A Comprehensive review of data-driven approaches for forecasting production from unconventional reservoirs: best practices and future directions.

ABSTRACT: Prediction of well production from unconventional reservoirs is a complex problem given an incomplete understanding of physics despite large amounts of data. Recently, Data Analytics Techniques (DAT) have emerged as an effective approach for production forecasting for unconventional reservoirs. In some of these approaches, DAT are combined with physics-based models to capture the essential physical mechanisms of fluid flow in porous media, while leveraging the power of data-driven methods to account for uncertainties and heterogeneities. Here, we provide an overview of the applications and performance of DAT for production forecasting of unconventional reservoirs examining and comparing predictive models using different algorithms, validation benchmarks, input data, number of wells, and fo

SUBMITTER: Rahmanifard H 

PROVIDER: S-EPMC11263255 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature