Probabilistic estimation of well duration has been common practice for more
than a decade; many papers have been written on the subject, and commercial
software is available for the purpose. Is the subject, therefore, mature? The
authors suggest that this is not the case and show that several essential
aspects of both data characterization and probabilistic analysis have been
overlooked in previous contributions.
In 2007, Nexen began a study with the objective of improving our process for
well-time estimation. Its workscope was to
- Assemble a statistically significant historical well database.
- Develop a consistent definition of nonproductive time (NPT) as it relates
to the original approved-for-expenditure (AFE) timings.
- Reanalyze the historical well database for NPT from the original daily
drilling reports (DDRs), on the basis of the definition above.
- Decide how NPT is best characterized (that is, determine the correct choice
of input variables).
- Determine the associated occurrence frequencies and
probability-density-function (PDF) parameters from the historical
- Validate the probabilistic model, by comparison of program predictions
against the historical data set.
- Work with a software provider to implement any necessary changes in a
commercially available product.
A database of 118 central North Sea wells was reanalyzed independently for
NPT from the original DDRs. These considerably underestimated the true NPT, by
19.7% on average. Train wrecks (mechanical NPT events of more than 2.5 days)
were only 4% by number but contributed 50% of NPT by duration. It was found
that "ordinary" mechanical NPT, train wrecks, waiting on weather (WOW) in open
water, and WOW with riser connected are all statistically distinct, with very
different occurrence frequencies and PDFs. Earlier workers did not observe this
distinction or properly validate their models against the well database.
Therefore, it is impossible to obtain historically accurate probabilistic
well-time predictions (i.e., that are consistent with the historical database)
using the previous state of the art. Moreover, such predictions will generally
be underestimates. This paper describes an accurate method that overcomes
previous limitations. While central North Sea data are used, the analysis
techniques are not area specific, and the method may be applied easily to other
areas in the oil field.
© 2010. Society of Petroleum Engineers
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- Original manuscript received:
27 November 2008
- Meeting paper published:
18 March 2009
- Revised manuscript received:
24 August 2009
- Manuscript approved:
25 November 2009
- Published online:
7 May 2010
- Version of record:
16 December 2010