From Shells to Stages: How to Select Pushbacks with Confidence 

1. Why Pushbacks?

If you’ve ever opened your pit optimisation software and seen 20 nested shells glowing on the screen, you’ll know the feeling: Which ones are real pushbacks?

Every junior planner faces this. The Lerchs–Grossmann (LG) or Pseudoflow algorithm happily hands you a family of shells. They’re all legal, all valid, all economic at some revenue factor (RF). But you can’t mine 20 stages. You can barely manage 6. In practice, most mines run on 3–4 pushbacks.

So the real question is: how do we go from a wall of shells → a handful of stages that actually work in the pit?

This article is your plain-language, mining-fluent guide. We’ll walk through where shells come from, how to “read” them for knees, how to reshape them into mineable pushbacks, and what pitfalls to avoid.

By the end, you’ll have the confidence to look at a nested shell pack and say: “These are our 3 pushbacks, here’s the math, and here’s why.”

👉🏽 You don’t need to build everything from scratch — we’ve linked a working Pushback Picker Template (Excel) below. Paste your shell summary into the input sheet and the graphs, efficiency plots, and stage picker are generated automatically. 

  2. Quick Refresher: The Building Blocks

Before we cut into pushbacks, let’s ground ourselves in the language every mine planner knows.

2.1 Optimisation

At its heart, optimisation is simply making the best decision under constraints. In mining, those constraints include geotechnical slopes, fleet availability, processing limits, operating costs, and permitting boundaries. The objective is always the same: to extract the maximum possible value, whether measured in NPV, cash flow, or ore tonnes delivered to the plant. A simple way to picture this is to imagine running a hotel. The rooms are your plant capacity, and the guests are your different ore types. You can’t host everyone, so you prioritise the guests who pay the highest rates — the ore that delivers the strongest margins. But just like a hotel must still follow the fire code and housekeeping capacity, your plan must still respect slope rules and mining fleet limits. Optimisation, then, is the discipline of filling your “hotel” with the best-paying guests without ever breaking the rules. 

2.2 Lerchs–Grossmann (LG) Algorithm

The Lerchs–Grossmann (LG) algorithm, developed back in 1965, is still the backbone of pit optimisation in tools like Whittle and Vulcan. It works by treating each block in the model as a node with a value equal to its revenue minus its cost. To keep slopes safe, the algorithm adds arcs of precedence — meaning if you want to mine one block, you must also mine all the blocks that support it. LG then solves for what’s called the maximum closure, which is simply the pit shape that delivers the maximum undiscounted value while obeying slope rules. For larger, more complex models, many planners now use Pseudoflow, LG’s faster cousin, which produces the same ultimate pit but in a fraction of the time. 

2.3 Nested Shells

The software doesn’t just give you a single pit; instead, it runs the optimisation across a range of Revenue Factors (RFs) — multipliers on metal price, recovery, and payability. At a low RF, say 0.4, you’re pretending prices are lower than reality, which produces a small, tight pit that only captures the richest core. At RF = 1.0, you’re working with today’s actual prices, giving you the economic ultimate pit. At RF values above 1.0, you’re effectively pretending prices are higher, and the pit grows larger by including more marginal ore and higher stripping. Each RF produces a different pit shell, and together these shells stack inside one another like Russian dolls, forming what we call nested shells. 

2.4 Strip Ratio

The strip ratio, defined as waste divided by ore, is the heartbeat of every open pit mine. A low strip ratio means you’re getting plenty of ore for little waste movement, making mining cheap and margin-rich. A high strip ratio, on the other hand, means you’re spending huge effort moving waste just to free up a little ore — expensive and unsustainable. As you can see in the graph below, strip ratio tends to creep upward slowly as revenue factors (RFs) increase, but eventually the curve bends sharply. That bend — where waste suddenly takes off while value growth slows — is exactly where pushback selection becomes most interesting. 

2.5 Pushbacks

A pushback is not just a shell. While shells are theoretical pit outlines generated by optimisation, a pushback is a mineable slice carved out of those shells and reshaped to work in the real world. That means cleaning up the shell geometry to allow proper ramp access, maintaining working widths for equipment, and ensuring wall continuity for safe, efficient mining. In other words, shells are the theory, but pushbacks are what the dozers and trucks actually move. It’s the vital step where software outlines are transformed into practical designs that operations can execute. 

3. The Core Problem: Too Many Shells

When you run LG or Pseudoflow, the optimisation typically generates 20–25 nested shells. They’re all valid, but you can’t mine them all. If you tried to mine the pit as one giant stage, cash flow would collapse because you’d be stripping waste for years before delivering meaningful ore to the plant. On the other hand, if you carved six or more stages, you’d quickly run into problems: multiple narrow working faces competing for equipment, ramps overlapping into “spaghetti,” and unstable mining interfaces between stages. That creates congestion, increases rehandles, and makes blending harder.

Experience shows the sweet spot is usually three to four pushbacks, depending on the size of the deposit. With this number, you can maintain sufficient mining width for trucks and shovels to work efficiently, while still sequencing ore early enough to support healthy cash flow. It also reduces the number of stage interfaces — those tricky contacts between one pushback and the next that often become bottlenecks if you slice the pit too finely. The real skill in mine planning is selecting which shells to stop at, balancing the economics with the geometry so each stage is both profitable and mineable.

4. The Method: Reading the Knees

So how do we cut down a family of 20 nested shells into the 3–4 pushbacks we can actually mine? The answer lies in reading the knees in the optimisation curves. By plotting Value vs Revenue Factor (RF) and Strip Ratio vs RF, we can see where the returns from expanding the pit begin to flatten while the cost of waste movement accelerates. These inflection points — the “knees” of the curves — mark the natural boundaries where it makes economic and operational sense to stop one stage and begin the next. In practice, they are the stepping stones that guide us from theoretical shells to practical, defendable pushbacks. 

4.1 The Two Curves

Take a look at the Value vs RF graph. Notice how the curve rises steeply at the beginning and then gradually flattens as the shells expand and more marginal ore is included. Now compare that to the Strip vs RF graph: at first, the line creeps upward almost flat, but then bends sharply as waste begins to grow faster than ore. The point where these two stories cross — where value stops rewarding you while strip starts punishing you — is the knee. That inflection on the graphs is your natural boundary for selecting a pushback. 

4.2 The Efficiency Trick

To make the knees stand out more clearly, we look not just at the curves but at the step-by-step changes between shells. For each pair of shells, calculate the difference in value (ΔValue=Valuei+1−Valuei)(ΔValue = Value_{i+1} − Value_i)(ΔValue=Valuei+1​−Valuei​) and the difference in strip ratio (ΔStrip=Stripi+1−Stripi)(ΔStrip = Strip_{i+1} − Strip_i)(ΔStrip=Stripi+1​−Stripi​). Then divide one by the other to get the efficiency, which tells you how much extra value you’re gaining for every unit of extra strip.

On the efficiency plot, the early shells usually show high numbers — you’re getting a lot of value for only a little extra waste. But when efficiency suddenly collapses compared to the last few steps, that sharp drop is your knee. If you look at the efficiency graph alongside the Value vs RF and Strip vs RF curves, you’ll see they all tell the same story: the pushback boundary is right at the point where returns fall off and waste surges.

👉🏽 You can skip the manual math — the Pushback Picker Excel Template automatically calculates ΔValue, ΔStrip, and Efficiency, and highlights candidate knees for you. Just paste your RF shell summary into the input sheet and the graphs update instantly.

Read it aloud like a planner:

• 0.40→0.50: +$30M for +0.1 strip = eff 300 (amazing).
  
  

• 0.50→0.60: +$30M for +0.2 strip = eff 150 (great).
  
  

• 0.60→0.70: +$20M for +0.3 strip = eff 66 (slowing).
  
  

• 0.70→0.80: +$15M for +0.4 strip = eff 37.5 (warning).
  
  

• 0.80→0.90: +$10M for +0.5 strip = eff 20 (ouch).
  
  

• 0.90→1.00: +$5M for +0.7 strip = eff 7.1 (painful).
  
  

• 1.00→1.10: +$2M for +1.5 strip = eff 1.3 (nope).
  
  

So the knees are at 0.60, 0.80, 1.00. That’s three pushback boundaries.

5. Turning Shells → Pushbacks

One of the most common rookie mistakes is to take an optimisation shell — say RF 0.60 — and declare, “That’s Stage 1.” But raw shells are rarely mineable. They often come with fingers too skinny for trucks to turn, isolated islands of ore with no access, or walls so tight there’s no room for a ramp at all. A true pushback is a reshaped shell: you trim off those beaks and spurs, merge isolated pods into a coherent shape, reserve ramp corridors at your design gradient (typically around 10%), and choose a consistent mining direction, such as advancing north-to-south or east-to-west. Only after this cleanup does a shell become a pushback that equipment can actually work safely and efficiently. It’s the point where theory meets practice — and the dozers, shovels, and trucks can finally do their job. 

6. Why Few Pushbacks Is the Sweet Spot

Get the number of stages wrong, and everyone feels the pain. With too few pushbacks — just one or two — the CFO cries, because ore is delayed, cash flow dries up, and NPV collapses under years of pre-stripping. With too many — six or more — the dispatchers cry, as ramps overlap, traffic turns into chaos, and blending becomes unstable. The sweet spot, proven again and again in gold and copper pits, is usually three to four pushbacks. That range balances both sides of the equation: early cash to keep finance happy, and enough working width and clean traffic flow to keep operations running smoothly. 

7. Common Pitfalls (And How to Dodge Them)

Deepest Shell Bias

• ❌ Mistake: Picking the largest shell just because it looks like the “ultimate” answer.

• ⚒️ Fix: Focus on the knees of the Value vs RF and Strip vs RF curves. Stop where the economics turn against you, not where the shell goes deepest.

Averaged Recoveries

• ❌ Mistake: Using a single recovery figure across all domains.

• ⚒️ Fix: Apply domain-specific recoveries and penalties so your shell economics match your cut-off and blending strategy later on.

Ramp Afterthought

• ❌ Mistake: Designing stages without leaving space for ramps, then discovering access doesn’t work.

• ⚒️ Fix: Reserve ramp corridors at the start (e.g., 10% gradient, switchback radii) to avoid painful redesigns.

No Guardbands

• ❌ Mistake: Planning right up to spec limits (e.g., As = 0.50%).

• ⚒️ Fix: Always apply buffers (e.g., plan at 0.45%) to allow for operational variability, sampling errors, and blending fluctuations.

Pretty Shell Trap

• ❌ Mistake: Falling in love with elegant-looking shells that have fingers, necks, or isolated islands.

• ⚒️ Fix: Remember that true beauty = clean traffic flow. Trim beaks, merge islands, and aim for continuous walls that trucks can work efficiently.

8. The Planner’s Checklist (Tomorrow at Your Desk)

Generate 20 nested shells (LG/Pseudoflow).
Use consistent economics (price, recovery, payability, costs, royalty, slopes). Keep RFs ascending.

Plot the curves: Value vs RF and Strip vs RF.
These are your primary readers—steep-then-flat for Value, flat-then-steep for Strip.

Compute step efficiency (ΔValue / ΔStrip).
For each RF step, calculate ΔValue and ΔStrip, then Efficiency = ΔValue ÷ ΔStrip. Add a 3-step moving average for context.

Identify and circle 3–4 knees.
Knees are where Efficiency collapses versus recent steps and where Value flattens while Strip bends up. Mark these directly on the graphs.

Select those RFs as candidate pushbacks.
Define Stage 1, 2, 3 (and optional 4) using the knee RFs as boundaries.

Reshape for mineability.
Trim fingers, merge islands, reserve ramp corridors at design gradient (~10%), verify switchback radii, and lock a clear advance direction (e.g., N→S).

Check stage durations and cash costs.
Estimate months at plant rate; sanity-check strip, unit mining cost, G&A, and cash cost per ounce/tonne against site thresholds.

Export a one-pager for review.
Include: stage table (RF From/To, Ore, Waste, Strip, Duration, Cost notes), the Value vs RF and Strip vs RF graphs with knees circled, and a small map view with ramp corridors inked in.

9. Why This Matters for Cash Flow and Market

Pushbacks are not just an engineering exercise — they are fundamentally about economics. Early pushbacks are designed to bring ore forward, protecting net present value (NPV) by generating cash flow sooner rather than later. Later pushbacks, on the other hand, often act as options — stages that can be mined if and when market conditions improve, but which aren’t essential to the base plan. The Revenue Factor (RF) is your price dial, just like interest rates are for bankers stress-testing mortgages. By testing pushbacks across different RF scenarios, you can see how robust your plan is to price swings. When the market moves, a well-designed pushback strategy flexes with it, ensuring the mine remains both profitable and executable. 

10. Final Word

Pushbacks are never guesses — they’re the product of a disciplined process. They are first born from LG or Pseudoflow shells, then selected at the knees of the Value and Strip curves, and finally reshaped into mineable stages with ramps, widths, and clean geometry. Once you understand this flow, you’ll never fear staring at a pack of 20 shells again. Instead, you’ll be able to stand at the pit crest, point to the curves, and confidently say: “These three pushbacks. They’re mineable, profitable, and defendable.” That moment of clarity is the true “aha” every planner remembers — when theory, economics, and practical mining all click into place.

👉🏽 To put this into practice right now, download the Pushback Picker Excel Template. Paste in your RF shell summary, and the workbook will generate the Value vs RF, Strip vs RF, and Efficiency curves — with knees highlighted — so you can identify pushbacks with confidence.