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

DRILL SPACING DETERMINES RESERVE ESTIMATION In mineral exploration and mining, drill spacing plays a critical role in determining the accuracy and reliability of reserve estimation. The distance between drill holes directly affects data density, geological confidence, and orebody interpretation quality. The section shown above represents an area with adequate drill density, where geological interpretation can be performed with higher confidence. With sufficient data spacing, ore boundaries, thickness variations, and mineralization continuity become clearer and more representative of the actual deposit conditions. Proper drill spacing provides several major advantages: • Higher geological confidence • Better ore continuity interpretation • More accurate tonnage and grade estimation • Reduced geological uncertainty • Stronger mine planning and production forecasting A dense and well-structured drilling pattern also improves the quality of geological domain modeling, allowing reserve calculations to become more reliable and economically realistic. On the other hand, poor drill spacing can lead to: Overestimation or underestimation of reserves -. Grade dilution -. Incorrect ore boundaries -. Higher operational risk -. Misleading economic valuation This is why reserve estimation must also consider: -. Safety Factor -. Loose Material Factor -. Mining Recovery -. Dilution Control These modifying factors are essential to minimize operational losses, geological uncertainty, and discrepancies between model tonnage and actual production. Ultimately, accurate reserve estimation is not only a technical achievement — it is a foundation for sustainable mining economics, reliable production planning, and stronger investor confidence. Closing Statement “Good data density creates strong geological confidence, Strong geological confidence creates reliable reserves, Reliable reserves create sustainable mining economics.” #Mining #Geology #CoalMining #OreMining #ReserveEstimation #ResourceModeling #MinePlanning #Geostatistics #NickelMining #CoalExploration #MiningEngineer #GeologicalModeling #JORC #KCMI #MiningIndustry

A well-designed block model is one of the most important foundations in nickel resource estimation. In lateritic nickel deposits, mineralization can change rapidly both laterally and vertically. Because of this, block size and model detail play a critical role in how accurately the resource can be identified and quantified. If the block model is too coarse, important geological variability and narrow high-grade zones may be smoothed or even missed entirely. On the other hand, a properly designed block model with appropriate block dimensions allows us to better capture: 1. grade continuity, 2. geological boundaries, 3. mineralization trends, 4. and the true geometry of the orebody. The slicing section shown here represents how actual field data is translated into a detailed block model using real nickel data. Each block carries geological and geochemical information that contributes to the final resource estimation. At the end of the day, resource modeling is not simply about filling blocks inside software — it is about understanding how detailed the model should be so the resources can be identified as accurately and maximally as possible. “A good block model does not only visualize the deposit — it reveals its true potential.” #NickelMining #Geology #OreReserve #MiningEngineering #ResourceModeling #BlockModel #TechnicalInsight

A large nickel resource does not always become a large mineable reserve. In mining, a mineral resource only represents the geological potential in the ground. To become an ore reserve, the material must pass through multiple technical, economic, geotechnical, and operational considerations. Factors such as: 1. pit slope constraints, 2. groundwater conditions, 3. mining recovery, 4. dilution, 5. haul road access, 6. operational practicality, 7. and economic cut-off grade can significantly reduce the amount of recoverable ore. This is why two deposits with similar resources may produce very different reserve outcomes. In reality, reserve estimation is not simply about maximizing tonnage — it is about identifying what can realistically, safely, and profitably be mined. All field data may be the same ingredients, but the final result depends on how the “chef” interprets and processes the data with the right understanding, experience, and mining judgment. At the end of the day: “The best reserve is not the biggest one — but the most realistic and recoverable one.” #NickelMining #OreReserve #MiningEngineering #GeotechnicalEngineering #MinePlanning #TechnicalInsight