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Abstract

Summary

Making hardware decisions against the backdrop of low oil prices, ageing fields and the need to maximize production rates requires high quality, reliable, and accurate well production data. For example, how much water and sand is being produced from wells and what impact will it have on processing facilities and hardware choices? Are processing facilities sufficient to cope with estimated production forecasts?

In this paper, we introduce a new methodology that looks at the different impacts of uncertainty rates on well production forecasts and how this information can provide input to hardware decisions. Such an approach is applicable not only at the early stages of the field development process but also at later stages where hardware is not being prioritized, as it should.

The method uses the reservoir simulation model as a basis for testing production hypotheses and enables operators to take advantage of geologic data in deciding which measurements contribute most to production forecasts and where they need the most robust measurement systems.

The paper will ask the question ‘What is the value of reducing uncertainty in well production rates via improved hardware?’ with the answer likely to have a major impact on future field development decisions.

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/content/papers/10.3997/2214-4609.201413036
2015-06-01
2024-03-28
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References

  1. Leahy, G. and Skorstad, A.
    [2013]. Uncertainty in Subsurface Interpretation. First Break, 31, 87–93.
    [Google Scholar]
  2. Webb, S. Dunlop, N. Revus, D. Myhre, A. Goodwin, N. and Heritage, J.
    [2008]. Rapid Model Updating with Right-Time Data. SPE Paper11246.
    [Google Scholar]
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