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Supervised learning for drilling formation sensing: model evaluation and parameter analysis dataset (2009-2013)
  • 2024/03/28 17:27
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English name
Supervised learning for drilling formation sensing: model evaluation and parameter analysis dataset (2009-2013)
CSTR
CSTR:11738.11.NCDC.XDA14.DB6398.2024
DOI
10.12072/ncdc.xda14.db6398.2024
Share type
Online
Category
Others
source site
contributors
CHEN Dong
Datasets description

  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.

Base information
collect time 2009/01/01  -  2013/12/31
collect place Tarim Basin
data size 122.9 MiB
data format csv,txt
Coordinate system
Data thumbnail
Data source description

  The raw data are logged from the Devonian Donghetang Formation in the Tarim Basin.

Data processing method

  Perceptual identification and parameter analysis of drilling formations using multiple supervised learning models.

Data quality description

  Data quality is good.

Project information
# 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
Citations and annotations
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For the achievements published in English, please refer to the following specifications： The dataset is provided by National Cryosphere Desert Data Center. (http://www.ncdc.ac.cn).

Data reference
  1. CHEN Dong. Supervised learning for drilling formation sensing: model evaluation and parameter analysis dataset (2009-2013). National Cryosphere Desert Data Center(http://www.ncdc.ac.cn), 2024. https://cstr.cn/CSTR:11738.11.NCDC.XDA14.DB6398.2024.
  2. CHEN Dong. Supervised learning for drilling formation sensing: model evaluation and parameter analysis dataset (2009-2013). National Cryosphere Desert Data Center(http://www.ncdc.ac.cn), 2024. https://www.doi.org/10.12072/ncdc.xda14.db6398.2024.
license agreement
Creative Commons License   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
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How to get the data 
east  90.00
west  75.00
south  37.00
north  42.00
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Service information
contacts:
Min Yufang
phone:
09314967596
mailbox:
ncdc@lzb.ac.cn
Contact information
contributors:
CHEN Dong
author:
CHEN Dong
manager:
CHEN Dong

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