rrc-mapdata-parser 0.1.0

Python module to ingest and process Texas Railroad Commission (RRC) Digital Map Information from .zip archives

RRC Mapdata Parser

A Python module to ingest and process Texas Railroad Commission (RRC) Digital Map Information directly from exported .zip archives.

Overview

This package processes ESRI Shapefile collections from RRC GIS exports. Currently focused on Wells layer with planned expansion to:

Layer	Status	Description
Wells	✅ Implemented	Surface, Bottom, and Arc features
Base	🚧 Planned	Airports, Cities, Roads, etc.
Surveys	🚧 Planned	Lines, Polygons, Bay tracts
Pipelines	🚧 Planned	Abandoned, Liquid, Gas

Installation

pip install rrc-mapdata-parser

For development:

pip install -e ".[dev]"

Usage

Main Parser Class (Recommended)

from rrc_mapdata_parser import RRCMapdataParser

# Create parser instance
parser = RRCMapdataParser(convert_values=True)

# Parse a zip file
result = parser.parse("well329.zip")

# Access wells data
wells = result.wells
print(f"County FIPS: {result.fips}")
print(f"Surface wells: {wells.surface_count}")
print(f"Bottom holes: {wells.bottom_count}")
print(f"Arcs: {wells.arc_count}")

# Iterate over surface wells
for well in wells.surface:
    print(f"API: {well.get('api12')}, Type: {well.get('SYMNUM')}")

# Find a specific well by API
well = wells.get_well_by_api("423290001234")

Processing Multiple Files

parser = RRCMapdataParser()

# Process multiple counties
for result in parser.parse_many(["well329.zip", "well307.zip"]):
    print(f"Processed {result.fips}: {result.wells.surface_count} wells")

Low-Level Functions

from rrc_mapdata_parser import ingest_zip, parse_shapefile

# Direct ingestion
result = ingest_zip("well329.zip", convert_values=True)

# Direct shapefile parsing
records = parse_shapefile("well329s.shp", convert_values=True)

Wells Layer Data

Layer Types

Pattern	Layer Type	Description
well<fips>s.*	Surface	Surface well point locations
well<fips>b.*	Bottom	Bottom hole point locations
well<fips>l.*	Arc	Lines connecting surface to bottom

Primary Keys

• APINUM - 12-digit API number (includes state code 42)
• API10 - 10-digit API number
• API - 8-digit API number

Coordinates

All coordinates maintain double-precision (DOUBLE 18, 8):

• LAT27, LONG27 - NAD27 datum
• LAT83, LONG83 - NAD83 datum

Relational Fields

• SURFACE_ID - Links to surface well points
• BOTTOM_ID - Links to bottom hole points

Code Conversion

With convert_values=True, numeric codes become readable text:

Field	Example Code	Converted Value
SYMNUM	4	"Oil Well"
SYMNUM	5	"Gas Well"
SYMNUM	11	"Injection/Disposal Well"
RELIAB	20	"WELLBORE Distances"
RELIAB	45	"Field Inspection by RRC personnel"

Technical Specifications

Property	Value
Coordinate System	Geographic (Decimal Degrees)
Default Datum	NAD27
Character Encoding	ISO-8859-1
Storage Overhead	1.5x - 2x of compressed size

Testing

# Run tests
pytest tests/ -v

# Run with coverage
pytest tests/ --cov=src/rrc_mapdata_parser

Place sample data at tests/data/well329.zip for integration tests.

License

MIT License