Estimating scale deposition through reservoir history matching in the Janice field

Oscar Vazquez, Callum Young, Vasily Demyanov, Daniel Arnold, Andrew Fisher, Alasdair Macmillan, Michael Andrew Christie

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Inorganic-scale precipitation and deposition in production wells can be significant impediment to effective reservoir management. In extreme cases, scale can cause the well to be abandoned as a result of reservoir-formation damage in the near-wellbore region and the narrowing of the production-tubing annulus, thus preventing fluid flow. The prediction of the time and location of scale formation is therefore essential for scale management. This study is focused on sulfate scales, which form when sulfate-rich seawater mixes with formation brines that are rich in barium, calcium, and strontium, and which are among the most difficult types of scale to prevent and remove.

Formation brines in reservoirs with a tendency for sulfate-scale deposition can have a very different makeup when compared with seawater, which may be injected for pressure support. Having such different chemistries allows seawater 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-scale deposition from multiple history-matched reservoir models by tracking injected seawater in the Janice field. There are many examples in the literature in which conventional reservoir history matching (namely, gas rate, oil rate, and bottomhole pressure) are used to generate an ensemble of good history-matched models that will estimate uncertainty of a hydrocarbon-reservoir production. In this study, the same approach will be adopted, but including produced-water chemistry--in particular, seawater breakthrough. This approach provides a methodology to predict the uncertainty of the formation-brine/injected-seawater mixing zone within the reservoir formation. The methodology provides a Bayesian confidence interval (P10/P50/P90) in time and space for the injected seawater, identifying which wells will be at risk on the basis of seawater breakthrough and in which zones of the reservoir mixing is more likely to occur.
Original languageEnglish
Pages (from-to)21-28
Number of pages8
JournalSPE Production and Operations
Issue number1
Publication statusPublished - Feb 2014


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