A data-driven workflow for predicting horizontal well production using vertical well logs

نویسندگان

  • Jorge Guevara
  • Matthias Kormaksson
  • Bianca Zadrozny
  • Ligang Lu
  • John Tolle
  • Tyler Croft
  • Mingqi Wu
  • Jan Limbeck
  • Detlef Hohl
چکیده

In recent work, data-driven sweet spotting technique for shale plays previously explored with vertical wells has been proposed. Here, we extend this technique to multiple formations and formalize a general data-driven workflow to facilitate feature extraction from vertical well logs and predictive modeling of horizontal well production. We also develop an experimental framework that facilitates model selection and validation in a realistic drilling scenario. We present some experimental results using this methodology in a field with 90 vertical wells and 98 horizontal wells, showing that it can achieve better results in terms of predictive ability than kriging of known production values.

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عنوان ژورنال:
  • CoRR

دوره abs/1705.06556  شماره 

صفحات  -

تاریخ انتشار 2017