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.
Cite
@article{arxiv.1705.06556,
title = {A data-driven workflow for predicting horizontal well production using vertical well logs},
author = {Jorge Guevara and Matthias Kormaksson and Bianca Zadrozny and Ligang Lu and John Tolle and Tyler Croft and Mingqi Wu and Jan Limbeck and Detlef Hohl},
journal= {arXiv preprint arXiv:1705.06556},
year = {2017}
}