Estimating Scale Deposition Through Reservoir History Matching in the Janice Field
- Oscar Vazquez (Heriot-Watt University) | Callum Young (Maersk Oil North Sea UK Limited) | Vasily Demyanov (Heriot-Watt University) | Dan Arnold (Heriot-Watt University) | Andrew Fisher (Maersk Oil North Sea Limited) | Alasdair Macmillan (Maersk Oil North Sea UK Limited) | Michael Christie (Heriot-Watt University)
- Document ID
- Society of Petroleum Engineers
- SPE Production & Operations
- Publication Date
- February 2013
- Document Type
- Journal Paper
- 21 - 28
- 2013. Society of Petroleum Engineers
- 5.2 Reservoir Fluid Dynamics, 5.5.8 History Matching, 4.3.4 Scale
- 1 in the last 30 days
- 322 since 2007
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Inorganic-scale precipitation and deposition in production wells can be asignificant impediment to effective reservoir management. In extreme cases,scale can cause the well to be abandoned as a result of reservoir-formationdamage in the near-wellbore region and the narrowing of the production-tubingannulus, thus preventing fluid flow. The prediction of the time and location ofscale formation is therefore essential for scale management. This study isfocused on sulfate scales, which form when sulfate-rich seawater mixes withformation brines that are rich in barium, calcium, and strontium, and which areamong the most difficult types of scale to prevent and remove.
Formation brines in reservoirs with a tendency for sulfate-scale depositioncan have a very different makeup when compared with seawater, which may beinjected for pressure support. Having such different chemistries allowsseawater and formation brine to be tracked. In this study, two different typesof water are considered: formation brine and injected seawater.
The objective of this work is to predict uncertainty in sulfate-scaledeposition from multiple history-matched reservoir models by tracking injectedseawater in the Janice field. There are many examples in the literature inwhich conventional reservoir history matching (namely, gas rate, oil rate, andbottomhole pressure) are used to generate an ensemble of good history-matchedmodels that will estimate uncertainty of a hydrocarbon-reservoir production. Inthis study, the same approach will be adopted, but including produced-waterchemistry--in particular, seawater breakthrough. This approach provides amethodology to predict the uncertainty of the formation-brine/injected-seawatermixing zone within the reservoir formation. The methodology provides a Bayesianconfidence interval (P10/P50/P90) in time and space for the injected seawater,identifying which wells will be at risk on the basis of seawater breakthroughand in which zones of the reservoir mixing is more likely to occur.
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Arnold, D., Vazquez, O., Demyanov, V. et al. 2012. Use of WaterChemistry Data in History Matching of a Reservoir Model. Presented at the SPEEuropec/EAGE Annual Conference, Copenhagen, Denmark, 4-7 June. SPE-154471-MS.http://dx.doi.org/10.2118/154471-MS.
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.
Christie, M., Demyanov, V., and Erbas, D. 2006. Uncertaintyquantification for porous media flows. J. Comput. Phys. 217(1): 143-158. http://dx.doi.org/10.1016/j.jcp.2006.01.026.
Demyanov, V., Subbey, S., and Christie, M. 2004. NeighbourhoodAlgorithm with Geostatistical Simulations for Uncertainty QuantificationReservoir Modeling: PUNQ-S3 Case study. Presented at the 9th EuropeanConference on the Mathematics of Oil Recovery, Cannes, France, 30 August-2September.
Hajizadeh, Y., Christie, M.A., and Demyanov, V. 2010.Comparative Study of Novel Population-Based Optimization Algorithms for HistoryMatching and Uncertainty Quantification: PUNQ-S3 Revisited. Presented at theAbu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, UAE,1-4 November. SPE-136861-MS. http://dx.doi.org/10.2118/136861-MS.
Huseby, O., Chatzichristos, C., Sagen, J. et al. 2005. Use ofnatural geochemical tracers to improve reservoir simulation models. J. Pet.Sci. Eng. 48 (3-4): 241-253. http://dx.doi.org/10.1016/j.petrol.2005.06.002.
Huseby, O.K., Andersen, M., Svorstol, I. et al. 2008. ImprovedUnderstanding of Reservoir Fluid Dynamics in the North Sea Snorre Field byCombining Tracers, 4D Seismic, and Production Data. SPE Res Eval &Eng 11 (4): 768-777. SPE-105288-PA. http://dx.doi.org/10.2118/105288-PA.
Huseby, O., Valestrand, R., Nævdal, G. et al. 2010. Natural andConventional Tracers for Improving Reservoir Models Using the EnKF Approach.SPE J. 15 (4): 1047-1061. SPE-121190-PA. http://dx.doi.org/10.2118/121190-PA.
Ishkov, O., Mackay, E.J., and Sorbie, K.S. 2009. Reacting IonsMethod To Identify Injected Water Fraction in Produced Brine. Presented at theSPE International Symposium on Oilfield Chemistry, The Woodlands. Texas, USA,20-22 April. SPE 121701. http://dx.doi.org/10.2118/121701-MS.
Mackay, E.J., Jordan, M.M., Feasey, N.D. et al. 2005.Integrated Risk Analysis for Scale Management in Deepwater Developments. SPEProd & Oper 20 (2): 138-154. SPE-87459-PA. http://dx.doi.org/10.2118/87459-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.
Østvold, T. 2009. MultiScale 7.1. Haugsund, Norway: ExgroupASA.
Sambridge, M.S. 1999. Geophysical inversion with aneighbourhood algorithm—II. Appraising the ensemble. Geophys. J. Int. 138 (3): 727-746. http://dx.doi.org/10.1046/j.1365-246x.1999.00900.x.
Scheck, M. and Ross, G. 2008. Improvement of Scale ManagementUsing Analytical and Statistical Tools. Presented at the SPE InternationalOilfield Scale Conference, Aberdeen, UK, 28-29 May. SPE-114103-MS. http://dx.doi.org/10.2118/114103-MS.
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.