Frac Design Using Machine Learning and Artificial Intelligence (original) (raw)

Day 2 Tue, October 04, 2022

Abstract

One of the biggest challenges in drilling/completion/hydraulic fracturing optimization is determining the optimal parameters in the infinite space of possible solutions. Applying a comprehensive parametric study with various geomechanical properties using both a frac simulator and a reservoir simulator is low efficient. This study proposes a workflow for optimizing unconventional reservoir development using machine learning and artificial intelligence (AI) in conjunction with advanced geomechanical modeling. The workflow consists of four steps: in Step1, appropriate acoustic interpretation models are used for geomechanical and in-situ stress characterization. In Step2, unsupervised machine learning optimizes completion designs based on formation anisotropy and heterogeneity along a well. In step3, a training database is built by generating multiple cases based on various simulations guided by a smart sampling algorithm. Proxy models are trained and validated by feeding the training ...

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