Choosing Resource Estimation Software: What Actually Matters for Your Project

I get asked “what software should I use?” at least once a month. Usually by a junior geologist who’s been told they need a $25,000 license to do resource estimation, or by a project manager who’s comparing software based on a feature list without understanding what the features actually do.

Here’s the truth: the software doesn’t estimate the resource. You do. The software is a tool — a calculator with a user interface. A competent geologist with a basic tool will produce a better estimate than an incompetent one with the most expensive software on the market.

That said, the tool matters for workflow efficiency, collaboration, and the types of analysis you can perform. This post covers what actually matters when choosing resource estimation software, without naming specific products or falling for marketing claims.

The four categories of resource estimation software

1. Full-suite mining packages

These are the heavyweights — everything from drillhole database management to block modeling to mine planning in one package. They’re what most major mining companies use for production-stage projects.

Strengths:

• Integrated workflow — data flows from database to model to mine plan without export/import
• Industry-standard output — investors and regulators recognize the file formats
• Full geostatistical toolkit — ordinary kriging, indicator kriging, conditional simulation, all built in
• Audit trail — every step is logged, which matters for JORC/KCMI compliance

Weaknesses:

• Cost — $15,000-$40,000 per license per year
• Learning curve — 3-6 months to become proficient, longer for advanced features
• Overkill for early-stage projects — if you have 30 drillholes, you don’t need a full mine planning suite

Best for: Production-stage mines, projects approaching feasibility, teams of 5+ geologists

2. Mid-range estimation tools

These focus on resource estimation without the full mine planning suite. They offer database management, geological modeling, and geostatistics but skip the mine design and scheduling modules.

Strengths:

• More affordable — $3,000-$10,000 per license
• Faster to learn — 1-2 months for proficiency
• Focused workflow — designed for geologists, not mining engineers
• Good geostatistics — most offer OK, IDW, and some form of kriging

Weaknesses:

• Limited integration with mine planning — you’ll need to export models to a separate tool
• Smaller user community — fewer tutorials, fewer third-party training resources
• Some lack advanced geostatistics — conditional simulation, multiple-point geostatistics

Best for: Advanced exploration projects, pre-feasibility studies, small teams

3. Scripting-based estimation (Python + GSLIB)

This is the approach I use most often for early-stage projects and for specialized analysis. You write Python scripts that call GSLIB (Geostatistical Software Library) executables for the actual estimation.

Strengths:

• Free — Python and GSLIB are open-source
• Full control — you see every parameter, every calculation, every assumption
• Reproducible — scripts can be version-controlled and re-run
• Flexibility — custom estimators, custom validation, custom reporting
• Transparency — perfect for JORC/KCMI audit trail

Weaknesses:

• Steep learning curve — you need to know Python AND geostatistics
• No GUI — everything is code, which intimidates some geologists
• Visualization is limited — you’ll need additional tools for 3D visualization
• No built-in database management — you handle data storage separately

Best for: Early-stage projects, research, custom analysis, geologists who can code

4. Cloud-based / web platforms

The newest category — browser-based tools that run estimation in the cloud. Still maturing but improving rapidly.

Strengths:

• No installation — works from any browser
• Collaboration — multiple geologists can work on the same model simultaneously
• Automatic updates — always on the latest version
• Lower upfront cost — subscription model, often $100-500/month

Weaknesses:

• Internet dependency — if your connection drops, you can’t work
• Data security — your drilling data is on someone else’s server
• Limited geostatistics — most cloud tools offer basic kriging but not advanced methods
• Immature ecosystem — fewer plugins, fewer integrations

Best for: Small teams, remote work, early-stage projects with simple geology

What actually matters (beyond the feature list)

Data management

Can the software import your data cleanly? Does it support the file formats your lab and surveyors use? Can it handle multiple drillhole databases without confusion?

I’ve seen projects delayed by weeks because the software couldn’t import a specific downhole survey format. Test the import workflow with your actual data before buying.

Validation tools

Does the software flag:

• Overlapping intervals?
• Survey deviations?
• Assays outside expected ranges?
• Missing samples?
• Collar-survey-assay mismatches?

These validations should be built in, not require custom scripting. If you have to write code to check for overlapping intervals, the software is failing you.

Geostatistical transparency

When you run kriging, can you see:

• The variogram model used?
• The search ellipse parameters?
• The number of samples used for each block?
• The kriging variance?
• The kriging efficiency or slope of regression?

If the software gives you a block model but can’t show you the variogram it used, you can’t audit the estimate. This is a JORC/KCMI compliance issue, not just a convenience issue.

Reporting

Can the software generate:

• Swath plots?
• Grade-tonnage curves?
• Validation reports?
• Cross-sections with modeled blocks overlaid on drillholes?
• Plan views with grade shells?

If you have to export to a third-party tool for basic visualization, your workflow is broken.

The decision framework

How many drillholes do you have?

• <50: Python + GSLIB, or a cloud tool. You don’t need a $25K license.
• 50-500: Mid-range tool. The database management justifies the cost.
• 500+: Full-suite. The integration and audit trail are necessary.

What’s your project stage?

• Exploration: Scripting or cloud. Flexibility matters more than integration.
• Pre-feasibility: Mid-range. You need proper geostatistics and documentation.
• Feasibility/Production: Full-suite. The audit trail and mine planning integration are non-negotiable.

Can your team use it? A $25,000 license that nobody knows how to use is worse than a free Python script that one person understands. Factor in training cost and time. If your team has never used a full-suite package, budget 3-6 months of training before they’re productive.

The Indonesian reality

Most Indonesian exploration companies I work with have 3-5 geologists and budgets that make $25K licenses unrealistic. For these teams, I recommend:

1. Python + GSLIB for estimation — free, transparent, and forces good documentation
2. A mid-range tool for visualization — if budget allows, for cross-sections and 3D views
3. Spreadsheet for database management — yes, really. A well-structured Excel workbook with validation rules is better than a poorly configured database in expensive software

This isn’t ideal. But it’s honest. And an honest estimate with free tools beats a polished estimate from expensive software that nobody in the team understands.

The bottom line

Software is a tool. The estimate is yours. Choose the tool that fits your project, your team, and your budget — not the one with the best marketing. And regardless of what you choose, document your workflow, validate your results, and be prepared to defend every parameter in front of a Competent Person review.

The best software investment you can make isn’t a license. It’s training. A geologist who understands geostatistics will produce a better estimate with a spreadsheet than one who doesn’t with the most expensive package on the market.