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

2017/05/15 by Jorge Guevara, Matthias Kormaksson, Guevara, Jorge +15
Computer Science · #FOS: Computer and information sciences #Other Computer Science (cs.OH) #cs.OH

paper · pdf · doi:10.48550/arxiv.1705.06556

Part of DM4OG 2017 proceedings (arXiv:1705.03451)

arxiv created 2017/05/15 · arxiv updated 2017/05/19

Abstract

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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