Soheil K.

"Do you generate a separate sequence for each orebody simulation?" I hear this very often. And the short answer is: 𝗡𝗼. 𝗡𝗼. 𝗔𝗻𝗱 𝗮𝗯𝘀𝗼𝗹𝘂𝘁𝗲𝗹𝘆 𝗻𝗼. Think about it: If you had a different extraction sequence for every simulation, which one would you follow? Which one would the medium and short-term planners inherit? Which one would operations execute in practice? It would be 𝗰𝗵𝗮𝗼𝘀. Planning needs clear and actionable guidance, not 100 sequencing versions. Let me break it down simply: When you're solving a LoM plan optimization problem using block-based scheduling approach, there are three major decisions to be made: • 𝗘𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲 (which blocks to mine and when) • 𝗖𝘂𝘁-𝗼𝗳𝗳/𝗱𝗲𝘀𝘁𝗶𝗻𝗮𝘁𝗶𝗼𝗻 𝗽𝗼𝗹𝗶𝗰𝘆 (where the material goes: mill, stockpile, leach pad, waste, etc.) • 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝘀𝘁𝗿𝗲𝗮𝗺 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 (material flow after the block's first destination is determined) Now, here’s the important part: The extraction sequence is what’s called a 𝗳𝗶𝗿𝘀𝘁-𝘀𝘁𝗮𝗴𝗲 decision (in two-stage stochastic optimization terminology). Which means: It must be defined 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄 before any additional information is revealed. It is also called a 𝘀𝗰𝗲𝗻𝗮𝗿𝗶𝗼-𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁 decision. You need a sequence that planning teams can actually work with. "First-stage" decisions are commitments you make before knowing exactly what Mother Nature has prepared for you. They're the backbone of the mine plan. ✅ So what sequence does stochastic mine planning actually give you? • A 𝘀𝗶𝗻𝗴𝗹𝗲 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝗱 𝗲𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲. • Built by looking at all orebody simulations 𝘀𝗶𝗺𝘂𝗹𝘁𝗮𝗻𝗲𝗼𝘂𝘀𝗹𝘆. • Designed to 𝗺𝗮𝘅𝗶𝗺𝗶𝘇𝗲 𝗡𝗣𝗩 while trying to minimize deviations from targets across uncertainties. In other words: You don't optimize for one future. 𝗬𝗼𝘂 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗮𝗰𝗿𝗼𝘀𝘀 𝗺𝗮𝗻𝘆 𝗳𝘂𝘁𝘂𝗿𝗲𝘀, and find the path that, on average, gives you the best, and 𝗺𝗼𝘀𝘁 𝗿𝗶𝘀𝗸-𝗿𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝘁 𝗼𝘂𝘁𝗰𝗼𝗺𝗲. That’s why the extraction sequence is scenario-independent. That’s why stochastic planning works in the real world and major mining companies are starting to integrate it into their planning workflow. So next time someone asks: "Do you generate a sequence for every simulation?" you can just smile and say: "𝗡𝗼, 𝘄𝗲 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲 𝗼𝗻𝗲 𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲 𝘁𝗵𝗮𝘁'𝘀 𝘀𝗺𝗮𝗿𝘁 𝗲𝗻𝗼𝘂𝗴𝗵 𝘁𝗼 𝘀𝘂𝗿𝘃𝗶𝘃𝗲 𝘁𝗵𝗲𝗺 𝗮𝗹𝗹." 𝘐𝘯 𝘧𝘶𝘵𝘶𝘳𝘦 𝘱𝘰𝘴𝘵𝘴, 𝘐 𝘸𝘪𝘭𝘭 𝘵𝘢𝘭𝘬 𝘢𝘣𝘰𝘶𝘵 𝘵𝘩𝘦 𝘰𝘵𝘩𝘦𝘳 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯 𝘵𝘺𝘱𝘦𝘴 𝘢𝘯𝘥 𝘩𝘰𝘸 𝘸𝘦 𝘨𝘦𝘵 𝘱𝘳𝘰𝘣𝘢𝘣𝘪𝘭𝘪𝘴𝘵𝘪𝘤 𝘧𝘰𝘳𝘦𝘤𝘢𝘴𝘵𝘴 𝘰𝘶𝘵 𝘰𝘧 𝘢 𝘴𝘪𝘯𝘨𝘭𝘦 𝘳𝘪𝘴𝘬–𝘳𝘦𝘴𝘪𝘭𝘪𝘦𝘯𝘵 𝘴𝘦𝘲𝘶𝘦𝘯𝘤𝘦. 𝘚𝘵𝘢𝘺 𝘵𝘶𝘯𝘦𝘥!

Let’s be honest—most people picture bankers as the folks who show up after the hard work is done, sign a few papers, and disappear until the next commodity cycle. But the reality? Far more interesting. And, honestly, a lot more demanding. I just watched the latest Fresh Thinking podcast, where Tarrant Elkington sat down with Bob Jankovic (former technical advisor at Scotiabank). And they shared some insights that are definitely worth thinking about for anyone in mining. Here’s what stood out: ✅ Banks aren’t just writing cheques—they’re technical gatekeepers. Banks ideally step in with their technical team after the "bankable" feasibility study is published and permits are issued. Before a single dollar moves, banks conduct deep technical due diligence. We’re talking about independent reviews, resource and reserve scrutiny, and, most importantly, a rigorous level of risk assessment. Why? Because banks don’t gamble. They invest. And they want to know your project can survive more than just a PowerPoint pitch. ✅ The “bankable feasibility study” isn’t just a box to tick. It’s your passport to capital. One key message was that while many obsess over “measured" vs. "indicated” classification ratios, what truly matters is the technical soundness and defensibility of your resource classification not just the ratios. Another note as Bob put it: 🛑“The highest risk definitely starts from the block model, and the resource/reserve interpretation.”🛑 That’s a line we don’t hear often enough, and it should make anyone pause. ✅ Junior miners, take note: If you want funding, don’t wait for the bank to uncover your blind spots. Get strong technical reviews early (independent or internal). It’s not just about impressing the suits—it’s about building real, evidence-based confidence in your project. So, what’s the bigger lesson here? Mining finance is about recognizing where uncertainty lies and confronting it in advance. The more we integrate structured risk analysis—especially around the geological model—the better we align our projects with the real expectations of capital markets. If you’re an executive, technical lead, or someone aiming to build more risk-resilient mining projects, it might be time to rethink how we quantify and communicate geological risk. 📺 Check out the full episode: https://youtu.be/JfxD5z0QXZU?si=1Se1Vj1kvFrOqu9l

Every mine plan looks good... on paper. Production targets are met. Budgets approved. Equipment ordered. Everyone feels good until the mine starts underperforming. Month after month. Quarter after quarter. And the excuses pile up: “Unexpected dilution” “Poor ground conditions” “Operational delays” But here’s the truth nobody wants to say out loud: The real failure happened years earlier, when we trusted the orebody model more than we should have. Mining is the only industry I know that builds billion-dollar businesses on statistical guesses... and then gets surprised when reality doesn't cooperate. Geological uncertainty is not a rounding error. It’s not a minor risk. It's shown to be the major contributor to project failures. It’s the foundation your entire operation stands on, or collapses on. And yet, companies build LOM plans assuming the estimated block model is the ground truth. Why? Because it's easier to assume certainty than to quantify uncertainty and plan for it. Because spreadsheets are cleaner when you don’t have multiple scenarios. Because no one wants to explain to the board that the “high-confidence” resource might still let them down. But pretending the orebody is perfect doesn't protect you. It just delays the realization. 🔍 Here’s what actually happens: Resource models, even “measured” ones, have built-in errors, including grade, volume, and continuity errors. Estimation methods like Kriging smooth out the grades, where high-grades (where we make money!) are underestimated, and low-grades are overestimated. Mine plans are optimized assuming every block behaves exactly as estimated. Operations find out the hard way that Mother Nature didn’t read the single 3D model. 🔴 And the cost? Missed production targets. Inability to control contaminants at the plant. Cash flow shortfalls. Poor reconciliation. Erosion of investor trust. Bad CAPEX decisions. Inability to fulfill contracts. All because we decided to ignore the geological uncertainty! ✅ What actually works? Quantify uncertainty, early and often. Simulate multiple orebody realizations that reproduce the local variability under the ground instead of relying on a single “best guess.” Optimize the strategic mine plan looking at all simulations. This will ensure you have integrated risk-management, prioritizing less risky, yet rich, areas early on till more information is available for later project stages. Report the production schedules probabilistically. Mining doesn’t fail because it’s inefficient. It fails because it assumes the earth will behave the way a model says it should. And when that assumption breaks, everything else does too. Maybe it’s time we stop treating geological uncertainty as a technical inconvenience. It’s the core business risk, and facing it in advance is the only way we’ll stop falling short.