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This exclusive webinar series covers important aspects of geology modeling, like integrated implicit and explicit modeling with Surpac, Block Modeling best practices, Kriging Neighborhood Analysis and Dynamic Anisotropy, dynamic blocking case studies, integration with Python, how AI and Machine Learning technologies are transforming the way we approach geology and deposit evaluation, and more.
Understand how the integrated implicit geology modeling in Surpac accelerates updates and empowers geologists to work smarter and faster, without sacrificing geological control or compromising the geological interpretation.
Glenn, Isaac, and Edem discuss common resource modeling pitfalls and how better collaboration, model handovers, and smart tools like AI and centralized platforms can improve accuracy, reduce risk, and align geology and engineering teams.
The latest Surpac updates introduce powerful tools like enhanced drillhole design, GeoTIFF integration, advanced block model reblocking, and a new Solid Intersections Library. These features improve workflows, data integration, and resource classification for geology professionals.
Discover how a Surpac expert optimizes ordinary kriging estimations using Kriging Neighborhood Analysis, Dynamic Anisotropy, and custom macros. Learn practical workflows and see a real-world case study on creating accurate, geologically realistic resource models.
Surpac 2025 Refresh 2 introduces the Scl Python Executor command, enabling seamless integration of Python scripts within TCL macros. Leverage advanced libraries like Shapely and Plotly for precise geometry, enhanced charting, and efficient data transformations.
Explore Surpac's advanced block modeling tools, including dynamic sub-blocking, super-blocking, and octree-based efficiency. Learn how to optimize storage, enhance precision, and manage large models with new features like user-defined reblocking and multi-model support.
Join our GEOVIA Specialist, Jose GONZALEZ, to explore how AI and ML are revolutionizing geology and resource evaluation. Learn to optimize timelines, costs, and data analysis with tools like Pipeline Pilot, while gaining insights into supervised, unsupervised, and deep learning techniques.