PDQ County Lease Production by Cycle
Lease production split by county, for leases that cross a county line.
What this is
One of the sixteen delimited tables inside the monthly Production Data Query dump. RRC publishes the dump as a single archive; EZRRC publishes each table inside it separately so you can take the one you need instead of a 3.6 GB zip.
64 million rows. The same lease-month production as the lease cycle table, but allocated to counties — because a Texas lease can straddle a county boundary and the …
How it is laid out
The Railroad Commission publishes this as CSV. Comma-separated text. We decode it into a table you can open anywhere. It has 34 columns and about 53.5M rows.
The columns you will most likely want:
-
oil_gas_codeWhether the lease is carried on the oil schedule or the gas schedule. -
district_noRRC's INTERNAL district number, 01 to 14 plus 20 for statewide. This is not the district name the … -
lease_noRRC lease number. Unique only within a district and a schedule, so a lease key is district + … -
cycle_yearProduction cycle year, four digits. -
cycle_monthProduction cycle month, two digits. -
county_noCounty FIPS code within Texas, zero-padded to three digits.
…and 28 more, all documented on the full page.
What we add
Produce county-level production totals that are actually correct for multi-county leases, which a naive lease-to-county join gets wrong.
Compare county production over time without double counting.
- 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 you use it
Summing this table by lease double counts a multi-county lease. Use the lease cycle table for lease totals and this one for county totals.
A lease number is only unique with the oil/gas code and the district in it. Oil lease 027587 in District 08 and gas lease 027587 in District 08 are different leases; …
The full page lists every trap in this dataset.