STOP BLAMING THE CUT-OFF GRADE In many technical reviews, discussions often focus on cut-off grades, pit optimization, reserve changes, or project economics. However, these outcomes are merely the final products of a much longer chain of geological assumptions. A cut-off grade does not create value. It only filters value from the model that already exists. Before reserve statements are published, before pit shells are generated, and before economic scenarios are evaluated, fundamental decisions have already been made regarding: • Geological domaining • Spatial continuity assumptions • Variogram interpretation- • Search strategy and estimation parameters • Grade distribution modeling Two competent professionals can start with the same drillhole dataset, use the same software, apply the same cut-off grade, and still arrive at different reserve outcomes. Why? Because geological interpretation drives the model long before economic optimization begins. The greatest risk in resource estimation is often not the estimation algorithm itself, but the assumptions used to represent geological reality. As resource professionals, our responsibility is not simply to generate models—it is to ensure that the geological understanding behind those models is robust, transparent, and defensible. Data is what we have. Geology is how we understand it. The model is how we quantify it. Value is what we create with it. #Mining #Geology #ResourceEstimation #Geostatistics #Variogram #CutOffGrade #MineralResources #OreReserve #MiningEngineering #ResourceGeology #GeologicalModeling #Kriging #MinePlanning #MiningValueChain #Zvenia

In many laterite nickel projects, especially during early exploration stages, we often face one uncomfortable reality: Our drilling density is still too sparse, but we already want to build a resource model. This is where the choice of interpolation method becomes extremely important. Recently, I compared RBF Interpolant (Leapfrog) and IDW on a nickel laterite dataset with relatively wide drill spacing. The results were very interesting and strongly relate to current discussions about whether we sometimes “over-force” geostatistics on immature data. What Happened in the Comparison? Using the same dataset: RBF Interpolant produced: smoother continuity, more geological-looking grade trends,more natural transitions between grade zones and minimal bull-eye effect. Meanwhile: IDW produced: stronger local influence around drillholes, more spotty distributions, clearer bull-eye patterns, higher local variability. This difference becomes very obvious visually. Why Does This Matter? Because in sparse drilling conditions: continuity is still uncertain, variograms are often unstable, anisotropy is not fully understood, and Ordinary Kriging may create a false sense of confidence. This is exactly why RBF becomes attractive. Instead of forcing a variogram model from limited data, RBF uses implicit mathematical continuity to generate smoother and more geologically coherent surfaces. The Interesting Part: Histograms The comparison also showed: RBF : lower variance, smoother distribution, more stable grade population. IDW : slightly higher variance, more local fluctuation, sharper spikes in distribution. This reflects the nature of each method: RBF prioritizes continuity, IDW prioritizes local distance weighting. Neither is automatically “better” they simply answer different geological questions. Should We Replace Kriging with RBF? Not necessarily. For formal resource reporting such as JORC and KCMI. Ordinary Kriging is still widely preferred because it provides: estimation variance, kriging efficiency, slope of Regression, defensible geostatistical validation. However using Ordinary Kriging on data that is still too sparse can sometimes be more dangerous than using a simpler method honestly aligned with the data quality. In Nickel Laterite, RBF can be very useful for: 1. Early-stage exploration 2. Wide drill spacing 3. Geological domaining 4. Implicit saprolite/limonite boundaries 5. Preliminary grade shells 6. Fast model updates The “best” interpolation method is not the most sophisticated one. It is the method that best matches: the drilling density, geological understanding, and confidence level of the dataset. CMIIW..

Reserve calculation does not begin in mining software—it begins with understanding the geology. In mineral exploration, geophysical surveys and geological interpretation are not separate disciplines; they are complementary tools that build the foundation of reliable resource and reserve estimation. Geophysics helps us identify structures, alteration zones, density contrasts, conductivity anomalies, and mineralization controls beneath the surface. Geology transforms these signals into meaningful geological models that explain how and why a deposit exists. When these disciplines are integrated effectively, exploration programs become more efficient by: • Improving drill targeting accuracy • Reducing exploration risk and uncertainty • Lowering unnecessary drilling costs • Accelerating discovery timelines • Producing more reliable resource and reserve models Whether exploring for Gold (Au), Copper (Cu), Silver (Ag), or Rare Earth Elements (REE), successful reserve calculations depend on a robust understanding of the geological framework controlling mineralization. The most valuable asset in exploration is not the drill rig, software, or geophysical equipment. It is the ability to understand the intrinsic geological value of the ground before making critical decisions. Because high-quality reserves are built upon high-quality geological understanding. Geophysics gives us the signals. Geology gives us the meaning. Together, they create the confidence behind every reserve estimate. The better we understand the Earth, the more value we create. #Mining #MineralExploration #Geology #Geophysics #ReserveEstimation #ResourceModeling #MiningEngineering #EconomicGeology #GoldMining #CopperMining #SilverMining #RareEarthElements #MiningConsulting #ExplorationGeology #ZveniaMining

GEOLOGY CONTROLS VARIOGRAMS, NOT SOFTWARE Variograms are often treated as a software output. But in reality, they are a mathematical expression of geological history. Every nugget, sill, range, and search radius is not created by the software — they already exist in the deposit. The software only helps us reveal them. Nugget reflects what happens at very short distances:micro-variability, local heterogeneity, sampling support, and sometimes measurement uncertainty. Sill represents the total variability captured within the geological domain. Range defines the limit of continuity — the distance where samples stop behaving as part of the same geological process. And the search radius is not an arbitrary setting. Whether using spherical or ellipsoidal search, the objective remains the same: Find the spatial continuity that geology created. Structures, weathering, sedimentation, tectonics, mineralization, remobilization, and alteration have been shaping these patterns for thousands of years. What we model today is the result of geological events recorded through time. Our responsibility is not to force continuity. Our responsibility is to understand it. Because at the end: Software calculates. Data records.Geology decides. Variograms do not invent continuity. They reveal the continuity that nature has already written. #Geostatistics #Variography #ReserveEstimation #ResourceModeling #Mining #Geology #OreReserve #BlockModel #SpatialContinuity #OrdinaryKriging #MiningEngineering #Exploration #GeologicalModeling #NickelMining #MinePlanning #Zvenia

Ultimo articulo de la serie de Xavier Emery (Universidad de Chile) que explora los vinculos entre la incertidumbre geologica, la clasificacion de recursos/reservas minerales, la progresion por etapas de los proyectos mineros, la planificacion minera, el modelamiento financiero y las decisiones de perforacion. El articulo cubre: - El sistema de 'etapas y puertas' para el desarrollo de proyectos mineros: estudios de perfil, prefactibilidad (EPF) y factibilidad (EF) - Rangos de precision por etapa: +/-25-50% (perfil), +/-15-25% (EPF), +/-10-15% (EF) - Requisitos minimos de clasificacion de recursos por etapa del proyecto - La matriz de sustentabilidad, concepto forjado en Codelco-Chile - Politicas de perforacion: analisis de espaciamiento de sondajes (DHSA) - Optimizacion de sondajes de relleno: donde, cuando y cuanto perforar Parte 5 de la serie sobre clasificacion y reporte de recursos minerales.

In geophysics, horizon gridding is much more than just filling gaps between picked points. The choice of interpolation method can strongly impact structural interpretation, reservoir geometry, and volumetric estimations. Some of the most commonly used interpolation methods include: - Nearest Neighbor — fast but often too blocky - Inverse Distance Weighting (IDW) — simple and stable for dense datasets - Minimum Curvature — widely used for smooth geological surfaces - Kriging — geostatistical approach with uncertainty modeling - Radial Basis Functions (RBF) — excellent for smooth continuous horizons - Triangulation / Delaunay — preserves local structures and faults - Machine Learning methods — increasingly used for complex stratigraphic patterns There is no universal "best" interpolation method. The optimal choice depends on: data density, fault complexity, structural style, noise level, and geological objectives. A good grid should honor both the data and the geology.

ADVANCED ESTIMATION CANNOT FIX POOR DRILL DATA Resource and reserve estimation often receives most of the attention — variograms, kriging, block models, and advanced algorithms. But none of them can compensate for poor input data. Before building confidence in a model, confidence must first be built in the drill database. A reliable estimation starts with disciplined validation: ✔ Collar verification ✔ Survey validation ✔ Assay QAQC (CRM, Blank, Duplicate) ✔ Interval and database cleaning ✔ Outlier identification and management Outliers should not automatically be removed, Some represent errors. Others represent the geology itself. The challenge is knowing the difference. A capped model without geological understanding can destroy value. An uncapped model without control can create false confidence. The objective is not to create a smooth model. The objective is to represent reality as accurately as possible. Because at the end of the workflow: Good geology + Good method + Poor data = Poor reserve. Validate first. Estimate later. Trust your data, not only your software. #ReserveEstimation #ResourceModeling #DrillData #Mining #Geology #QAQC #Geostatistics #OreReserve #BlockModel #OutlierManagement #MineralResources #MiningEngineering #Exploration #GeologicalModeling #MinePlanning #NickelMining #Zvenia

The term "independent peer review" is applied across the resource industry to a wide range of activities, much as "bankable feasibility study" came to describe everything from a desktop screen to a definitive study. What is presented to the board as independent assurance is, on examination, often neither independent of the project sponsor nor delivered by peers in any defensible sense of the term. Three approaches dominate. 1) The internal senior review, in which a major selects two or three of its own engineers who were not assigned to the project and represents the exercise as independent. The reviewers report up the same chain as the sponsor, depend on the same executives for their next assignment, and have an interest in the findings being received as constructive. Only the largest internationals have a bench deep enough to source credibly independent individuals, and even they supplement with externals on material decisions. 2) The management consultant stage gate, structured around a generic framework and conducted by personnel who are intelligent and well presented but who have not held line responsibility for the design, construction or commissioning of a comparable asset. The output measures process compliance. Engineering judgement against the business case is what the board requires, and on that measure the peer test is not met. 3) Engineering verification by another engineering house. Technical competence is adequate, but the firms are direct competitors who exchange staff and bid against each other on subsequent work. The incentive to identify a fundamental flaw in a competitor's study is weak, and the scope is narrow technical assurance rather than business case validation. The methodology to address these gaps was developed during the 1990s with the majors. "Peer" is held to mean best in class in the relevant function, with a demonstrated track record and the personal confidence of the directors and executives, rather than merely senior or available. The business case is at the centre of every review, designed backward from the decision the board has to make on the commitment of shareholder funds. Findings are reported balanced, with positives alongside deltas. All matters of Fact are reconciled, with evidence on the table, before the report is signed, and matters of Opinion in dispute are published within the report, with the project team's position recorded.

In mining, a visually perfect block model does not always represent a successful operation. Many resource models fail when real mining conditions begin: - slope instability, - unexpected dilution, - water problems, - Poor ore control, -Unrealistic mining selectivity. A reserve model should not only satisfy reporting standards.It must also survive operational reality. This is why geological interpretation, geotechnical understanding, hydrogeology, mining recovery, and operational practicality must work together from the early stage of resource estimation. The best reserve is not always the biggest number. It is the reserve that can actually be mined safely, consistently, and profitably #Mining #Geology #Nickel #ResourceEstimation #ReserveEstimation #Geotechnical #OreControl #MiningEngineering #BlockModel #MinePlanning

In mining, reserve estimation is not only about creating a visually impressive block model. A model may look perfect inside the software, but mining reality is far more complex. -. If geotechnical conditions are ignored, slopes can fail. -. If hydrogeology is underestimated, water inflow can stop operations. -. If dilution and mining recovery are not considered properly, the actual ore delivered to the plant may never match the estimated reserve. This is why resource and reserve estimation should never stand alone. Geology, geotechnical engineering, hydrogeology, ore control, mining selectivity, and operational practicality must work together from the beginning. Because at the end of the day: The best reserve is not the biggest number on paper.It is the reserve that can actually be mined safely, consistently, and profitably. #Mining #Nickel #Geology #ResourceEstimation #ReserveEstimation #BlockModel #Geotechnical #Hydrogeology #OreControl #MinePlanning #MiningEngineering #OpenPitMining