{"version":"1.0","provider_name":"MRMR 2026","provider_url":"https:\/\/mrmr2026.cim.org\/fr","author_name":"Viorel Anghel","author_url":"https:\/\/mrmr2026.cim.org\/fr\/author\/vanghelcim-org\/","title":"Automated and Collaborative Resource Modeling Workflows - MRMR 2026","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"YuG8PI3A5F\"><a href=\"https:\/\/mrmr2026.cim.org\/fr\/automated-and-collaborative-resource-modeling-workflows\/\">Automated and Collaborative Resource Modeling Workflows<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/mrmr2026.cim.org\/fr\/automated-and-collaborative-resource-modeling-workflows\/embed\/#?secret=YuG8PI3A5F\" width=\"600\" height=\"338\" title=\"&laquo; Automated and Collaborative Resource Modeling Workflows &raquo; &#8212; MRMR 2026\" data-secret=\"YuG8PI3A5F\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/mrmr2026.cim.org\/wp-includes\/js\/wp-embed.min.js\n<\/script>","description":"Automated and Collaborative Resource Modeling Workflows &#8211; Modernizing Traditional to Probabilistic Techniques Short Course Level: AdvancedFacilitators: Dhaniel Carvalho, Resource Modeling Solutions\u202fAna Chiquini, Principal Geologist, GeologicAI\u00a0 \u00a0 Short Course Objectives Understand the fundamentals of automated resource modeling workflows using RMSP and AMP. Apply traditional deterministic estimation methods and probabilistic simulation approaches. Use Python-based RMSP scripts to build, run, and automate grade estimation and simulation workflows. Interpret workflow steps, validation checks, and key modeling decisions to improve transparency and auditability. Visualize models, manage automated updates, share results, and apply version control within the collaborative AMP environment. Recognize advanced concepts such as domain uncertainty characterization, hierarchical truncated plurigaussian (HTPG) simulation, and vein simulation. Develop the ability to use automation to improve efficiency, consistency, and decision-making in resource modeling. Target Audience This course is targeted at geologists and mining engineers involved in resource estimation and modeling, including Qualified Persons (QPs) and technical specialists. It is suitable for practitioners seeking exposure to modern, automated workflows, Python-based tools, collaborative modeling environments, and contemporary estimation and simulation approaches. Abstract This one-day workshop offers a practical, hands-on approach to understanding automated resource modeling workflows with the Resource Modeling Solutions Platform (RMSP) and the Automated Modeling Platform (AMP), from traditional deterministic methods (e.g. IDW, Kriging) to advanced probabilistic approaches (e.g. continuous and categorical simulation). The workflows are developed in a centralized and version-controlled environment that promotes cross-disciplinary collaboration. Rather than extensively exploring the theoretical foundations of the methods used, participants will be provided with pre-built workflows that demonstrate their practical usage and key considerations. Each step of the grade estimation and simulation workflows will be broken down and explained, so attendees can understand what is being done and why.\u202f Time will be dedicated towards the end of the course for introducing advanced topics, including methods for characterizing domain uncertainty of varying deposit styles, such as hierarchical truncated plurigaussian (HTPG) simulation and vein simulation. Through ready-to-use scripts and examples, participants will follow along, using RMSP and Python-based tools to automate deterministic and probabilistic models. Automation is key not only to improve efficiency and consistency but also to allow geologists to dedicate more time to critical thinking and geological interpretation &#8211; the core of effective resource modeling. By embedding rigorous checks and validations throughout the workflow, automation ensures that models are reliable, transparent, and auditable.\u202f By the end of the course, participants will have a solid foundation of how to apply automated workflows to improve decision-making in modern resource modeling.\u202f Through the use of AMP, participants will also gain familiarity in working within a collaborative environment, including sharing results and applying version control for managing changes to data, parameters, and workflows RMSP is a Python library for resource modeling that improves transparency, automation, and performance using a fast C++ engine. Its Python interface makes models easy to audit, integrate with data systems, and automatically update as new data becomes available, helping mining companies make faster and more informed decisions. The Automatic Modeling Platform (AMP) is a cloud-hosted environment for running and visualizing RMSP workflows. It manages computing, data storage, user access permissions, and version control, enabling teams across an organization to collaborate on workflow development, review, and automated updating. AMP therefore promotes engagement of stakeholders in the modeling process, while automated and rapid model updates allow for better decision-making that is informed by the latest data. AMP can be deployed within an organization\u2019s cloud network or hosted externally. About the instructors Dhaniel Carvalho, Resource Modeling Solutions\u202f Dhaniel conducts geostatistical and resource modeling projects at Resource Modeling Solutions (RMS) with a focus on the APAC region. Dhaniel holds a MSc in geostatistics and has gained comprehensive expertise in resource modeling for multiple commodities and deposit types around the world during 15 years in industry. Dhaniel previously held the role of Principal Resource Geologist at Glencore and was responsible for leading a team of geologists, providing technical guidance and resource modeling training worldwide for operations, sign-off of Resources for Resources &amp; Reserves reporting, participating in feasibility studies and due diligences. Dhaniel is the chair of the organizing committee for the AusIMM Mineral Resource Estimation Conference. Ana Chiquini, Principal Geologist, GeologicAI\u00a0 Ana manages geostatistical and resource modeling projects at Resource Modeling Solutions, with a focus on the APAC region. Ana has comprehensive industry expertise in a range of commodities and deposit types, in multiple mining jurisdictions.\u00a0 Ana previously held the role of Principal Resource Estimation at Rio Tinto Copper, where she was responsible for producing and overviewing resource modeling and due diligence work. Ana holds a Master&#8217;s Degree in geostatistics and brings 15 years of industry experience in Mineral Resource evaluation, disclosure, and management. Ana has delivered a variety of training courses on geology modeling and Mineral Resource estimation in English, Portuguese and Spanish.","thumbnail_url":"https:\/\/mrmr2026.cim.org\/wp-content\/uploads\/2026\/05\/Dhaniel-Carvalho.jpg","thumbnail_width":800,"thumbnail_height":800}