vamseeachanta SODIR Data Extractor Skill
Extract and process Norwegian Petroleum Directorate (SODIR) field and production data
When to Use This Skill
Use this skill when you need to:
- Extract Norwegian continental shelf field data
- Query SODIR production statistics
- Compare Norwegian fields with GOM fields
- Build cross-basin analysis datasets
- Access historical NCS field performance
Core Pattern
"""
ABOUTME: Norwegian Petroleum Directorate (SODIR) data extraction
ABOUTME: Provides field and production data from the Norwegian Continental Shelf
"""
from dataclasses import dataclass
from typing import List, Optional
import requests
import pandas as pd
@dataclass
class SODIRField:
"""Norwegian field information."""
field_name: str
discovery_year: int
status: str # PRODUCING, SHUT DOWN, etc.
operator: str
area_name: str # Quadrant/block area
water_depth_m: float
recoverable_oil_mmbbl: float
recoverable_gas_bcm: float
@dataclass
class SODIRProduction:
"""Monthly production record."""
field_name: str
year: int
month: int
oil_kbbl: float
gas_msm3: float
ngl_kbbl: float
condensate_kbbl: float
water_kbbl: float
class SODIRDataClient:
"""
Client for SODIR (Norwegian Petroleum Directorate) data.
Data sources:
- https://factpages.sodir.no/
- Public API and downloadable datasets
"""
BASE_URL = "https://factpages.sodir.no/api"
def __init__(self, cache_dir: str = ".cache/sodir"):
self.cache_dir = cache_dir
def get_field_list(self, status: str = None) -> List[SODIRField]:
"""
Get list of Norwegian fields.
Args:
status: Filter by status (PRODUCING, SHUT DOWN, etc.)
Returns:
List of SODIRField objects
"""
# Download field data from SODIR
url = f"{self.BASE_URL}/field"
response = requests.get(url)
data = response.json()
fields = []
for item in data:
if status and item.get("status") != status:
continue
fields.append(SODIRField(
field_name=item["fldName"],
discovery_year=item.get("fldDiscoveryYear", 0),
status=item.get("fldStatus", ""),
operator=item.get("cmpLongName", ""),
area_name=item.get("fldArea", ""),
water_depth_m=item.get("fldWaterDepth", 0),
recoverable_oil_mmbbl=item.get("fldRecoverableOil", 0),
recoverable_gas_bcm=item.get("fldRecoverableGas", 0)
))
return fields
def get_field_production(
self,
field_name: str,
start_year: int = None,
end_year: int = None
) -> pd.DataFrame:
"""
Get monthly production for a field.
Args:
field_name: SODIR field name
start_year: Optional start year filter
end_year: Optional end year filter
Returns:
DataFrame with monthly production
"""
url = f"{self.BASE_URL}/field/{field_name}/production"
response = requests.get(url)
data = response.json()
records = []
for item in data:
year = item.get("prfYear", 0)
if start_year and year < start_year:
continue
if end_year and year > end_year:
continue
records.append(SODIRProduction(
field_name=field_name,
year=year,
month=item.get("prfMonth", 1),
oil_kbbl=item.get("prfPrdOilNetMillSm3", 0) * 6.29,
gas_msm3=item.get("prfPrdGasNetBillSm3", 0),
ngl_kbbl=item.get("prfPrdNGLNetMillSm3", 0) * 6.29,
condensate_kbbl=item.get("prfPrdCondensateNetMillSm3", 0) * 6.29,
water_kbbl=item.get("prfPrdProducedWaterInFieldMillSm3", 0) * 6.29
))
df = pd.DataFrame([vars(r) for r in records])
df["date"] = pd.to_datetime(
df[["year", "month"]].assign(day=1)
)
return df.sort_values("date")
def compare_with_gom(
self,
ncs_field: str,
gom_api: str
) -> pd.DataFrame:
"""
Compare NCS field with GOM well production.
Returns aligned production comparison.
"""
# Get NCS data
ncs_df = self.get_field_production(ncs_field)
# Get GOM data (via BSEE client)
from worldenergydata.bsee.data import get_production_data
gom_df = get_production_data(api_number=gom_api)
# Align by months on production
ncs_df["months"] = range(len(ncs_df))
gom_df["months"] = range(len(gom_df))
comparison = pd.merge(
ncs_df[["months", "oil_kbbl"]].rename(columns={"oil_kbbl": "ncs_oil"}),
gom_df[["months", "oil_bbl"]].rename(columns={"oil_bbl": "gom_oil"}),
on="months",
how="outer"
)
return comparison
YAML Configuration Template
# config/input/sodir-extraction.yaml
metadata:
feature_name: "sodir-extraction"
created: "2025-01-15"
data_source:
type: "sodir"
cache_enabled: true
cache_ttl_days: 7
query:
fields:
- "JOHAN SVERDRUP"
- "TROLL"
- "EKOFISK"
status_filter: "PRODUCING"
start_year: 2015
end_year: null
output:
format: "csv"
path: "data/sodir/"
include_metadata: true
CLI Usage
# Extract field list
python -m worldenergydata.sodir \
--action list-fields \
--status PRODUCING \
--output data/sodir/fields.csv
# Get production data
python -m worldenergydata.sodir \
--action production \
--field "JOHAN SVERDRUP" \
--start-year 2019 \
--output data/sodir/johan_sverdrup.csv
Best Practices
- Cache SODIR data locally to reduce API calls
- Use field names exactly as they appear in SODIR
- Convert units (Sm3 to bbl) for comparison with BSEE data
- Handle missing data gracefully for early production periods