npv-analyzer-model-setup

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.

The npv-analyzer skill performs economic evaluation and Net Present Value (NPV) analysis for oil & gas assets. Developers can use it for cash flow modeling, price scenario analysis, and Monte Carlo simulations to generate P10/P50/P90 probabilistic outputs. It also calculates key financial metrics like IRR and payback period for field development projects.