  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.
