<jupyter_start><jupyter_text>Accessing Marcellus Shale Energy Laboratory Data Opening MSEEL data is just the same as opening SEG Wiki and GDR OpenEi.Choose one file in the [website](http://www.mseel.org/data/Wells_Datasets/Bogges/) and simply use !wget<jupyter_code>!wget http://www.mseel.org/data/Wells_Datasets/Bogges/Bogges_1/Drilling/1H_Highlands.csv<jupyter_output>--2020-10-17 10:33:51--  http://www.mseel.org/data/Wells_Datasets/Bogges/Bogges_1/Drilling/1H_Highlands.csv
Resolving www.mseel.org (www.mseel.org)... 192.168.127.12
Connecting to www.mseel.org (www.mseel.org)|192.168.127.12|:80... connected.
HTTP request sent, awaiting response... 200 OK
Length: 852422432 (813M) [application/octet-stream]
Saving to: ‘1H_Highlands.csv’

1H_Highlands.csv    100%[===================>] 812.93M  30.1MB/s    in 27s     

2020-10-17 10:34:18 (29.7 MB/s) - ‘1H_Highlands.csv’ saved [852422432/852422432]<jupyter_text>The following will download all the data inside MSEEL. Don't do this if you need just particular part of the folder. It takes ~7-10 minutes to finish downloading all.<jupyter_code>!wget -r -np -nH --cut-dirs=3 -R index.html http://www.mseel.org/data/Wells_Datasets/Bogges/<jupyter_output><empty_output>
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{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '368005', 'license': 'MIT', 'n_tokens_mistral': 551, 'n_tokens_neox': 479, 'n_words': 103, 'path': 'how_to_access_mseel.ipynb', 'repo_name': 'Skipper6931/open-geoscience-repository', 'size': '1218'}