Geological Literature
Development of a machine learning approach to estimate temperature distribution for evaluating supercritical geothermal resources (B31)(abs.)
ISHITSUKA K., KOBAYASHI Y., MOGI T., UGO T., SUZUKI K., WATANABE N., YAMAYA Y., OKAMOTO K., ASANUMA H., KAJIWARA T., SUGIMOTO T., SAITO R.
| item | description |
|---|---|
| Title | Development of a machine learning approach to estimate temperature distribution for evaluating supercritical geothermal resources (B31)(abs.) |
| Authors | ISHITSUKA K., KOBAYASHI Y., MOGI T., UGO T., SUZUKI K., WATANABE N., YAMAYA Y., OKAMOTO K., ASANUMA H., KAJIWARA T., SUGIMOTO T., SAITO R. |
| Data name | Annual Meeting, Geothermal Research Society of Japan, Abstracts with Programs |
| Volume | 2019 |
| Page | 97-97 |
| Year | 2019 |
| Publisher | Geothermal Research Society of Japan |
| Language | JA |
| GEOLIS URL | https://darc.gsj.jp/archives/detail?cls=geolis&pkey=202070087 |
| @id | https://gbank.gsj.jp/ld/resource/geolis/202070087 |