Jakarta, 20 - 21 April 2026 Visit our community Contact Us PT Empat Pilar Adidaya Dynamic Anisotropy for Nickel Resource Estimate Training

PT Empat Pilar Adidaya – Dynamic Anisotropy for Nickel Resource Estimate Training

Surpac Resource Estimate Training

Beyond Static Models: Dynamic Anisotropy for the Future of Nickel Mining

Industry Process Consultant: Join Damanik

Dynamic Anisotropy for Nickel Resource Estimate using GEOVIA Surpac isn’t just about tweaking models it’s about unlocking the real story hidden in the ore. When anisotropy is ignored, numbers can deceive. But when it’s embraced, resource estimates gain accuracy, credibility, and true economic meaning.

On 20–21 April 2026, participants from PT Empat Pilar Adidaya gathered at the ACALA Training Center in Jakarta to step beyond static assumptions and into dynamic thinking. They experienced firsthand how Surpac brings anisotropy to life—turning theory into practice, and practice into confidence.

The training was especially powerful because participants used their own exploration data. They compared static anisotropy models fixed orientations applied across the deposit with dynamic anisotropy models that adapt to local geological trends.

The side-by-side results made the difference clear, static models often oversimplified ore continuity, while dynamic anisotropy produced estimates that were more realistic, defensible, and economically meaningful.

This training emphasized that dynamic anisotropy is not just a technical adjustment it is a strategic foundation for achieving accuracy, sustainability, and economic value in nickel resource estimation. By embedding anisotropy into geological modeling, participants learned how to transform static assumptions into adaptive models that reflect real mineralization trends.

Training Highlights

  •  Fundamentals of anisotropy in nickel deposits
  • Building and interpreting directional variograms
  • Applying dynamic anisotropy in Surpac block modeling
  • Comparing static vs. dynamic estimation approaches
  • Validation through cross-validation and sensitivity testing
  • Aligning outputs with international reporting standards (SNI, JORC, NI 43-101)

The program was attended by participants from PT Empat Pilar Adidaya, who gained hands-on experience in applying dynamic anisotropy to strengthen the robustness of their nickel resource evaluations. Their active involvement reflected a strong commitment to advancing technical excellence and ensuring long-term project value.

The atmosphere was collaborative and energetic every drillhole, variogram, and adjustment mattered. This training reaffirmed that in nickel mining, precision is not optional it is survival.

Throughout the training, there were many demonstrations and discussions that addressed the challenges participants had been facing in their work.

By openly sharing their experiences and testing solutions with real exploration data, they were able to see problems from new perspectives and work through them together.

In the end, the training didn’t just provide knowledge, it gave participants practical answers and clear pathways forward to overcome the issues they had struggled with before.

Technical & Practical Skills with Surpac

  • Participants master the concept of Dynamic Anisotropy for Nickel Resource Estimate and learn to apply it directly in Surpac block modeling.
  • Surpac provides a powerful platform for variogram analysis, anisotropy configuration, and model validation, enabling participants to transform theory into practical workflows that improve accuracy and reliability.

Strategic & Professional Impact

  • Improved confidence in nickel resource estimation, strengthening project credibility and long‑term economic value.
  • By leveraging Surpac’s integrated tools, participants enhance their professional expertise and contribute to a culture of precision, sustainability, and excellence in mining projects.

This program reflects ACALA’s ongoing commitment to advancing industry knowledge and empowering professionals to deliver excellence in resource estimation.

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