npv-analyzer

name	npv-analyzer
description	Perform NPV analysis and economic evaluation for oil & gas assets. Use for cash flow modeling, price scenario analysis, Monte Carlo simulation, P10/P50/P90 probabilistic analysis, working interest calculations, and financial metrics (IRR, payback, NPV) for field development projects.
type	reference
version	1.0.0
category	data/energy
capabilities	[]
requires	[]
tags	[]

Npv Analyzer

When to Use

• Calculating NPV for field development projects
• Modeling cash flows with production forecasts
• Running oil/gas price scenario analysis (low/mid/high)
• Monte Carlo simulation for P10/P50/P90 NPV estimates
• Probabilistic risk analysis with multiple input distributions
• Applying working interest and royalty calculations
• Evaluating different development types (subsea, platform, FPSO)
• Computing IRR, payback period, and profitability index
• Calculating Value at Risk (VaR) and Expected Shortfall
• Comparing economic outcomes across multiple scenarios

Core Pattern

Production Forecast → Price Assumptions → Cash Flow Model → Discount → Metrics

Implementation

Data Models

from dataclasses import dataclass, field
from datetime import date
from typing import Optional, List, Dict, Tuple
from enum import Enum
import numpy as np
import pandas as pd

class DevelopmentType(Enum):
    """Field development concepts."""

*See sub-skills for full details.*
### NPV Calculator

```python
from typing import List, Dict, Optional
import numpy as np
import numpy_financial as npf

class NPVCalculator:
    """
    Calculate NPV and related economic metrics for oil & gas projects.
    """


*See sub-skills for full details.*
### Scenario Analyzer

```python
from typing import List, Dict
from dataclasses import replace
import pandas as pd

class ScenarioAnalyzer:
    """
    Run multiple NPV scenarios with different price assumptions.
    """


*See sub-skills for full details.*
### Monte Carlo Simulator

```python
 dataclasses  dataclass, field
 typing  , , , 
 enum  Enum
 numpy  np
 pandas  pd

 ():
    
    NORMAL = 

*See sub-skills  full details.*


```python
 plotly.graph_objects  go
 plotly.subplots  make_subplots
 pathlib  Path

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