A variety of supervised learning models are used for perceptual identification and parameter analysis of drilling formations.
The data fields are schematized as follows:
ILD:Induction Logging Device;
SP:Spontaneous Potentialv
CN:Neutron Logging;
ILM:Intermediate Logging Device;
GR:Gamma Ray Logging;
CAL:Caliper;
AC:Acoustic Logging;
DEN:Density Logging.
| collect time | 2009/01/01 - 2013/12/31 |
|---|---|
| collect place | Tarim Basin |
| data size | 122.9 MiB |
| data format | csv,txt |
| Coordinate system |
The raw data are logged from the Devonian Donghetang Formation in the Tarim Basin.
Perceptual identification and parameter analysis of drilling formations using multiple supervised learning models.
Data quality is good.
| # | number | name | type |
| 1 | XDA14000000 | Strategy Priority Research Program (Category A) of Chinese Academy of Sciences | |
| 2 | XDA14040000 | Key technologies for ultra-deep guided drilling | Strategy Priority Research Program (Category A) of Chinese Academy of Sciences |
This work is licensed under a
Creative
Commons Attribution 4.0 International License.
| # | title | file size |
|---|---|---|
| 1 | _ncdc_meta_.json | 4.0 KiB |
| 2 | 监督学习的钻井地层感知:模型评估和参数分析数据集.zip | 122.9 MiB |
Tarim Basin Devonian Donghetang Formation logging curve oil and gas logging lithology identification
©Copyright 2005-. Northwest Institute of Eco-Environment and Resources, CAS.
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