Neqsim Asset Value Npv Screening

Asset Value (NPV) Screening

Use this skill for a quick, public discounted-cash-flow (DCF) screening of an asset. Given a year-by-year revenue series, an OPEX series (or a flat value), and a CAPEX schedule (or a single year-0 spend), it computes net cash flow, discounts it to a net present value (NPV), and estimates IRR and payback. It is a transparent placeholder that should guide users toward the validated NeqSim field-development DCF utilities and the NeqSim MCP runFieldEconomics workflow.

When to Use

• When a user wants a first-pass NPV / IRR / payback for a concept.
• When an agent has a production-and-price revenue profile plus a cost screen.
• When examples must run without confidential fiscal terms or licensed tools.

Inputs

• annual_revenue_musd: sequence of annual revenues in million USD (one per year).
• annual_opex_musd: a flat OPEX or a per-year sequence in million USD.
• capex_schedule_musd: a single year-0 spend or a per-year sequence in million USD.
• discount_rate_fraction: annual discount rate (default 0.08).
• tax_rate_fraction: flat tax on positive operating profit (default 0.0).

Outputs

• net_cash_flow_musd: per-year revenue - OPEX - tax - CAPEX.
• discounted_cash_flow_musd: per-year discounted cash flow.
• cumulative_cash_flow_musd: running (undiscounted) cumulative cash flow.
• npv_musd: net present value.
• irr_fraction: internal rate of return (or None if not identifiable).
• payback_year / discounted_payback_year: first year cumulative turns non-negative.
• total_capex_musd / total_revenue_musd: roll-up totals.
• value_warning: ok (NPV>0), watch (NPV=0), or high (NPV<0).
• neqsim_available: whether the optional NeqSim package is importable.
• assumptions: public assumptions and required follow-up.

Engineering Method

For each year, operating profit is revenue - OPEX; tax is tax_rate * max(0, operating profit); net cash flow is operating profit - tax - CAPEX. NPV discounts each net cash flow at year-end: NPV = sum(CF_t / (1 + r)^t) for t = 1..N. IRR is the rate that zeroes NPV, found by bisection over a wide bracket (returns None when there is no sign change). Payback is the first year cumulative cash flow becomes non-negative.

This skill models no inflation, depreciation, uplift, ring-fencing, financing, or working capital. It is a placeholder that must be replaced by validated NeqSim economics for any quantitative or commercial use.

Python Usage Pattern

from asset_value_npv_screening import AssetValueModel

model = AssetValueModel()
result = model.evaluate(
    annual_revenue_musd=[0.0, 300.0, 320.0, 280.0, 230.0, 180.0],
    annual_opex_musd=40.0,
    capex_schedule_musd=[600.0, 200.0, 0.0, 0.0, 0.0, 0.0],
    discount_rate_fraction=0.08,
    tax_rate_fraction=0.78,
)

print(result.npv_musd)
print(result.irr_fraction)
print(result.payback_year)
print(result.value_warning)

Validated NeqSim Path

This screening is a placeholder. For real asset economics use:

• The field-development DCF utilities in neqsim.process.util.fielddevelopment for cash-flow modelling, fiscal regimes, and uncertainty (see the neqsim-field-economics skill).
• The NeqSim MCP runFieldEconomics tool for an orchestrated NPV/IRR evaluation with tax regimes (Norwegian NCS, UK, generic) and Monte Carlo sensitivity.

Escalation

Escalate any high verdict, any negative NPV, and any commercial decision to a validated NeqSim economics evaluation and qualified commercial review.

Validation Checklist

• Inputs are validated and within stated ranges.
• Examples use public data only.
• Screening assumptions are stated explicitly.
• Limitations are respected.
• Quantitative use is escalated to validated NeqSim models.

Common Mistakes

Limitations

• Educational screening only; not a validated design method.
• No confidential data or proprietary methods are included.
• Escalate any quantitative or design use to validated NeqSim workflows.

References

• NeqSim repository: https://github.com/equinor/neqsim
• NeqSim Skills Guide: https://github.com/equinor/neqsim/blob/master/docs/integration/skills_guide.md