The oil industry is evolving and inventing new ways to increase production and spending less time screening candidates. We expanded on the previous paper (Abu Bakar et al. 2020) where we described the benefit of combining multiple workflows based on engineering models to be used as validations checks and created a confidence score for the wells to be executed in the field.

The main objective of this paper is to share an alternative solution to enhance or complement the results of each of the workflows by using artificial intelligence/machine learning (AI/ML) to predict well production and/or fill data gaps needed to run the workflows.

The workflows taken into consideration in this paper are gas lift optimization (GLO), gas lift diagnostics (GLD), gas lift surveillance (GLS), sand management monitoring (SMM) workflow, and well test validation (WTV).

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