Baker Hughes Rig Counts via ICE Data API

It is the industry's reference read on drilling activity - the weekly tally of active drilling rigs that headlines, earnings calls and central-bank briefings quote when they want to know whether operators are accelerating or retrenching - delivered through Datadory as structured rows instead of a chart screenshot. Intercontinental Exchange distributes the suite commercially and describes it as "a globally recognized indicator of drilling activity and industry trends within the oil and gas sector," published weekly with authoritative counts of active rigs across North America and key international regions.

Two things separate a benchmark from a press release. First, continuity: documented history runs back to 1990, so any single week lands inside a thirty-plus-year arc of booms, busts and recoveries rather than floating free of context. Second, segmentation: the same week resolves by region, by what the rig is chasing (natural gas versus oil), by how it drills (horizontal, vertical or directional), and by where it works (onshore versus offshore). A total tells you that activity moved; the segments tell you why.

Set inside the wider catalog - 1,744 datasets averaging a 7.81 quality score - the Oil & Gas Drilling slice holds 21 datasets averaging 7.86, and this record scores 8/10: carried by verified specifications, global reach and unmatched brand recognition, docked mainly because no public field list exists to verify beyond the documented specification block. Get a sample of this dataset and judge the rows before any commitment.

One count week, resolved four ways. The documented shape:

# one count week, one region, one segment - shape as documented
week_ending_date : <friday of the reported week>
region           : NORTH_AMERICA
well_type        : Oil
rig_count_value  : 542

# same week, same region, drilling for gas instead
well_type        : Gas
rig_count_value  : 128

# same week, vertical rigs only
drilling_method  : Vertical
rig_count_value  : 77

# offshore rows carry their own split
site_type        : Offshore
rig_count_value  : 14

Read the anatomy rather than the values. One row resolves to a single cell of the grid - a week, a region, a target, a method, a setting - and hands over its count. The figures shown illustrate the shape; live values ship with your sample, cut to whichever regions and segments you actually model. That flatness is the appeal: every row is typed identically, so a decade-over-decade comparison is a group-by rather than a parsing project, and the gas-versus-oil crossover - the single most-watched inflection in energy sentiment - falls out of two filtered columns instead of a hand-built reconciliation.

Six fields carry every observation, reconstructed from the catalog's documented specifications: Week Ending Date (the weekly reporting period), Region (North America through key international regions), Well Type (natural gas or oil), Drilling Method (horizontal, vertical or directional), Site Type (onshore or offshore), and Rig Count Value (the active-rig count for that combination). Definitions above are marked inferred rather than verified: ICE publishes the specification block but not a public field list, so the dictionary ships pinned against live records when your sample is cut - and any naming differences get settled there, before anything downstream depends on them.

Three chips summarize the footprint:

• Geography: North America plus key international regions - the documented global footprint, wide enough to compare US shale activity against international drilling in one keyed panel.
• Temporal: weekly observations with documented history since 1990. More than three decades of readings means the current week always has a comparable week thirty years deep, and cycle analysis does not have to splice vendors mid-series.
• Granularity: one count per week per segment - region crossed with well type, drilling method and site type. There is no pre-blended index and no estimation layer; the value is the tally as published, which keeps derived utilization or momentum metrics reproducible.

Set against the catalog's 7.81 average, the record's 8/10 rests on breadth and continuity rather than on published row-level documentation - the trade a commercial distribution deal makes, and one a sample resolves quickly.

API, files, or your warehouse. Daily, weekly, or hourly.

Pick the channel your team already works in and set the cadence to match the decision you are feeding - overnight flat files sized for research benches, a direct pipe into Snowflake, BigQuery or Redshift, or lookup calls for anything interactive.

Every delivery ships the field dictionary above unchanged plus sample rows for validation, flattened to one observation per week per segment so a region-by-method pivot arrives pre-keyed. Name the regions, targets and methods you care about and the sample comes back shaped to them before any commitment.

• Investors and quant researchers read the weekly count as the market's coincident activity pulse: the gas-versus-oil split signals which price deck operators are responding to, and the thirty-year runway supports honest backtests of activity-to-production lags.
• Oilfield-service and equipment teams treat regional and method splits as a demand map - horizontal-directed weeks concentrate in shale plays and pull different pressure-pumping and drilling-tool demand than vertical work.
• E&P strategy and planning groups benchmark their own activity against the global tally, sizing share-of-activity shifts by region without assembling country-level sources by hand.
• Macro and commodity analysts use the count as an input to supply forecasting: rigs today are production in six months, and the offshore/onshore split keeps deepwater lead times from contaminating short-cycle reads.
• Journalists and academics cite the industry-standard number rather than vendor estimates, and the segmentation turns "drilling slowed" into a claim about gas-directed or offshore activity specifically.

For contrast inside the same industry: EIA Crude Oil and Natural Gas Drilling Activity (Rotary Rigs) counts US rotary rigs monthly from 1949 onward, and EIA U.S. Active Well Service Rigs tallies the maintenance fleet keeping existing wells alive. Neither spans the globe weekly; that lane belongs to this series.

Investors and quant researchers get the benchmark activity signal with the longest commercial weekly runway in the industry - the rare series whose name recognition survives a compliance review. Data scientists and ML engineers join a five-dimension typed table to anything keyed on date in one line. Market researchers and consultants anchor drilling-activity chapters on the citation everyone already recognizes. Energy services and equipment teams read demand signals by method and region instead of waiting for order books to confirm. Persona-by-persona detail lives on the industry hub at /industries/oil-gas-drilling.

Three things worth knowing upfront.

First, the field dictionary is documented-inferred, not verified: the catalog publishes a specification block - geography, history since 1990, weekly frequency, the segmentation axes - but no public field list or sample payload, so exact column names and whether particular geographies break out separately get confirmed when your sample is cut. This is normal for commercially distributed benchmarks, not a red flag unique to this record.

Second, granularity stops at the segment level. Rows resolve by week, region, target, method and site type - there is no operator, well or basin identity underneath, so anything needing asset-level detail belongs with a registry product such as the Texas Railroad Commission data sets or BSEE Well API.

Third, cadence is yours to set after validation: the sample proves the schema, then the daily, weekly, or hourly decision follows the workflow you are feeding. None of these caveats blocks a sample; all three get settled before anything depends on the feed.