Porosity prediction from well logging data via a hybrid MABC-LSSVM model.
Saved in:
| Title: | Porosity prediction from well logging data via a hybrid MABC-LSSVM model. |
|---|---|
| Authors: | Su W; State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, China., Gao J; State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, China., Wu W; State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, China., Zhang H; Frontiers Science Center for Rare Isotopes, Lanzhou University, Lanzhou, Gansu, China.; School of Nuclear Science and Technology, Lanzhou University, Lanzhou, Gansu, China. |
| Source: | PloS one [PLoS One] 2025 Oct 27; Vol. 20 (10), pp. e0335244. Date of Electronic Publication: 2025 Oct 27 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 1932-6203 |
|---|---|
| DOI: | 10.1371/journal.pone.0335244 |
