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
- 10 in the last 30 days
- 284 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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