Open Access
Issue
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 75, 2020
Article Number 18
Number of page(s) 25
DOI https://doi.org/10.2516/ogst/2020011
Published online 30 March 2020
  • Adams E.W., Grélaud C., Pal M., Csoma A.E., Al Ja’aidi O.S., Al Hinai R. (2011) Improving reservoir models of Cretaceous carbonates with digital outcrop modelling (Jabal Madmar, Oman): Static modelling and simulating clinoforms, Petrol. Geosci. 17, 3, 309–322. doi: 10.1144/1354-079310-031. [CrossRef] [Google Scholar]
  • Arbués P., Mellere D., Falivene O., Fernández O., Muñoz J.A., Marzo M., De Gibert J.M. (2007) Context and architecture of the Ainsa-1-quarry channel complex, Spain, in: Nielsen T.H., Shew R.D., Steffens G.S., Studlick J.R.J. (eds), Atlas of Deep-Water Outcrops. AAPG Studies in Geology 56, Chapter 147, American Association of Petroleum Geologists, Tulsa, OK. [Google Scholar]
  • Armitage D.A., Stright L. (2010) Modeling and interpreting the seismic-reflection expression of sandstone in an ancient mass-transport deposit dominated deep-water slope environment, Mar. Pet. Geol. 27, 1, 1–12. doi: 10.1016/j.marpetgeo.2009.08.013. [Google Scholar]
  • Bakke K., Kane I.A., Martinsen O.J., Petersen S.A., Johansen T.A., Hustoft S., Jacobsen F.H., Groth A. (2013) Seismic modeling in the analysis of deep-water sandstone termination styles, AAPG Bull. 97, 9, 1395–1419. doi: 10.1306/03041312069. [CrossRef] [Google Scholar]
  • Bartel D.C., Busby M., Nealon J., Zaske J. (2006) Time to depth conversion and uncertainty assessment using average velocity modeling, in: 66th SEG Annual International Meeting, New Orleans, Louisiana, USA, SEG Expanded Abstracts, pp. 2166–2170. doi: 10.1190/1.2369965. [Google Scholar]
  • Batzle M., Wang Z. (1992) Seismic properties of pore fluids, Geophysics 57, 11, 1396–1408. doi: 10.1190/1.1443207. [CrossRef] [Google Scholar]
  • Bear J. (1972) Dynamics of fluids in porous media, Elsevier, New-York. [Google Scholar]
  • Beyer R.T. (1965) Nonlinear acoustics, Phys. Acoust. 2, Part B, 231–264. doi: 10.1016/B978-0-12-395662-0.50014-X. [CrossRef] [Google Scholar]
  • Biot M.A. (1941) General theory of three-dimensional consolidation, J. Appl. Phys. 12, 155–164. doi: 10.1063/1.1712886. [Google Scholar]
  • Borozdina O., Mamaghani M., Barsalou R., Lantoine M., Pain A. (2019) Coreflood Model Optimization Workflow for ASP Pilot Design Risk Analysis, in: SPE Middle East Oil and Gas Show and Conference, 18–21 March, Manama, Bahrain, Society of Petroleum Engineers. doi: 10.2118/194855-MS. [Google Scholar]
  • Bourbiaux B., Fourno A., Nguyen Q.-L., Norrant F., Robin M., Rosenberg E. (2015) Experimental and numerical assessment of chemical enhanced oil recovery in oil-wet naturally fractured reservoirs, SPE J. 21, 3, 706–719. doi: 10.2118/169140-PA. [CrossRef] [Google Scholar]
  • Bourbié T., Coussy O., Zinszner B. (1987) Acoustics of porous media, Editions Technip, Paris. [Google Scholar]
  • Bourgeois A., Joseph P., Lecomte J.-C. (2004) Three-dimensional full wave seismic modelling versus one-dimensional convolution: The seismic appearance of the Grès d’Annot turbidite system, in: Joseph P., Lomas S.A. (eds), Deep-water sedimentation in the Alpine Basin of SE France: New perspectives in the Grès d’Annot and related systems. Special Publications 221, Geological Society, London, UK, pp. 401–417. [Google Scholar]
  • Calvert R. (2005) Insights and methods for 4D reservoir monitoring and characterization. Distinguished Instructor Series n°8, SEG and EAGE, Tulsa, OK/Houten, The Netherlands. doi: 10.1190/1.9781560801696. [CrossRef] [Google Scholar]
  • Cockin A.P., Malcolm L.T., McGuire P.L., Giordano R.M., Sitz C.D. (2000) Analysis of a single-well chemical tracer test to measure the residual oil saturation to a hydrocarbon miscible gas flood at Prudhoe Bay, SPE Res. Evalu. Eng. 3, 6, 544–551. doi: 10.2118/68051-PA. [CrossRef] [Google Scholar]
  • Cossé R. (1993) Basics of reservoir engineering, Éditions Technip, Paris. [Google Scholar]
  • Deans H.A. (1971) Method of determining fluid saturations in reservoirs. US Patent No. 3,623,842. [Google Scholar]
  • Deans H.A., Carlisle C.T. (2007) The single-well chemical tracer test – a method for measuring reservoir fluid saturations in situ, in: Holstein E.D. (ed), SPE Petroleum Engineering Handbook, Reservoir Engineering and Petrophysics, Vol. V, Society of Petroleum Engineers, pp. 615–649. [Google Scholar]
  • Delamaide E., Zaitoun A., Gérard R., Tabary R. (2014) Pelican lake field: First successful application of polymer flooding in a heavy-oil reservoir, SPE Res. Evalu. Eng. 17, 3, 340–354. doi: 10.2118/165234-PA. [CrossRef] [Google Scholar]
  • Delaplace P., Delamaide E., Roggero F., Renard G. (2013) History matching of a successful polymer flood pilot in the Pelican Lake heavy oil field (Canada), in: SPE Annual Technical Conference and Exhibition, 30 September–2 October, New Orleans, LA, USA. doi: 10.2118/166256-MS. [Google Scholar]
  • Delépine N., Labat K., Clochard V., Ricarte P., Le Bras C. (2010) 4D Joint pre-stack seismic stratigraphic inversion of the Sleipner-CO2 case, in: 72nd EAGE Conference and Exhibition Incorporating SPE EUROPEC 2010, Barcelona, Spain, Extended Abstract, K009. doi: 10.3997/2214-4609.201400921. [Google Scholar]
  • Demin W., Zhenhua Z., Jiecheng C., Jingchun Y., Shutang G., Li L. (1997) Pilot test of alkaline surfactant polymer flooding in Daqing oil field, SPE Res. Eng. 12, 4, 229–233. doi: 10.2118/36748-PA. [CrossRef] [Google Scholar]
  • Doherty P.D., Soreghan G.S., Castagna J.P. (2002) Outcrop-based reservoir characterization: A composite phylloid-algal mound, western Orogrande basin (New Mexico), AAPG Bull. 86, 5, 779–795. doi: 10.1306/61EEDB98-173E-11D7-8645000102C1865D. [Google Scholar]
  • Doligez B., Beucher H., Geffroy F., Eschard R. (1999) Integrated reservoir characterization: improvement in heterogeneous stochastic modeling by integration of additional external constraints, in: Schatzinger R., Jordan J. (eds), Reservoir Characterization – Recent Advances, AAPG Memoir, Vol. 71, American Association of Petroleum Geologists, Tulsa, OK, pp. 333–342. [Google Scholar]
  • Douarche F., Da Veiga S., Feraille M., Enchéry G., Touzani S., Barsalou S. (2014) Sensitivity analysis and optimization of surfactant-polymer flooding under uncertainties, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 69, 4, 603–617. doi: 10.2516/ogst/2013166. [CrossRef] [Google Scholar]
  • Douarche F., Rousseau D., Bazin B., Tabary R., Moreau P., Morvan M. (2012) Modeling Chemical EOR Processes: Some illustrations from Lab to Reservoir Scale, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 67, 6, 983–998. doi: 10.2516/ogst/2012059. [CrossRef] [Google Scholar]
  • Dubos-Sallée N., Rasolofosaon P.N.J. (2010) Data-driven quantitative analysis of the CO2 plume extension from 4D seismic monitoring in Sleipner, in: 72nd EAGE Conference and Exhibition incorporating SPE EUROPEC 2010, Barcelona, Spain, Extended Abstract, K010. doi: 10.3997/2214-4609.201400922. [Google Scholar]
  • Falivene O., Arbués P., Gardiner A., Pickup G., Muñoz J.A., Caberra L. (2006a) Best practice stochastic facies modeling from a channel-fill turbidite sandstone analog (the Quarry outcrop, Eocene Ainsa Basin, northeast Spain), AAPG Bull. 90, 7, 1003–1029. doi: 10.1306/02070605112. [CrossRef] [Google Scholar]
  • Falivene O., Arbués P., Howell J., Muñoz J.A., Fernández O., Marzo M. (2006b) Hierarchical geocellular facies modelling of a turbidite reservoir analogue from the Eocene of the Ainsa Basin, NE Spain, Mar. Pet. Geol. 23, 6, 679–701. doi: 10.1016/j.marpetgeo.2006.05.004. [Google Scholar]
  • Falivene O., Arbués P., Ledo J., Benjumea B., Muñoz J.A., Fernández O., Martínez S. (2010) Synthetic seismic models from outcrop-derived reservoir-scale three-dimensional facies models: The Eocene Ainsa turbidite system (southern Pyrenees), AAPG Bull. 94, 3, 317–343. doi: 10.1306/08030908157. [CrossRef] [Google Scholar]
  • Galli A., Beucher H., Le Loc’h G., Doligez B., Heresim Group. (1994) The Pros and Cons of the truncated Gaussian method, in: Armstrong M., Dowd P.A. (eds), Geostatistical Simulations, Quantitative Geology and Geostatistics, Vol. 7, Springer, Dordrecht, pp. 217–233. doi: 10.1007/978-94-015-8267-4_18. [CrossRef] [Google Scholar]
  • Gasparrini M., Lopez-Cilla I., Blazquez-Fernandez S., Rosales I., Lerat O., Martin-Chivilet J., Doligez B. (2016) A multidisciplinary modeling approach to assess facies-dolomitization-porosity interdependence in a lower cretaceous platform (Northern Spain), in: Advances in Characterization and Modeling of Complex Carbonate Reservoirs – In Memory of Eric Mountjoy, SEPM (Society for Sedimentary Geology), Broken Arrow, OK. doi: 10.2110/sepmsp.109.07. [Google Scholar]
  • Gassmann F. (1951) Über die elastizität poröser medien, Vierteljahrsschrift der Naturforschenden Geselschaft in Zürich 96, 1–23. English translation available from: http://sepwww.stanford.edu/sep/berryman/PS/gassmann.pdf. [Google Scholar]
  • Green D.W., Willhite G.P. (1998) Enhanced oil recovery. SPE Textbook Series Vol. 6, SPE, TX, USA. [Google Scholar]
  • Hatchell P. (2015) Experience with time-lapse monitoring using ocean bottom nodes in deepwater fields. EAGE E-lecture Series, https://www.youtube.com/watch?v=1jm70tZ8liE. [Google Scholar]
  • Helgerud M.B., Miller A.C., Johnston D.H., Udoh M.S., Jardine B.G., Harris C., Aubuchon N. (2011) 4D in the deepwater Gulf of Mexico: Hoover, Madison, and Marshall fields, Lead. Edge 30, 9, 1008–1018. [Google Scholar]
  • Holgate N.E., Hampson G.J., Jackson C.A.-L., Petersen S.A. (2014) Constraining uncertainty in interpretation of seismically imaged clinoforms in deltaic reservoir, Troll field, Norwegian North Sea: Insights from forward seismic models of outcrop analogs, AAPG Bull. 98, 12, 2629–2663. doi: 10.1306/05281413152. [CrossRef] [Google Scholar]
  • Hou J., Liu Z., Zhang S., Yue X., Yang J. (2005) The role of viscoelasticity of alkali/surfactant/polymer solutions in enhanced oil recovery, J. Pet. Sci. Eng. 47, 3–4, 219–235. doi: 10.1016/j.petrol.2005.04.001. [Google Scholar]
  • Houck R.T. (2010) Value of geophysical information for reservoir management, Meth. Appl. Res. Geophys. 15, 29. [Google Scholar]
  • Houpeurt A. (1975) Éléments de mécanique des fluides dans les milieux poreux, Editions Technip, Paris. [Google Scholar]
  • Iske A., Randen T. (2006) Mathematical methods and modelling in hydrocarbon exploration and production, Springer Science & Business Media, Berlin, Germany. [Google Scholar]
  • Iversen E., Tygel M. (2008) Image-ray tracing for joint 3D seismic velocity estimation and time-to-depth conversion, Geophysics 73, 3, S99–S114. doi: 10.1190/1.2907736. [CrossRef] [Google Scholar]
  • Janson X., Fomel S. (2011) 3-D forward model of an outcrop-based geocellular model, in: Martinsen O.J., Pulham A.J., Haughton P.D.W., Sullivan M.D. (eds), Outcrops Revitalized, Society for Sedimentary Geology, pp. 87–106. doi: 10.2110/sepmcsp.10.087. [CrossRef] [Google Scholar]
  • Jardin A., Joseph P., Koochak Zadeh M., Lerat O. (2010) Quantitative interpretation of multi-dimensional seismic models of turbidite channels from the Ainsa-1 quarry, Spain, 72nd EAGE Conference & Exhibition, Barcelona, Spain. Expanded Abstract, P065. doi: 10.3997/2214-4609.201401078. [Google Scholar]
  • Johnston D.H. (2013) Practical applications of time-lapse seismic data. Distinguished Instructor Series n°16, SEG, Tulsa, OK. doi: 10.1190/1.9781560803126. [CrossRef] [Google Scholar]
  • Joseph P. (2017) Use of virtual outcrops for mobile learning during field trips and practical case studies in geosciences, in: Presented at the Workshop WS17 “Value of Virtual outcrops in Geosciences”, 79th EAGE Conference and Exhibition, 16 June, Paris, France. [Google Scholar]
  • Koster K., Gabriels P., Hartung M., Verbeek J., Deinum G., Staples R. (2000) Time-lapse seismic surveys in the North Sea and their business impact, Lead. Edge 19, 3, 286–293. [Google Scholar]
  • Kragh E.D., Christie P. (2002) Seismic repeatability, normalized rms, and predictability, Lead. Edge 21, 7, 640–647. [Google Scholar]
  • Labat K., Delépine N., Clochard V., Ricarte P. (2012) 4D joint stratigraphic inversion of prestack seismic data: Application to the CO2 storage reservoir (Utsira sand formation) at Sleipner site, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 67, 2, 329–340. doi: 10.2516/ogst/2012006. [CrossRef] [Google Scholar]
  • Lake L.W., Johns R.T., Rossen W.R., Pope G.A. (2014) Fundamentals of enhanced oil recovery, Society of Petroleum Engineers. [Google Scholar]
  • Landrø M. (2001) Discrimination between pressure and fluid saturation changes from time-lapse seismic data, Geophysics 66, 3, 836–844. doi: 10.1190/1.1444973. [CrossRef] [Google Scholar]
  • Landro M., Solheim O.A., Hilde E., Ekren B.O., Stronen L.K. (1999) The Gullfaks 4D seismic study, Petrol. Geosci. 5, 3, 213–226. [CrossRef] [Google Scholar]
  • Le Ravalec M., Tillier E., Da Veiga S., Enchéry G., Gervais V. (2012) Advanced integrated workflows for incorporating both production and 4D seismic-related data into reservoir models, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 67, 2, 207–220. doi: 10.2516/ogst/2011159. [CrossRef] [Google Scholar]
  • Lerat O., Nivlet P., Doligez B., Lucet N., Roggero F., Berthet P., Lefeuvre F., Vittori J. (2007) Construction of a stochastic geological model constrained by high resolution 3D seismic data – application to the Girassol field, offshore Angola, in: Presented at the SPE Annual Technical Conference and Exhibition, 11–14 November, Anaheim, CA, USA, pp. 11–14. doi: 10.2118/110422-MS. [Google Scholar]
  • Leray S., Douarche F., Tabary R., Peysson Y., Moreau P., Preux C. (2016) Multi-objective assisted inversion of chemical EOR corefloods for improving the predictive capacity of numerical models, J. Pet. Sci. Eng. 146, 1101–1115. doi: 10.1016/j.petrol.2016.08.015. [Google Scholar]
  • Lumley D.E., Behrens R.A., Wang Z. (1997) Assessing the technical risk of a 4-D seismic project, Lead. Edge 16, 9, 1287–1292. [Google Scholar]
  • Lumley D.E., Nunns A.G., Delorme G., Adeogba A.A., Bee M.F. (1999) Meren Field, Nigeria: A 4D seismic case study, in: SEG Technical Program Expanded Abstracts 1999, Society of Exploration Geophysicists, Tulsa, OK, pp. 1628–1631. [CrossRef] [Google Scholar]
  • Lyons W.C., Plisga G.J. (2011) Standard handbook of petroleum and natural gas engineering, 3rd edn., Gulf Professional Publishing, Burlington, MA. [Google Scholar]
  • Manrique E.J., Thomas C.P., Ravikiran R., Izadi Kamouei M., Lantz M., Romero J.L., Alvarado V. (2010) EOR: current status and opportunities, in: Presented at the SPE Improved Oil Recovery Symposium, 24–28 April, Tulsa, OK, USA. doi: 10.2118/130113-MS. [Google Scholar]
  • Marçal E., de Castro Andrade R.M., Viana W. (2017) Mobile Learning em aulas de campo: um estudo de caso em Geologia (Mobile Learning in field trips: a case study in Geology), RIED: Rev. Iberoam. Educ. Distancia 20, 2, 315–336. In Portugese. [Google Scholar]
  • Massonnat G.J., Rolando J.-P., Danquigny C. (2017) The ALBION project: An observatory in the heart of a carbonate reservoir, Abu Dhabi International Petroleum Exhibition & Conference, 13–16 November, Abu Dhabi, UAE. Society of Petroleum Engineers. doi: 10.2118/188539-MS. [Google Scholar]
  • Mavko G., Mukerji T., Dvorkin J. (1998) The rock physics handbook, Cambridge Univ. Press, Cambridge, UK. [Google Scholar]
  • Muskat M., Wyckoff R.D. (1937) Flow of homogeneous fluids through porous media, J.W. Edwards, Ann Arbor, MI. [Google Scholar]
  • Onuwaje A., Adejonwo A., Al-Mandhary I., Detomo R. Jr, Effiom O., Gouveia W., Kremers N., Legius E., MacLellan A., Mcclenaghan R., Quadt E. (2009) The Bonga 4D – Shell Nigeria’s first deepwater time lapse monitor, in: 71st EAGE Conference and Exhibition incorporating SPE EUROPEC 2009. [Google Scholar]
  • OpenFlow Softwares (2015/2016) Version 2015/2016, IFPEN/Beicip-Franlab, Rueil-Malmaison, France. http://www.beicip.com/openflow-suite. [Google Scholar]
  • Peaceman D.W. (1983) Interpretation of well-block pressures in numerical reservoir simulation with nonsquare grid blocks and anisotropic permeability, SPE J. 23, 3, 531–543. doi: 10.2118/10528-PA. [Google Scholar]
  • Pickering K.T., Corregidor J., Clark J.D. (2015) Architecture and stacking patterns of lower-slope and proximal basin-floor channelised submarine fans, Middle Eocene Ainsa, Earth Sci. Rev. 144, 47–81. doi: 10.1016/j.earscirev.2014.11.017. [Google Scholar]
  • Pringle J.K., Howell J.A., Hodgetts D., Westerman A.R., Hodgson D.M. (2006) Virtual outcrop models of petroleum reservoir analogues: A review of the current state-of-the-art, First Break 24, 3, 33–42. doi: 10.3997/1365-2397.2006005. [CrossRef] [Google Scholar]
  • Rasolofosaon P.N.J., Zinszner B. (2009) Poroelastic equations closely examined by ultrasonic experiments in rocks, in Ling H.I., Smyth A., Betti R. (eds), Poromechanics IV, Proceedings of the Fourth Biot Conference on Poromechanics, DEStech Publications Inc., Lancaster, pp. 661–666. [Google Scholar]
  • Rasolofosaon P.N.J., Zinszner B. (2012) Experimental verification of the petroelastic model in the laboratory – Fluid substitution and pressure effects, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 67, 2, 303–318. doi: 10.2516/ogst/2011167. [CrossRef] [Google Scholar]
  • Rasolofosaon P.N.J., Zinszner B. (2014) Petroacoustics – a tool for applied seismics, EDP Sciences, Les Ulis, France. http://books.ifpenergiesnouvelles.fr/ebooks/petroacoustics/index.htm. [Google Scholar]
  • Roggero F., Lerat O., Ding D.Y., Berthet P., Bordenave C., Lefeuvre F., Perfetti P. (2012) History matching of production and 4D seismic data: Application to the Girassol field, offshore Angola, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 67, 2, 237–262. doi: 10.2516/ogst/2011148. [CrossRef] [Google Scholar]
  • Schmitz J., Deschamps R., Joseph P., Lerat O., Doligez B., Jardin A. (2014) From 3D photogrammetric outcrop models to reservoir models: An integrated modelling workflow, in: Presented at the Vertical Geology Conference, 5–7 February, Lausanne, Switzerland. [Google Scholar]
  • Schwab A.M., Cronin B.T., Ferreira H. (2007) Seismic expression of channel outcrops: Offset stacked versus amalgamated channel systems, Mar. Pet. Geol. 24, 6–9, 504–514. doi: 10.1016/j.marpetgeo.2006.10.009. [Google Scholar]
  • Sheriff R.E. (2002) Encyclopedic dictionary of applied geophysics, SEG, Tulsa, OK. doi: 10.1190/1.9781560802969. [CrossRef] [Google Scholar]
  • Stright L., Stewart J., Campion K., Graham S. (2014) Geologic and seismic modeling of a coarse-grained deep-water channel reservoir analog (Black’s Beach, La Jolla, California), AAPG Bull. 98, 4, 695–728. doi: 10.1306/09121312211. [CrossRef] [Google Scholar]
  • Tillier E., Le Ravalec M., Da Veiga S. (2012) Simultaneous inversion of production data and seismic attributes: Application to a synthetic SAGD produced field case, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 67, 2, 289–301. doi: 10.2516/ogst/2012004. [CrossRef] [Google Scholar]
  • Vargo J., Turner J., Bob V., Pitts M.J., Wyatt K., Surkalo H., Patterson D. (2000) Alkaline-surfactant-polymer flooding of the Cambridge Minnelusa Field, SPE Res. Evalu. Eng. 3, 6, 552–558. doi: 10.2118/68285-PA. [CrossRef] [Google Scholar]
  • Yilmaz Ö. (2001) Seismic data analysis: Processing, inversion, and interpretation of seismic data, SEG, Tulsa, OK. doi: 10.1190/1.9781560801580. [CrossRef] [Google Scholar]
  • Zarate-Rada J. (2016) Chemical enhanced oil recovery modelling, MS Memoir in Développement et Exploitation des Gisements, IFP School, Rueil-Malmaison, France. Available from: https://hal-ifp.archives-ouvertes.fr/hal-01779611/document. [Google Scholar]
  • Zerpa L.E., Queipo N.V., Pintos S., Salager J.L. (2005) An optimization methodology of alkaline–surfactant–polymer flooding processes using field scale numerical simulation and multiple surrogates, J. Pet. Sci. Eng. 47, 3–4, 197–208. doi: 10.1016/j.petrol.2005.03.002. [Google Scholar]
  • Zinszner B., Pellerin F.M. (2007) A geoscientist’s guide to petrophysics, Editions Technip, Paris. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.