Machine Learning-Based Completions Sequencing for Well Performance Optimization

arXiv:2402.15608v1 Announce Type: new
Abstract: Establishing accurate field development parameters to optimize long-term oil production takes time and effort due to the complexity of oil well development, and the uncertainty in estimating long-term well production. Traditionally, oil and gas companies use simulation software that are inherently computationally expensive to forecast production. Thus, machine learning approaches are recently utilized in literature as an efficient alternative to optimize well developments by enhancing completion conditions. The primary goal of this project is to …

abstract arxiv companies complexity cs.lg development forecast long-term machine machine learning oil oil and gas companies optimization parameters performance production sequencing simulation software type uncertainty