Prefeasibility hazard adjusted NPV

A mining company asked us to perform a Prefeasibility hazard adjusted NPV evaluation. Our action first focused on bringing clarity in their risk register which presented numerous classic mistakes. Among these the usual confusion in terminology, confusing risks and hazards, uncertainties vs risks, etc. Once the risk register was corrected it was possible to perform the requested hazard adjusted NPV and to draw valuable conclusions. Among these, we highlighted potential fatal flaws of the project which warranted in depth analyses…

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Tailings risks correlations

Tailings risk correlations or lack thereof refers to a phenomenon we oftentimes encounter in ORE ERMs deployments in various industries. The risk bubble in the p-C graph The figure below shows a classic simplified result from a ERM. The quadrant is the probability (p), Consequence (C) quadrant with the addition of the risk tolerance band. The band has a width corresponding to the divergent opinion between optimistic and pessimistic key stakeholders on tolerance. A given hazard has uncertainties on both…

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A risky mission

We undertake a risky mission today. That is to reply to information requests we have received from various interested readers in a very concise manner. The risks of the mission mostly arise from: the wide breath of the requests: “please let us know where we could learn about Riskope tailings management activities and methodologies” and the necessity to select among the vast available documentation. A classic preliminary reply We generally start our reply by inviting interested readers to visit Riskope’s…

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Zero to 300 in thirty

Zero to 300 in thirty is not the performance of a new sensational sport car. And we are talking about thirty years, not seconds! Actually, zero to 300 in thirty years is the cumulative experience Riskope and its founders have dealing with tailings dams risk assessments all over the world.  You should not understand it as an “average” evaluation either, as the evolution has been trending towards exponential. Let’s discover together what we are talking about. Zero to 300 in…

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FUV vs RIDM friends or foes at CIMBC22

FUV vs RIDM friends or foes at CIMBC22 sounds like a riddle, right? But it is not! Please, note FUV was actually never written as an acronym. Actually FUV stands for firmitas, utilitas, et venustas in Latin language.  Today we freely translate the terms into English as reliability, serviceability and beauty, straying a tad away from the original meaning. However, Henry Wotton, a seventeenth century translator, coined “firmness, commodity, and delight” as essential components of all successful architectural design. Wotton remained faithful…

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Pit failure at Codelco Ministro Hayes in Chile

We read about the recent pit failure at Codelco Ministro Hayes in Chile. We have also read that there will be no impact on the mining operations in this particular case but that is not significant in today’s proposed discussion. This failure is particularly interesting for Riskope as we recently performed a ORE2_Slopes quantitative risk assessment on a large open pit mine in Austral Africa. For a change the client mining company and the mine location are confidential. By the way,…

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Tolerable risk thresholds

Tolerable risk thresholds, aka risk tolerance are always project and owner-specific. They indicate the level of risk which has been deemed acceptable for a specific project or operation. Furthermore, tolerable risk thresholds and appetite for risk is quite different for various key stakeholders, for instance: Mine owner, Regulatory Bodies, Adjacent Communities, etc.   So how can one manage the sometimes divergent tolerable risk thresholds between stakeholders? Additionally, a topic that comes regularly in the mining world is diverging risk tolerance among…

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Why everything we know about Tailings Dams failure is wrong

If you think the title is provocative you are right. Why everything we know about Tailings Dams failure is wrong aims to discuss a different way of looking at TD failures. Biases occur if one uses statistical samples from a failure data base to evaluate TD likelihood of failure. That is because one considers the sub sample of failed dam as opposed to the overall inventory. Indeed if one ignores the base inventory one could draw misleading conclusions. Berkson’s paradox…

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