Planning and implementing the redevelopment of volve field, Norwegian north sea using knowledge discovery in databases data mining and numerical simulation techniques

Alexander McAllister* (Corresponding Author), Lateef Akanji

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, a brownfield development plan was investigated by mining the data
pack from Equinor Volve field repository, modelling and simulating to establish
the quantity of hydrocarbon that is still recoverable therefrom. This is aimed at
identifying the most appropriate technique for recovering additional oil from the
brown field. Firstly, a data-mining algorithm that is based on knowledge
discovery in databases (KDD) was developed, the reservoir model was built and
utilised in history matching and selection of enhanced oil recovery option. The
preceding development achieved 46% recovery thus a window of 8-12%
additional recovery was set as a goal. The field development plan has two
options; the best technical option which had a double peripheral layout spot
pattern with 7 injectors (2 water 5 WAG) and 10 producers (3 of which were
horizontal and 7 vertical). The incremental increase goal was hit, with recovery
increasing by 10% by year 3 and 12% by year 4. However, it was felt the impact
on the environment of such a project was simply too significant thus the
recommended case took the form of 6 producers and 1 water injector. This was
the improved reactivated well trajectory case.
Original languageEnglish
Pages (from-to)2567 – 2593
Number of pages27
JournalJournal of Engineering Science and Technology
Volume17
Issue number4
Early online date1 Aug 2022
Publication statusPublished - 1 Aug 2022

Keywords

  • Data mining (DM)
  • Enhanced oil recovery (EOR)
  • Field development plan (FDP)
  • Knowledge discovery in databases (KDD)
  • Water alternating gas (WAG)

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