| dc.contributor.author | Cui, Yuehua | |
| dc.contributor.author | Gao, Jianwen | |
| dc.contributor.author | Song, Shijun | |
| dc.contributor.author | Luo, Wenqin | |
| dc.contributor.author | Chen, Sisi | |
| dc.contributor.author | Wang, Lei | |
| dc.contributor.author | Fu, Kun | |
| dc.contributor.author | Tang, Tianrui | |
| dc.contributor.author | Wang, Jiahao | |
| dc.contributor.author | Yu, Hongyan | |
| dc.date.accessioned | 2026-08-20T11:20:04Z | |
| dc.date.available | 2026-08-20T11:20:04Z | |
| dc.date.copyright | 2026/05/17 | |
| dc.date.issued | 2026 | |
| dc.identifier.other | JLEED9.EYENG-6541.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4312046 | |
| dc.description.abstract | AbstractAccurate fracture characterization is fundamental for optimizing hydrocarbon recovery
in tight sandstone reservoirs, yet traditional methods like borehole image logging
remain cost-prohibitive for field-scale deployment. This study develops a ... | |
| dc.publisher | American Society of Civil Engineers | |
| dc.title | Machine Learning–Driven Fracture Analysis and Prediction in Tight Sandstone Gas Reservoirs Using Geophysical Well Logging | |
| dc.type | Journal Article | |
| dc.journal.volume | 152 | |
| dc.journal.issue | 4 | |
| dc.journal.title | Journal of Energy Engineering | |
| dc.identifier.doi | 10.1061/JLEED9.EYENG-6541 | |
| dc.journal.fristpage | 04026030-1 | |
| dc.journal.lastpage | 04026030-14 | |
| dc.page | 14 | |
| dc.tree | Journal of Energy Engineering:;2026:;Volume ( 152 ):;issue: 004 | |
| dc.contenttype | Fulltext | |
