npv-analyzer

This sub-skill provides YAML configuration templates for structuring queries to extract BSEE oil and gas data. It supports multiple query types (by block, API, lease, field, or area) across different datasets including WAR and APD. Developers use it to define structured parameters for targeted data extraction from BSEE systems.

This skill performs decline curve analysis to forecast oil and gas well production and estimate ultimate recovery (EUR). It fits Arps models, generates type curves, and supports probabilistic outputs for reserve calculations. Use it for production forecasting, reserve estimation, and field development planning in energy applications.

This skill provides a basic example of implementing a Net Present Value (NPV) calculation for an oil and gas project using a dedicated Python library. It demonstrates how to define core components like production forecasts, price assumptions, and fiscal terms to model project economics. Use this as a starter template for simple cash flow analysis before moving to more complex scenarios.

This skill provides structured data models and Python classes for extracting and processing BSEE oil and gas production data. It includes Pydantic/dataclass models for well records, production data, and API clients to handle BSEE's public datasets. Use this reference skill when you need to programmatically access, parse, or analyze standardized offshore energy production data.