79–83. [Google Scholar] [CrossRef]
- Latip, A.S.A.; Balogun, A.-L.; Din, A.H.M.; Ansar, A.M.H. The Use of InSAR for Monitoring Deformation of Offshore Platforms. IOP Conf. Ser. Earth Environ. Sci. 2021, 767, 012033. [Google Scholar] [CrossRef]
- Mes, M.J. Ekofisk reservoir pressure drops and seabed subsidence. In Offshore Technology Conference; OnePetro: Richardson, TX, USA, 1990. [Google Scholar]
- Andreas, H.; Abidin, H.Z.; Gumilar, I.; Sarsito, D.A.; Pradipta, D. The Use of GNSS GPS Technology for Offshore Oil and Gas Platform Subsidence Monitoring. In Multi-Purposeful Application of Geospatial Data; IntechOpen: London, UK, 2018. [Google Scholar] [CrossRef]
- Gebre-Egziabher, D.; Gleason, S. GNSS Applications and Methods; Artech House: Norwood, MA, USA, 2009. [Google Scholar]
- Wisniewski, B.; Bruniecki, K.; Moszynski, M. Evaluation of RTKLIB’s Positioning Accuracy Using low-cost GNSS Receiver and ASG-EUPOS. TransNav Int. J. Mar. Navig. Saf. Sea Transp. 2013, 7, 79–85. [Google Scholar] [CrossRef]
- Gandolfi, S.; Macini, P.; Poluzzi, L.; Tavasci, L. GNSS measurements for ground deformations detection around offshore natural gas fields in the Northern Adriatic Region. Proc. IAHS 2020, 382, 89–93. [Google Scholar] [CrossRef]
- Palano, M.; Pezzo, G.; Serpelloni, E.; Devoti, R.; D’Agostino, N.; Gandolfi, S.; Sparacino, F.; Anderlini, L.; Poluzzi, L.; Tavasci, L.; et al. Geopositioning time series from offshore platforms in the Adriatic Sea. Sci. Data 2020, 7, 373. [Google Scholar] [CrossRef]
- Xie, S.; Law, J.; Russell, R.; Dixon, T.H.; Lembke, C.; Malservisi, R.; Rodgers, M.; Iannaccone, G.; Guardato, S.; Naar, D.F.; et al. Seafloor Geodesy in Shallow Water with GPS on an Anchored Spar Buoy. J. Geophys. Res. Solid Earth 2019, 124, 12116–12140. [Google Scholar] [CrossRef]
- Haines, B.J.; Desai, S.D.; Born, G.H. GPS monitoring of vertical seafloor motion at Platform Harvest. Adv. Space Res. 2013, 51, 1369–1382. [Google Scholar] [CrossRef]
- Haines, B.; Desai, S.D.; Kubitschek, D.; Leben, R.R. A brief history of the Harvest experiment: 1989–2019. Adv. Space Res. 2021, 68, 1161–1170. [Google Scholar] [CrossRef]
- Yokota, Y.; Kaneda, M.; Hashimoto, T.; Yamaura, S.; Kouno, K.; Hirakawa, Y. Experimental verification of seafloor crustal deformation observations by UAV-based GNSS-A. Sci. Rep. 2023, 13, 4105. [Google Scholar] [CrossRef]
- Iannaccone, G.; Guardato, S.; Donnarumma, G.P.; De Martino, P.; Dolce, M.; Macedonio, G.; Chierici, F.; Beranzoli, L. Measurement of Seafloor Deformation in the Marine Sector of the Campi Flegrei Caldera (Italy). J. Geophys. Res. Solid Earth 2018, 123, 66–83. [Google Scholar] [CrossRef]
- De Martino, P.; Guardato, S.; Donnarumma, G.P.; Dolce, M.; Trombetti, T.; Chierici, F.; Macedonio, G.; Beranzoli, L.; Iannaccone, G. Four Years of Continuous Seafloor Displacement Measurements in the Campi Flegrei Caldera. Front. Earth Sci. 2020, 8. [Google Scholar] [CrossRef]
- Iannaccone, G.; Guardato, S.; Vassallo, M.; Elia, L.; Beranzoli, L. A New Multidisciplinary Marine Monitoring System for the Surveillance of Volcanic and Seismic Areas. Seismol. Res. Lett. 2009, 80, 203–213. [Google Scholar] [CrossRef]
- Iannaccone, G.; Vassallo, M.; Elia, L.; Guardato, S.; Stabile, T.A.; Satriano, C.; Beranzoli, L. Long-term Seafloor Experiment with the CUMAS Module: Performance, Noise Analysis of Geophysical Signals, and Suggestions about the Design of a Permanent Network. Seismol. Res. Lett. 2010, 81, 916–927. [Google Scholar] [CrossRef]
- Quinn, R.; Boland, D. The role of time-lapse bathymetric surveys in assessing morphological change at shipwreck sites. J. Archaeol. Sci. 2010, 37, 2938–2946. [Google Scholar] [CrossRef]
- Tay, K.-L.; Parrott, R.; Doe, K.; MacDonald, A.; Hung, Y.-T. Environmental monitoring of nearshore dredged material ocean disposal sites. In Handbook of Environment and Waste Management; World Scientific Publishing: Hackensack, NJ, USA, 2013; pp. 887–948. [Google Scholar] [CrossRef]
- Davis, E.; Wright, C.; Demetrius, S.; Choi, J.; Craley, G. Precise Tiltmeter Subsidence Monitoring Enhances Reservoir Management. In Proceedings of the SPE/AAPG Western Regional Meeting, Long Beach, CA, USA, 19–23 June 2000. [Google Scholar] [CrossRef]
- Ukil, A.; Braendle, H.; Krippner, P. Distributed temperature sensing: Review of technology and applications. IEEE Sens. J. 2011, 12, 885–892. [Google Scholar] [CrossRef]
- Cannon, R.; Aminzadeh, F. Distributed acoustic sensing: State of the art. In Proceedings of the SPE Digital Energy Conference and Exhibition, The Woodlands, TX, USA, 5–7 March 2013; p. SPE-163688. [Google Scholar]
- Amer, R.; Xue, Z.; Hashimoto, T.; Nagata, T. Distributed fiber optic strain sensing for geomechanical monitoring: Insights from field measurements of ground surface deformation. Geosciences 2021, 11, 285. [Google Scholar] [CrossRef]
- Wang, Y.; Bi, X.; Feng, S.; Ma, Y.; Yue, Q. Subsidence monitoring of offshore platforms. Procedia Eng. 2011, 15, 1015–1020. [Google Scholar] [CrossRef]
- Bert, M.K. Radar Interferometry: Persistent Scatterers Technique; Springer: Dordrecht, The Netherlands, 2006. [Google Scholar]
- Geodetic Survey Division. GPS Positioning Guide, 1st ed.; Geodetic Survey Division: Washington, DC, USA, 1993. [Google Scholar] [CrossRef]
- Ruddy, I.; Andersen, M.A.; Pattillo, P.D.; Bishlawi, M.; Foged, N. Rock Compressibility, Compaction, and Subsidence in a High-Porosity Chalk Reservoir: A Case Study of Valhall Field. J. Pet. Technol. 1989, 41, 741–746. [Google Scholar] [CrossRef]
Technique | Advantages | Limitation |
---|---|---|
InSAR Accuracy: 1 mm to 10 mm Depth of water column does not affect measurements | Multi-temporal monitoring | Limited vertical accuracy |
All-weather monitoring capability | Not suitable for horizontal wells, as subsidence bowl can be away from the platform | |
Repeatability of measurements | Tropospheric distortion and correction are not fully developed | |
Extensive coverage | Knowledge of compartmentalization can be restricted, as those data are restricted to a few data points to be spatially interpolated | |
Requires line of sight to the target area | ||
GNSS Accuracy: 5 mm to 20 mm Depth of water column does not affect measurements | Precise measurements | Requires clear sky view for optimal performance |
Extensive coverage if installed on multiple platforms | Ionospheric distortions | |
Continuous monitoring | Satellite multipath effects | |
Remote monitoring | Inaccuracies in satellite orbits | |
Non-invasive to other operations | Tropospheric anomalies | |
Long-term data collection | Not suitable for horizontal wells | |
Integration with other data (GNSS + inclinometers; pressure sensors) | Knowledge of compartmentalization can be restricted, as those data are restricted to a few data points to be spatially interpolated | |
Hydrostatic leveling Accuracy: 1 mm to 10 mm Shallow waters | High precision | Limited resolution |
Direct measurement | Limited coverage | |
Stable and robust: hydrostatic leveling is less susceptible to atmospheric conditions | Labor intensive: the setup and operation of hydrostatic leveling systems can be labor intensive, requiring frequent site visits for measurements | |
Continuous monitoring | Prone to long-term drift, requiring periodic recalibration | |
Single-point measurements | ||
Fiber optic cables Accuracy: 1 mm to 5 mm Deep sea depending on cable design | High sensitivity | Installation complexity |
Continuous monitoring | cost | |
Distributed sensing | Limited coverage | |
Non-intrusive | Data transfer and storage challenges due to large volumes of data | |
Multipurpose: can monitor strain, temperature, and other environmental parameters | Calibration and validation: regular calibration and validation of fiber optic sensors are necessary | |
(FBG) strain sensors Accuracy: 1 mm to 5 mm Deep-sea environments depending on cable design | High sensitivity | Initial cost |
Distributed FBG sensors can be positioned along a single optical fiber, enabling distributed sensing over a large area | Limited absolute measurements: the sensors measure strain relative to their initial state, making them more suitable for detecting changes rather than providing absolute subsidence measurements | |
Real-time monitoring | Complexity of interpretation | |
Requires sophisticated data analysis techniques | ||
Tiltmeters Accuracy: 0.01 to 1 arcsecond Deep sea depending on design | High sensitivity | Limited coverage |
Direct measurement | Calibration and adjustment | |
Variety of applications beyond subsidence monitoring, such as structural health monitoring and landslide detection | Limited range | |
Installation complexity | ||
Agisco compensator Accuracy: 10 mm to 100 mm Shallow to moderate depths | High precision | Installation and calibration |
Directly measures subsidence | Limited vertical range | |
Can provide real-time or near-real-time data on subsidence events | Regular maintenance and occasional repairs may be required | |
Long-term monitoring | Limited coverage | |
Can be integrated with other monitoring techniques | Regular maintenance and occasional repairs may be required to ensure the instrument’s accuracy | |
Time-lapse gravimetry and pressure accuracy: 10 mm to 100 mm Deep-sea use depending on equipment design | Direct measurement | Calibration challenges |
Long-range monitoring | Deployment challenges | |
Non-intrusive | Limited accessibility: maintenance and repair | |
Casing collar deformation analysis Accuracy: 1 mm to 10 mm Shallow to moderate depths | Direct measurement | Limited measurement locations |
Cost effective | Restricted vertical range | |
Long-term monitoring | Dependency on casing collars: accurate measurements depend on the integrity and stability of the casing collars; any shifts or movements in the collars can affect data accuracy | |
Lack of continuous data | ||
Requires detailed baseline data for effective comparison | ||
Radioactive marker technique (RMT) Accuracy: 1 mm to 5 mm Shallow to moderate depths | Direct measurement | Radiation hazards |
High precision | Regulatory approval | |
Long-term monitoring | Limited vertical range | |
Continuous monitoring | Data interpretation complexity | |
Comprehensive coverage: RMT markers can be placed at multiple depths | Marker installation requires specialized equipment and procedures | |
Specialized safety protocols required to handle radioactive materials | ||
Expensive | ||
Microelectromechanical systems (MEMSs) Accuracy: 1 mm to 5 mm Deep-sea environments depending on sensor design | High precision | Calibration and stability: requires regular calibration and can be prone to stability issues over time |
Compact size | Limited range | |
Real-time monitoring | Sensor drift | |
Cost effective | Sensor lifetime | |
Ease of installation | Data processing complexity | |
Durability: MEMS sensors are designed to withstand harsh environmental conditions, including exposure to moisture and corrosive elements | Data transmission reliability: wireless communication might be affected by interference, signal attenuation, or communication range limitations | |
Multiparameter monitoring | ||
Wireless communication | ||
Low power consumption | ||
Versatile applications: capable of monitoring a wide range of physical parameters | Calibration and stability: requires regular calibration and can be prone to stability issues over time | |
Bathymetry Accuracy: 1 mm to 1cm Shallow and deep sea | Comprehensive mapping | Limited vertical precision |
Non-intrusive | Interference from structures such as pipelines | |
Large area coverage | Depth limitations | |
High accuracy | Lack of real-time monitoring | |
Air gap measurements Accuracy: 10 mm to 100 mm Unaffected by water column height | Direct vertical measurements | Dependent on tidal variations |
Simple and cost effective | Limited range, especially for larger subsidence events | |
Real-Time Monitoring | Continuous monitoring challenges | |
Early warning indicators of potential subsidence or structural issues | Environmental factors like wind and waves can introduce noise into air gap measurements | |
Can be influenced by sea state and vessel motion | ||
Radar water-level measurements Accuracy: 1 cm to 20 cm Shallow environments | Non-contact measurement physically with the water | Environmental factors like wind and waves can introduce noise into air gap measurements |
Continuous monitoring | Tidal fluctuations can impact water level measurements | |
Remote sensing | Radar signals can be affected by interference from other structures, equipment, or vessels in the vicinity | |
Large coverage area | Cost | |
Electric log data Accuracy: 10 mm to 100 mm Depends on the well | Available historical data | Limited to well locations |
Multi-well monitoring | Costly and time consuming | |
Direct measurement of subsurface changes | Invasive process, as obtaining data requires accessing and instrumenting wells, which might interfere with ongoing operations | |
High vertical resolution | Dependent on well conditions and logging technology | |
Limited temporal resolution | ||
Formation–compaction monitoring tool (FCMT) Accuracy: 1 mm to 10 mm From shallow to relatively deep waters, up to around 3000 m | Direct measurement of compaction | Localized monitoring |
High precision | Installation and data retrieval | |
Long-term monitoring | Dependency on well access | |
Specific to reservoir conditions: FCMT can be customized to suit the specific geological and reservoir conditions | Limited data points | |
Customizable to specific geological settings |
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Thomas, F.; Livio, F.A.; Ferrario, F.; Pizza, M.; Chalaturnyk, R. A Review of Subsidence Monitoring Techniques in Offshore Environments. Sensors 2024, 24, 4164. https://doi.org/10.3390/s24134164
Thomas F, Livio FA, Ferrario F, Pizza M, Chalaturnyk R. A Review of Subsidence Monitoring Techniques in Offshore Environments. Sensors. 2024; 24(13):4164. https://doi.org/10.3390/s24134164
Chicago/Turabian StyleThomas, Frank, Franz A. Livio, Francesca Ferrario, Marco Pizza, and Rick Chalaturnyk. 2024. "A Review of Subsidence Monitoring Techniques in Offshore Environments" Sensors 24, no. 13: 4164. https://doi.org/10.3390/s24134164
APA StyleThomas, F., Livio, F. A., Ferrario, F., Pizza, M., & Chalaturnyk, R. (2024). A Review of Subsidence Monitoring Techniques in Offshore Environments. Sensors, 24(13), 4164. https://doi.org/10.3390/s24134164