Produced-Water-Chemistry History Matching Using a 1D Reactive Injector/Producer Reservoir Model
- Oscar Vazquez (Heriot-Watt University) | Ross A. McCartney (Oilfield Water Services Limited) | Eric Mackay (Heriot-Watt University)
- Document ID
- Society of Petroleum Engineers
- SPE Production & Operations
- Publication Date
- September 2013
- Document Type
- Journal Paper
- 369 - 375
- 2013. Society of Petroleum Engineers
- 5.2 Reservoir Fluid Dynamics, 5.6.5 Tracers, 4.3.4 Scale, 5.5.8 History Matching
- 3 in the last 30 days
- 390 since 2007
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Understanding connectivity between injection and production wells isvaluable information for reservoir management. Typically, connectivity might beevaluated by use of downhole-pressure information or by injecting tracers intothe reservoir. A less-established but inexpensive technique is to history matchproduced-water compositions. For example, previous studies with this methodhave identified barriers to flow in reservoirs. Information on connectivity isalso beneficial to scale management, particularly that in which sulfate(SO4) -rich seawater is injected into reservoirs containingformation water rich in divalent cations [i.e., barium (Ba), strontium (Sr),calcium (Ca)], because, in these cases, the sulphate mineral-scaling conditionsin production wells are a function of the physical properties of the flow pathsconnecting the injection and production wells (Wright et al. 2008).
In this study, we have considered this latter relationship from a reverseperspective and explored the potential of history matching produced-watercompositions to understand the physical properties of flow paths connectinginjection and production wells for reservoirs under seawater flood. We haveperformed this history matching with a 1D reactive transport model connectingan injector and a producer through a number of noncommunicating layerscharacterized by permeability, porosity, and height (completion interval)(Vazquez et al. 2009). The model simulates the injection of seawater, themixing of the seawater with reservoir-formation brine, and the subsequentdeposition of sulfate scales (barium and calcium sulphate among others) in thereservoir under equilibrium and kinetic conditions. The results of interest arethe predicted produced-water compositions over time from the model, similar tothe approach presented by McCartney et al. (2012), Tjomsland et al. (2010), andWright et al. (2008).
The model has been used to demonstrate the way in which produced-watercompositions vary as the physical properties of the layers between the wellsare modified, and, particularly, the way in which they vary in the presence ofthief zones. Finally, a stochastic method was applied--in particular aparticle-swarm-optimization (PSO) algorithm--for the automatic history matchingof actual produced-water compositions from individual wells in fields underseawater flooding. The results are promising and show that this technique canprovide valuable information about the nature of interwell connectivity.
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Appelo, C.A.J. 1994. Cation and proton exchange, pH variations,and carbonate reactions in a freshening aquifer. Water Resour. Res. 30 (10): 2793-2805. http://dx.doi.org/10.1029/94wr01048.
Appelo, C.A.J. and Postma, D. 1999. Geochemistry,Groundwater, and Pollution. Rotterdam, The Netherlands: A.A. Balkema.
Arya, A., Hewett, T.A., Larson, R.G. et al. 1988. Dispersionand Reservoir Heterogeneity. SPE Res Eng 3 (1): 139-148.SPE-14364-PA. http://dx.doi.org/10.2118/14364-PA.
Bethke, C.M. 2005. The Geochemist's Workbench Version 6.0 User'sManual. Ubana, Illinois: University of Illinois.
Blount, C.W. and Dickson, F.W. 1973. Gypsum-AnhydriteEquilibria in Systems CaSO4-H2O andCaSO4-NaCl-H2O. Am. Mineral. 58:323-331.
Braden, J.C. and McLelland, W.G. 1993. Produced Water ChemistryPoints to Damage Mechanisms Associated With Seawater Injection. Presented atthe SPE Western Regional Meeting, Anchorage, Alaska, 26-28 May. SPE-26045-MS.http://dx.doi.org/10.2118/26045-MS.
Fan, C., Kan, A., Zhang, P. et al. 2012. Scale Prediction andInhibition for Oil and Gas Production at High Temperature/High Pressure. SPEJ. 17 (2): 379-392. SPE-130690-PA. http://dx.doi.org/10.2118/130690-PA.
Houston, S.J., Yardley, B., Smalley, P.C. et al. 2006.Precipitation and Dissolution of Minerals During Waterflooding of a North SeaOil Field. Presented at the SPE International Oilfield Scale Symposium,Aberdeen, 31 May-1 June. SPE-100603-MS. http://dx.doi.org/10.2118/100603-MS.
Hyeong, K. and Capuano, R.M. 2001. Ca/Mg of brines inMiocene/Oligocene clastic sediments of the Texas Gulf Coast: buffering bycalcite/disordered dolomite equilibria. Geochim. Cosmochim. Acta 65 (18): 3065-3080. http://dx.doi.org/10.1016/S0016-7037(01)00659-7.
Johnson, J.W., Oelkers, E.H., and Helgeson, H.C. 1992.SUPCRT92: A software package for calculating the standard molal thermodynamicproperties of minerals, gases, aqueous species, and reactions from 1 to 5000bar and 0 to 1000°C. Comput. Geosci. 18: 899-947. [yearcorrection]
Kaasa, B. 1998. Prediciton of pH, mineral precipitations andmultiphase equilibria during oil recovery. PhD Thesis No. IUK 103,Department of Materials Science and Engineering, NTNU, Trondheim, Norway.
Kennedy, J. and Eberhart, R. 1995. Particle swarm optimisation.In Proceedings of the IEEE International Conference on Neural Networks,Vol. 4, 1942-1948. Piscataway, New Jersey: IEEE Service Center.
Mackay, E.J. 2003. Modeling In-Situ Scale Deposition: TheImpact of Reservoir and Well Geometries and Kinetic Reaction Rates. SPE Prod& Oper 18 (1): 45-56. SPE-81830-PA. http://dx.doi.org/10.2118/81830-PA.
Mackay, E.J. and Jordan, M.M. 2003. Natural Sulphate Ion Stripping duringSeawater Flooding in Chalk Reservoirs. Presented at the RSC Chemistry in theOil Industry VIII Conference, Manchester, UK, 3-5 November.
Mackay, E.J., Jordan, M.M., and Torabi, F. 2003. PredictingBrine Mixing Deep Within the Reservoir and Its Impact on Scale Control inMarginal and Deepwater Developments. SPE Prod & Oper 18(3): 210-220. SPE-85104-PA. http://dx.doi.org/10.2118/85104-PA.
Mackay, E.J., Sorbie, K.S., Kavle, V.M. et al. 2006. Impact ofIn-Situ Sulfate Stripping on Scale Management in the Gyda Field. Presented atthe SPE International Oilfield Scale Symposium, Aberdeen, UK, 31 May-1 June.SPE-100516-MS. http://dx.doi.org/10.2118/100516-MS.
McCartney, R.A., Williams, J.C., and Coghlan, G.P. 2005.Processes Determining the Composition of Produced Water From Subsea Fields andImplications for Scale Management--Birch Field, UKCS. Presented at the SPEInternational Symposium on Oilfield Scale, Aberdeen, 11-12 May. SPE-94869-MS.http://dx.doi.org/10.2118/94869-MS.
McCartney, R.A., Melvin, K., Wright, R., and Sørhaug, E. 2007. Seawaterinjection into reservoirs with ion exchange properties and high sulphatescaling tendencies: Modelling of reactions and implications for scalemanagement, with specific application to the Gyda Field. Presented at the 18thInternational Oil Field Chemistry Symposium, Geilo, Norway, 25-28 March.
McCartney, R.A., Tjomsland, T., Sandøy, B. et al. 2012.Application of Multirate Tests to Scale Management: Part 1--Interpretation ofProduced-Water Analyses. SPE Prod & Oper 27 (2): 211-222.SPE-131011-PA. http://dx.doi.org/10.2118/131011-PA.
Mahadevan, J., Lake, L.W., and Johns, R.T. 2003. Estimation ofTrue Dispersivity in Field-Scale Permeable Media. SPE J. 8(3): 272-279. SPE-86303-PA. http://dx.doi.org/10.2118/86303-PA.
Mohamed, L., Christie, M., and Demyanov, V. 2010a. Comparisonof Stochastic Sampling Algorithms for Uncertainty Quantification. SPE J. 15 (1): 31-38. SPE-119139-PA. http://dx.doi.org/10.2118/119139-PA.
Mohamed, L., Christie, M.A., and Demyanov, V. 2010b. ReservoirModel History Matching With Particle Swarms: Variants Study. Presented at theSPE Oil and Gas India Conference and Exhibition, Mumbai, India, 20-22 January.SPE-129152-MS. http://dx.doi.org/10.2118/129152-MS.
Onwubolu, G.C. and Babu, B.V. 2004. New OptimizationTechniques in Engineering. Berlin: Studies in Fuzziness and Soft Computing,Springer-Verlag.
Parkhurst, D.L. and Appelo, C.A.J. 1999. User's Guide toPHREEQC (Version 2)--A Computer Program for Speciation, Batch-Reaction,One-Dimensional Transport, and Inverse Geochemical Calculations.Water-Resources Investigations Report 99-4259, US Geological Survey, Denver,Colorado http://wwwbrr.cr.usgs.gov/projects/GWC_coupled/phreeqc/index.html.
Paulo, J., Mackay, E.J., Menzies, N. et al. 2001. Implicationsof Brine Mixing in the Reservoir for Scale Management in the Alba Field.Presented at the International Symposium on Oilfield Scale, Aberdeen, 30-31January. SPE-68310-MS. http://dx.doi.org/10.2118/68310-MS.
Petrotech. 2006. MultiScale Version 7 User Manual. Haugesund,Norway: Petrotech Knowledge AS.
Petrovich, R. and Hamouda, A.A. 1998. Dolomitisation of Ekofiskoilfield reservoir chalk by injected seawater. In Water-Rock Interaction:Proceedings of the 9th International Symposium on Water-RockInteraction--WRI-9, Taupo, New Zealand, 30 March-3 April 1998, ed. G.B.Arehart and J.R. Hulston, 345-348. Rotterdam, The Netherlands: A.A.Balkema.
Rothwell, N.R., Sørensen, A., Peak, J.L. et al. 1993. GYDA:Recovery of Difficult Reserves by Flexible Development and ConventionalReservoir Management. Presented at the Offshore Europe, Aberdeen, 7-10September. SPE-26778-MS. http://dx.doi.org/10.2118/26778-MS.
Sorbie, K.S. and Mackay, E.J. 2000. Mixing of injected, connateand aquifer brines in waterflooding and its relevance to oilfield scaling.J. Pet. Sci. Eng. 27 (1-2): 85-106. http://dx.doi.org/10.1016/S0920-4105(00)00050-4.
Sparks, D.L. 1995. Environmental Soil Chemistry. SanDiego, California: Academic Press/Elsevier Science.
Tavassoli, Z., Carter, J.N., and King, P.R. 2004. Errors inHistory Matching. SPE J. 9 (3): 352-361. SPE-86883-PA. http://dx.doi.org/10.2118/86883-PA.
Tjomsland, T., Sandoey, B., Fadnes, F.H. et al. 2010.Application of Multi-Rate Well Tests to Scale Management. Presented at the SPEInternational Conference on Oilfield Scale, Aberdeen, 26-27 May. SPE-131011-MS.http://dx.doi.org/10.2118/131011-MS.
Vazquez, O., Mackay, E., and Sorbie, K. 2012. A two-phasenear-wellbore simulator to model non-aqueous scale inhibitor squeezetreatments. J. Pet. Sci. Eng. 82-83 (0): 90-99. http://dx.doi.org/10.1016/j.petrol.2011.12.030.
Vazquez, O., Mackay, E.J., and Sorbie, K.S. 2009. Modelling thePlacement of Scale Squeeze Treatments in Heterogeneous Formations withPressurised Layers. Presented at the 8th European Formation Damage Conference,Scheveningen, The Netherlands, 27-29 May. SPE-121856-MS. http://dx.doi.org/10.2118/121856-MS.
Vazquez, O., Fisher, A., Arnold, D. et al. 2013a. EstimatingScale Deposition Through Reservoir History Matching in the Janice Field.Presented at the 2013 SPE International Symposium on Oilfield Chemistry, TheWoodlands, TX, USA, 8-10 April. SPE-164112-MS. http://dx.doi.org/10.2118/164112-MS.
Vazquez, O., Corne, D., Mackay, E. et al. 2013b. AutomaticIsotherm Derivation From Field Data for Oilfield Scale-Inhibitor SqueezeTreatments. SPE J. 18 (3): 563-574. SPE-154954-PA. http://dx.doi.org/10.2118/154954-PA.
Wright, R., McCartney, R.A., and Sørhaug, E. 2008.Understanding Trends in Sulphate Concentrations in Produced Water WithinOilfields Under Seawater Flood and With Calcium-Rich Formation Water. Presentedat the SPE International Oilfield Scale Conference, Aberdeen, 28-29 May.SPE-113974-MS. http://dx.doi.org/10.2118/113974-MS.
Yuan, M.D. and Todd, A.C. 1991. Prediction of Sulfate ScalingTendency in Oilfield Operations. SPE Prod Eng 6 (1): 63-72.SPE-18484-PA. http://dx.doi.org/10.2118/18484-PA.