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Statewide API Data (dBase)

The API-to-lease map: every mapped Texas well bore, its lease, its quad and its plug date.

What this is:

MAF016, RRC's Mapping Well Data Download, decoded from the 254 per-county dBase files into one table of 1,556,119 entries covering 1,198,492 distinct API numbers.

How it is laid out:

The Railroad Commission publishes this as dBase (DBF). DBF tables from the 1980s. Readable by GIS software, not by a spreadsheet. We decode it into a table you can open anywhere. It has 26 columns and about 1.6M rows.

The columns you will most likely want:

  • county_code The county whose dBase file this row came from, taken from the file name: api003.dbf gives '003'.
  • api_no The eight-digit API number as the file publishes it: three digits of county then five of unique well.
  • seq The entry's ordinal among the rows sharing its API number, in file order.
  • api_county The county component of the API number, split out so it joins to texas.wellbore's api_county without string surgery.
  • api_unique The five-digit well component of the API number, split out to match texas.wellbore's api_unique.
  • api_number The same API written 42-CCC-UUUUU, which is the form texas.permits and texas.wellbore use.

…and 20 more, all documented on the full page.

What we add:

Turn an API number into a lease: 812,660 entries name an oil lease number and 306,668 a gas well ID, which is the handle PDQ production and the proration schedules are keyed on.

There is more on the full page, including what this joins to.

  • Decoded out of the Commission's original format into something Excel opens.
  • Filterable before you download, so you can take one county instead of the whole state.
  • The Commission's single-letter codes translated into words.

Worth knowing before use:

One row per API is wrong here. The mapping extract carries a bore once for each lease or schedule entry it has been under, so the 1,556,119 rows cover 1,198,492 API numbers. `seq` numbers the entries within an API, and 215,300 bores have a second one.

The full page lists every trap in this dataset.

Get it:

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