Mine/Well Production Forecasts

This use case explains how to forecast production volumes and revenue for mines, wells and other resource assets in Model Reef.

You will:

• Represent mines, wells or fields as branches and sub-branches.

• Build drivers for ore mined, ore processed, grades, recoveries and product yields.

• Connect production to commodity prices, realisations and revenue.

• Capture timing, ramp-up, decline and shut-down behaviour.

Model Reef is not a geological or reservoir simulator. It consumes high-level mine plan or reservoir assumptions and transforms them into financial statements, cashflows and valuations.

When to use this pattern

Use this pattern when:

• Production is driven by mining or extraction of a finite resource.

• You need a forward view of tonnes, grades, recoveries and saleable product.

• You want to link life-of-mine or field plans to P&L, Balance Sheet and Cashflow.

• You need to test price, volume, recovery and cost scenarios.

It works well with:

• Capex & Equipment Lifecycle Model

• Commodity Price Sensitivity

• Multi-Site Resource Consolidation

• Valuation Engine Overview

Architecture overview

1

Structure

• Branches for sites, pits, seams or fields.

• Optional sub-branches for stages, benches or development areas.

2

Production drivers

• Ore or fluid throughput.

• Grades and recoveries.

• Product yields for one or more saleable products.

3

Price and revenue drivers

• Benchmark and realised prices.

• Payable percentages and penalties.

• Currency where relevant.

4

Timing and life of asset

• Ramp-up, steady-state and decline phases.

• Scheduled shutdowns, maintenance and end-of-life.

Step 1: Set up branches for mines, wells and sites

In the branch tree, create a structure that matches how you report operationally, for example:

• Resources Group

  • Mine - Open Cut A

    • Pit - Stage 1

    • Pit - Stage 2

  • Mine - Underground B

  • Field - Gas C

  • Central Overheads

Each mine or field branch should hold that site's production, costs and, in many cases, site-specific capex and rehabilitation provisions. Central Overheads can hold group management, corporate functions and shared costs.

1

Build ore or fluid throughput and grade drivers

In the Data Library, create time-series drivers for each producing asset, for example:

• Ore Mined - Mine A (tonnes per period).

• Ore Processed - Mine A (tonnes per period).

• Head Grade - Mine A (for example grams per tonne or percentage).

• Recovery Rate - Mine A (percentage).

• Fluid Production Rate - Well A (barrels or cubic metres per period).

For multi-product assets, create separate grade and recovery drivers per product where required.

Drivers can be:

• Imported from mine schedules or reservoir models.

• Smoothed from high-level annual plans.

• Scenario-specific for different ramp-up or depletion paths.

From these, define production quantities such as:

• Metal in Ore = Ore Processed × Grade.

• Recovered Product = Metal in Ore × Recovery Rate.

• Saleable Product after processing and losses.

2

Connect production to revenue

Next, create Revenue variables per product and site, for example:

• Revenue - Copper Concentrate - Mine A.

• Revenue - Gold Bullion - Mine B.

• Revenue - Gas Sales - Field C.

For each, specify:

• Benchmark price driver (for example LME, index or contract reference).

• Realisation factors such as treatment and refining charges, payables and penalties.

• Currency drivers if you need to approximate foreign currency revenue.

Formulas might look like:

• Realised Price = Benchmark Price × Payable Percentage - Treatment and Refining Charges per Unit.

• Revenue = Saleable Product Quantity × Realised Price.

Where a site produces multiple products, repeat this process for each and let P&L aggregate them via standard Revenue mapping.

3

Represent ramp-up, steady-state and decline

Use production and grade drivers to reflect the asset life cycle, for example:

• Low volumes in early development and commissioning periods.

• Ramp-up to nameplate capacity over a defined period.

• Steady-state for a number of years.

• Decline as ore or reservoir quality decreases or volumes drop.

• Final shutdown at end-of-life with residual production.

You can:

• Shape throughput and grade drivers directly, or

• Apply modifiers that adjust base throughput and grade by phase.

Ensure that ramp-up and decline patterns align with your technical planning work, and use scenarios to capture uncertainty in ramp-up speed and ultimate recoveries.

4

Capture operating cost structures linked to production

Create Opex and Staff variables that link to production drivers, for example:

• Opex - Mining Costs - per Tonne Mined.

• Opex - Processing Costs - per Tonne Processed.

• Opex - Power and Utilities - per Tonne or per Unit of Product.

• Opex - Royalties and Production Taxes - per Unit or Percentage of Revenue.

• Staff - Site Operations and Maintenance Teams.

Formulas can be:

• Mining Cost = Ore Mined × Cost per Tonne Mined.

• Processing Cost = Ore Processed × Cost per Tonne Processed.

• Royalties = Revenue × Royalty Rate.

This keeps costs aligned with production volumes and makes margin sensitivity analysis more meaningful.

5

Add shutdowns, maintenance and unscheduled downtime

Use timing and frequency settings or modifiers to represent:

• Planned shutdowns for major maintenance.

• Seasonal restrictions that limit production.

• Unplanned downtime allowances based on historical performance.

This is often implemented as:

• Uptime factors applied to throughput drivers.

• Additional Opex variables for major maintenance events.

• Adjustments to cost drivers when running at partial capacity.

The aim is to ensure that both production and cost patterns capture realistic operating schedules.

6

Use scenarios for volume, grade and recovery risk

Clone the mine or portfolio model into scenario models to test:

• Different grade and recovery paths (for example optimistic, base and pessimistic).

• Higher or lower throughput rates.

• Different ramp-up durations and start dates.

• Changes in product mix or by-product credits.

In each scenario, adjust relevant drivers and examine:

• Revenue and margin patterns over time.

• Cashflow profiles and peak funding requirements.

• Life-of-mine or field valuation metrics from the Valuation Engine.

• Impact on debt capacity and covenant headroom.

Check your work

• Production profiles match mine plans or engineering outputs when calibrated.

• Revenue and cost structures reconcile to historical performance for operating assets.

• Ramp-up and decline behaviour looks realistic to operational and technical stakeholders.

• Scenario outcomes align qualitatively with risk narratives used internally.

Troubleshooting

Production volumes do not match technical schedules

Check that you are using the same unit basis, time resolution and loss factors as your mine planning team and that you have not double counted recoveries.

Margins behave strangely at low throughput

Separate fixed and variable costs where helpful and ensure volume linked cost drivers are not applied to zero or minimal production periods unless that reflects real costs.

Model feels overly complex for early stage studies

Start with simple annual average grades and recoveries, then only add more detailed patterns when you have better information or the decision warrants it.

Related guides

• Build a Board Reporting Pack

• Build a Bottom Up Forecast

• Historical Fundamentals Imported

• Variable Type