| name | neqsim-norwegian-continental-shelf-data |
| calculation_basis | screening |
| version | 0.4.0 |
| description | Public Norwegian Continental Shelf (NCS) reference-facts database, carbon-cost basis, decline-curve forecasting, and screening analysis. USE WHEN: a task needs offline, source-attributed NCS production, resource, field, carbon-cost/emission-abatement, or Arps decline-forecast facts (from norskpetroleum.no / Norwegian Offshore Directorate FactPages) to orient a production, resource-accounting, field-inventory, emission-reduction, or production-forecast screening before a validated NeqSim reservoir/process study. |
| last_verified | 2026-07-13 |
| requires | {"python_packages":[],"java_packages":[],"env":[],"network":[]} |
Norwegian Continental Shelf Reference Data
Use this skill to load a bundled, source-attributed snapshot of public
Norwegian Continental Shelf (NCS) facts and run screening-level analysis of
production, resources, and the field inventory. The data is sourced from
norskpetroleum.no (Norwegian Petroleum,
run by the Norwegian Ministry of Energy and the Norwegian Offshore Directorate)
and the Norwegian Offshore Directorate (Sodir, formerly NPD) FactPages, which
publish open, reusable-with-attribution data about NCS activity.
The skill ships a curated public seed (headline national KPIs, a resource
accounting split, sea areas, and a qualitative inventory of major fields) plus a
tolerant ingestion path for the official Sodir yearly saleable-production CSV
exports, so a full production time series and per-field figures can be refreshed
without changing any code. All content is public; no proprietary or confidential
data is included. It is a data and screening-analysis skill, not a reservoir
simulator — quantitative production forecasting must use the validated NeqSim
SimpleReservoir / runReservoir workflows.
When to Use
- When a task needs quick, offline, source-attributed NCS facts (production,
resources, exports, field counts) to frame an analysis.
- When building a production, resource-accounting, or field-inventory study of
the Norwegian shelf and you want a normalized schema plus an ingestion path
for the official Sodir/norskpetroleum.no tables.
- When an agent needs an upstream "NCS context" feed before a validated NeqSim
reservoir-depletion, production-routing, or asset-economics screening.
- When a task needs the public Norwegian carbon-cost basis (CO2 Tax Act rates,
EU ETS allowance cost, NOx Fund contribution) or a first-pass economic
screening of an emission-abatement measure (power-from-shore, waste-heat
recovery, compressor upgrade, flaring reduction) before a validated NeqSim
energy/combustion model and a qualified commercial review.
- When a task needs a screening production forecast: fit an Arps decline
(exponential/hyperbolic/harmonic) to a produced-rate series and project a
forward rate profile, remaining volume, and EUR to an economic-limit rate,
before a validated NeqSim reservoir forecast.
Inputs
- No inputs are required to load the bundled public seed.
NcsDataset.list_fields(...): optional filters sea_area, main_product
(oil/gas), status, operator.NcsDataset.ingest_annual_production(rows): iterable of dicts with year and
either oe_mill_sm3 or component volumes (oil_mill_sm3, gas_bill_sm3,
ngl_mill_sm3_oe, condensate_mill_sm3).NcsDataset.ingest_sodir_production_csv(path): local path to a Sodir yearly
saleable-production CSV export (read locally, no network).NcsDataset.ingest_field_reserves(rows) / ingest_sodir_field_reserves_csv(path):
overlay per-field recoverable/remaining/produced oil-equivalent volumes from
parsed rows or a local Sodir field-reserves CSV export.NcsDataset.ngl_tonne_to_sm3_oe(tonnes): NGL mass to o.e. (1 tonne = 1.9 Sm3 o.e.).carbon_cost_basis(year=None): public Norwegian carbon-cost rates for a year
(default: latest known); falls back to the most recent earlier published year.annual_carbon_cost(co2_tonnes_per_year=..., nox_tonnes_per_year=0.0, year=None, use_combined_co2_cost=True): screening annual carbon cost (NOK/year).abatement_screening(measure=..., fuel_gas_avoided_sm3_per_year=... OR co2_avoided_tonnes_per_year=..., capex_nok=..., added_energy_cost_nok_per_year=0.0, gas_price_nok_per_sm3=0.0, horizon_years=15, discount_rate=0.08): NPV, simple
payback, and breakeven CO2 price of an emission-reduction measure.combustion_co2_tonnes(fuel_gas_sm3_per_year) / emission_source_split(2024).fit_arps_decline(series, from_peak=True): fit an Arps decline model to a
(time, rate) produced-rate series (best of exponential/hyperbolic/harmonic).forecast_production(fit, economic_limit_rate=..., start_time=None, max_years=50.0, timestep_years=1.0, cumulative_to_date=None): forward rate
profile, remaining volume, years-to-limit, and EUR.sodir_download_plan() / refresh_instructions(): offline refresh helper
(returns official download URLs + ingestion routing; no network access).resource_remaining(total_billion_sm3_oe, produced_fraction, latest_annual_oe_mill_sm3=None).
Outputs
national_summary() / national_kpi(key): headline KPIs, each with value,
unit, reference year, note, and source_url.resource_accounting(): total resources and produced/remaining fractions.list_fields(), find_field(), field_counts(): field inventory queries and
aggregations by sea area, product, and status.- Per-field
recoverable_oe_mill_sm3, remaining_oe_mill_sm3, and
cumulative_produced_oe_mill_sm3 on each NcsField (populated by ingestion),
with rank_fields_by_remaining() and remaining_reserves_by_area().
annual_production() / production_for_year(year): the annual o.e. series
(seed plus anything ingested).resource_remaining(...): produced/remaining volumes, remaining fraction, and
a static reserves-to-production (R/P) horizon in years.production_share(record): oil/gas/NGL/condensate share of total o.e.production_trend(series): first-to-last change, CAGR, and rising/falling/flat.fields_started_by_decade(fields): field starts grouped by decade.carbon_cost_basis(year): a CarbonCostBasis with the CO2 tax (per Sm3 gas,
per litre oil, per tonne CO2), gas-venting tax, EU ETS allowance cost, combined
effective CO2 cost, NOx Fund rate, and the public gas combustion factor, each
with source_url and attribution.annual_carbon_cost(...): a CarbonCost with the CO2 tax, EU ETS, combined,
and NOx components plus the total NOK/year.abatement_screening(...): an AbatementScreening with avoided carbon cost,
avoided fuel value, added energy cost, net annual saving, simple payback,
discounted NPV, breakeven CO2 price, a verdict, and stated assumptions.POWER_FROM_SHORE_FIELDS, CO2_SOURCE_SPLIT_2024, GAS_CO2_FACTOR_KG_PER_SM3:
bundled public context constants.fit_arps_decline(...): an ArpsFit with the model name, b-exponent, initial
rate, nominal decline rate (1/year), R-squared, and peak time.forecast_production(...): a with the forward profile, remaining volume, years-to-economic-limit, cumulative-to-date,
and estimated ultimate recovery (EUR), with stated assumptions.
Engineering Method
The bundled seed encodes published headline NCS figures (e.g. 129 fields since
1971 with 97 in production at year-end 2025, 239.2 mill Sm3 o.e. produced in
2025 with more than half gas, and total resources of 15.6 billion Sm3 o.e. of
which 56 % has been produced/sold/delivered), each carrying its own reference
year and source URL. Oil-equivalent aggregation uses the standard NCS convention
1 Sm3 o.e. = 1000 Sm3 gas, so gas in billion Sm3 equals million Sm3 o.e., with
NGL and condensate taken as already in million Sm3 o.e. Resource remaining is a
simple split of the published total by the produced fraction; the R/P horizon is
a static ratio of remaining volume to the latest annual rate, not a forecast.
Production trend and share are descriptive statistics over the (seeded or
ingested) annual series.
This skill performs no reservoir, PVT, or hydraulic physics. It is a transparent
public data layer and screening calculator that must be paired with validated
NeqSim workflows for any quantitative production or forecasting use.
Python Usage Pattern
from norwegian_continental_shelf_data import (
load_dataset, resource_remaining, production_share,
)
ds = load_dataset()
print(ds.attribution)
prod = ds.national_kpi("annual_production_oe")
print(prod["value"], prod["unit"], prod["as_of_year"], prod["source_url"])
ra = ds.resource_accounting()
remaining = resource_remaining(
total_billion_sm3_oe=ra["total_petroleum_resources"]["value"],
produced_fraction=ra["produced_sold_delivered_fraction"]["value"],
latest_annual_oe_mill_sm3=prod["value"],
)
print(remaining.remaining_billion_sm3_oe, remaining.reserve_to_production_years)
barents = ds.list_fields(sea_area="barents_sea")
print(ds.field_counts())
from norwegian_continental_shelf_data import sodir_download_plan
for target in sodir_download_plan():
print(target.dataset, target.factpages_page_url, target.ingest_with)
from norwegian_continental_shelf_data import (
carbon_cost_basis, abatement_screening,
)
basis = carbon_cost_basis()
(basis.co2_tax_nok_per_tonne_co2, basis.combined_co2_nok_per_tonne)
screen = abatement_screening(
measure=,
fuel_gas_avoided_sm3_per_year=,
capex_nok=,
gas_price_nok_per_sm3=,
horizon_years=,
discount_rate=,
year=,
)
(screen.co2_avoided_tonnes_per_year, screen.simple_payback_years,
screen.npv_nok, screen.verdict)
norwegian_continental_shelf_data (
fit_arps_decline, forecast_production,
)
series = [(, ), (, ), (, ), (, ), (, )]
fit = fit_arps_decline(series)
fc = forecast_production(
fit, economic_limit_rate=, max_years=, cumulative_to_date=,
)
(fit.model, fit.decline_rate_per_year, fit.r_squared)
(fc.years_to_limit, fc.remaining_volume, fc.estimated_ultimate_recovery)
Data Refresh
The seed is a snapshot. To load the full, current dataset:
- Download the official yearly production and field tables from the
norskpetroleum.no quick-downloads page
or the Sodir FactPages CSV exports. Use
sodir_download_plan() / refresh_instructions() for the entry points and
the matching ingestion method (offline; it only builds URLs).
- Ingest with
NcsDataset.ingest_sodir_production_csv(path) (yearly
production), NcsDataset.ingest_sodir_field_reserves_csv(path) (per-field
recoverable/remaining reserves), or NcsDataset.ingest_annual_production(rows)
/ ingest_field_reserves(rows) (parsed rows).
- Always keep the source attribution and reference year with any reused figure.
Validated NeqSim Path
This skill supplies public data; it does not forecast production. For
quantitative NCS production analysis use:
- NeqSim
SimpleReservoir (neqsim.process.processTools.simplereservoir) with
gas/oil/water producers and a runTransient(deltat) time loop, and the NeqSim
MCP runReservoir tool for reservoir-versus-time behaviour.
- The community
reservoir-depletion-screening and production-network-routing
skills for a screening reservoir/production chain seeded with these facts.
- The community
asset-value-npv-screening and energy-emissions-screening
skills to turn a production profile into value and emissions screening.
Validation Checklist
Common Mistakes
| Symptom | Cause | Fix |
|---|
| Stale numbers | Using only the bundled seed | Ingest current Sodir/norskpetroleum.no tables |
| Wrong o.e. total | Mixing gas units | Gas in billion Sm3 equals million Sm3 o.e.; keep units consistent |
| Over-reading a field record | Treating operator/status as current truth | Re-verify per-field data against FactPages |
| Forecasting from R/P | Reading the static R/P ratio as a forecast | Use NeqSim SimpleReservoir / runReservoir |
Limitations
- Educational public data layer and screening calculator only; not a validated
design or forecasting method.
- The bundled seed is a curated headline snapshot; per-field production/reserves
and the full annual series require ingesting official exports.
- No reservoir, PVT, hydraulic, or economic physics is performed.
- No confidential or proprietary data is included; attribution to
norskpetroleum.no / the Norwegian Offshore Directorate is required for reuse.
- The carbon-cost basis carries a small set of published annual rates; the
abatement screening is a transparent single-measure cash-flow calculation, not
a certified emission inventory, a marginal-abatement-cost curve, or a validated
energy model. It does not replace, and human review is required before, any
investment or emission-reduction decision.
- The Arps decline forecast is a transparent empirical curve fit to a produced
-rate series; it is not a reservoir simulator or a material-balance model and
does not capture drive mechanism, aquifer, or infill effects. Use validated
NeqSim
SimpleReservoir / runReservoir for quantitative forecasting.
Related NeqSim Functionality
This skill supplies and renders public data; it feeds downstream NeqSim
workflows rather than running calculations itself:
- NeqSim Java:
neqsim.process.processTools.simplereservoir.SimpleReservoir
(runTransient) for reservoir-versus-time production, and
neqsim.process.equipment.pipeline.PipeBeggsAndBrills for flowline/riser
hydraulics downstream of the reservoir.
- NeqSim MCP tools:
runReservoir, runPipeline, runProcess,
runFieldEconomics.
- Reached from Python via
from neqsim import jneqsim (or the devtools setup).
- Community companions:
reservoir-depletion-screening,
production-network-routing, asset-value-npv-screening,
energy-emissions-screening.
References
