Rock property catalog
One of the first things I do on a new play is to start building a Big Giant Spreadsheet. What goes in the big giant spreadsheet? Everything — XRD results, petrography, geochemistry, curve values, elastic parameters, core photo attributes (e.g. RGB triples), and so on. If you're working in the Athabasca or the Eagle Ford then one thing you have is heaps of wells. So the spreadsheet is Big. And Giant.
But other people's spreadsheets are hard to use. There's no documentation, no references. And how to share them? Email just generates obsolete duplicates and data chaos. And while XLS files are not hard to put on the intranet or Internet, it's hard to do it in a way that doesn't involve asking people to download the entire spreadsheet — duplicates again. So spreadsheets are not the best choice for collaboration or open science. But wikis might be...
The wiki as database
Regular readers will know that I'm a big fan of MediaWiki. One of the most interesting extensions for the software is Semantic MediaWiki (SMW), which essentially turns a wiki into a database — I've written about it before. Of course we can read any wiki page over the web, but you can query an SMW-powered wiki, which means you can, for example, ask for the elastic properties of a rock, such as this Mesaverde sandstone from Thomsen (1986). And the wiki will send you this JSON string:
{u'exists': True,
u'fulltext': u'Mesaverde immature sandstone 3 (Kelly 1983)',
u'fullurl': u'http://subsurfwiki.org/wiki/Mesaverde_immature_sandstone_3_(Kelly_1983)',
u'namespace': 0,
u'printouts': {
u'Lithology': [{u'exists': True,
u'fulltext': u'Sandstone',
u'fullurl': u'http://www.subsurfwiki.org/wiki/Sandstone',
u'namespace': 0}],
u'Delta': [0.148],
u'Epsilon': [0.091],
u'Rho': [{u'unit': u'kg/m\xb3', u'value': 2460}],
u'Vp': [{u'unit': u'm/s', u'value': 4349}],
u'Vs': [{u'unit': u'm/s', u'value': 2571}]
}
}This might look horrendous at first, or even at last, but it's actually perfectly legible to Python. A little bit of data wrangling and we end up with data we can easily plot. It takes no more than a few lines of code to read the wiki's data, and construct this plot of \(V_\text{P}\) vs \(V_\text{S}\) for all the rocks I have so far put in the wiki — grouped by gross lithology:
A page from the Rock Property Catalog in Subsurfwiki.org. Very much an experiment, rocks contain only a few key properties today.
If you're interested in seeing how to make these queries, have a look at this IPython Notebook. It takes you through reading the data from my embryonic catalogue on Subsurfwiki, processing the JSON response from the wiki, and making the plot. Once you see how easy it is, I hope you can imagine a day when people are publishing open data on the web, and sharing tools to query and visualize it.
Imagine it, then figure out how you can help build it!