A data-driven field-scale approach to estimate the permeability of fractured rocks. Issue 10 (26th November 2022)

• Record Type: Journal Article
• Authors: Li, Danqi; Shirani Faradonbeh, Roohollah; Lv, Adelina; Wang, Xiangyu; Roshan, Hamid
• Is Part Of: International journal of mining, reclamation and environment. Volume 36:Issue 10(2022)
• Page Start: 671
• Page End: 687
• Publication Date: 2022-11-26
• Subjects: Fractured rocks -- gene expression programming -- multiple linear regression -- permeability -- response surface methodology; Mining engineering -- Periodicals; Mineral industries -- Environmental aspects -- Periodicals; Abandoned mined lands reclamation -- Periodicals; 622.292
• DOI: 10.1080/17480930.2022.2086769
• Languages: English
• ISSNs: 1748-0930

Abstract

Abstract: In this study, based on compiled numerical-experimental datasets, important variables, including porosity, density, compressional and shear wave velocity, were utilised to develop a novel model for predicting coal permeability with high accuracy. Multiple linear regression, response surface methodology and gene expression programming were employed to develop empirical models based on the foregoing variables. The performance of the developed models was evaluated using statistical indices. The results showed that the GEP-based model has the best prediction performance compared with other techniques. The proposed GEP-based model with its explicit structure can be readily used in practical applications by field engineers.