CorePlan vs Krux: What's the difference?

Explore powerful features that outperform Krux.

The challenge

Great data starts in the field with sample acquisition, techniques and field data (as under Section 1 of the JORC code).

But it’s frighteningly common to see explorers spend millions on drilling…. only to have their drilling data recorded on paper or spreadsheets.

‍

How it affects you under the code

Say you’re analysing assay data from a drilling campaign that finished several months prior. You want to use this data to plan the next phase of drilling. But when you want to verify the assay results against your drilling data, you realise that the hole IDs weren’t updated and the data was assigned to the wrong drill holes. Where should you begin to untangle this mess - and the waterfall effect it created across the rest of your data?

Wouldn’t it be preferable to avoid this by doing things correctly the first time around?

Not to mention, it also poses problems down the track if you get to the stage where you’re ready for resource estimation and reporting.

Under Section 3 of the JORC code, explorers need to be able to demonstrate that: “measures have been taken to ensure that the data has not been corrupted, by, for example, transcription or keying errors between initial collection…and that data validation procedures were used.”

....Pretty difficult to prove using pen and paper methods, no?

‍

The strategy

A strategy to help your team and contractors capture data correctly at the source is implementing data capture controls.

Digital tools can help you to build control measures and implement safeguards like validation rules, approval processes and chain of custody logs directly into your data capture process to tackle this problem at the source.

Here’s how:

Validation rules are a way to create a foundation for great data at the point of entry. An example of a validation rule in digital field data capture could be the application of drilling interval parameters so that intervals cannot overlap and must run in sequential order starting with the value of the last recorded interval, so no interval is missed. Similarly, if critical drill hole information like dip and azi, easting and northing, hole depth etc are missing, they can be flagged so that the issues can be resolved on the spot, not retrospectively. This way you’re not finding critical holes in the data when it’s time to compile your reports and presentations.

Approval processes are an additional step in the validation process, but well worth it when there are thousands or even tens of thousands of dollars worth of drilling being done each day. An example of an approval process in action would be a geologist digitally signing off on a daily drilling report before it is entered into the data management system or database. This way, there is an opportunity to resolve mistakes and prevent them from entering the database at the point of entry. Not to mention, an opportunity to prevent errors from showing up in the bill at the end of the month, affecting your overall drilling spend and time spent reconciling invoices.

Chain of custody logs create a comprehensive and auditable data history. This way, you can see who has touched it along its journey and what happened at each stage for a complete trail of evidence. These can be generated and stored in the system for ease of reference later on.

Tracking processes built into modern software can help make sure that you dot your i’s and cross your t’s when it comes to critical workflows like sample dispatch and assay data receipt. Once the samples leave the core yard, they’re out of your control, but by tracking them, you can be sure that you receive a complete set of assay results, that every drill hole has been accounted for, and that none have been forgotten or fallen off the back of a truck, never to be seen again.

‍

The challenge

Say you’re running a drill program with multiple drilling contractors.

Or, you're running multiple drilling campaigns in various locations around the country or even the world.

How do you efficiently make sure you’re meeting your drilling technique and drill hole information data reporting requirements under Sections 1 and 2 of the JORC code on every shift, with every rig and every crew - if each of your projects and contractors captures, labels and supplies data in different ways?

‍

How it affects you under the code

If you miss out on critical data whilst you're drilling, it's pretty hard to go back and fix up the data retrospectively (not to mention - it's bad practice!).

It could lead to issues understanding exactly what you did in the field, which can be problematic if you need to revisit the data, plan a twin hole etc etc.

‍

The strategy

Sometimes, you don’t have control over how you receive your daily drilling data.

Luckily, automation found in drill program management software can process any plod from any drilling contractor in any format and reformat it to suit your requirements.

During this process, missing, duplicate or overlapping data that's often hidden in spreadsheets is flagged, helping you prevent errors from entering your database. It also means less time that your geos have to spend manually transcribing data between different spreadsheets and systems.

Here are 6 more strategies for managing drilling data across multiple contractors.

‍

The challenge

Geologists must work with massive amounts of data to make a discovery.

But traditional ways of running an exploration project force that data into silos, whether that’s different software, different formats etc.

And whilst you might have all the data somewhere, you must consult multiple locations to find information or run reports. But wait - it’s all in different formats. So, you then need to spend time downloading it and reformatting it into a new document so that the individual parts will play nicely together. Or, some of it is stored in proprietary formats of PDFs, so you have to manually copy it onto your spreadsheet. Meanwhile, hours have passed, and all you wanted to do was create a list of drill hole logs displaying mineralisation.

‍

How it affects you under the code

The more you touch the data, the more chances of human error entering the dataset or the database.

Recall, under Section 3:

Explorers need to be able to demonstrate that: “measures have been taken to ensure that the data has not been corrupted, by, for example, transcription or keying errors between initial collection…and that data validation procedures were used.”

‍

The strategy

Don’t let yourself get stuck in this time-sucking trap. Make your software do the heavy lifting for you!

Look for software that supports interoperability (the easy transfer of data between software platforms using open systems and formats), saving you time and effort in wrangling data and helping you get more bang for your software buck.

‍

Interoperability, open systems and the OMF

In mining, transferring data between different software packages is a widespread issue. The Global Mining Standards and Guidelines Group (GMSG) has developed an early-stage open standard format - the Open Mining Format (OMF) - to help.

‍Did you know that this problem is obsolete in other industries because open-format tools are the accepted standard?

Proprietary formats are a big problem in mining that hinders interoperability by making it difficult to move data between platforms. They are also not future-proof.

What happens if you want to move to a different type of software or the software becomes obsolete? Moving this data to another platform is a huge job, both in moving the sheer volume of data collected over the years and the high chance of errors during the translation process (your DBA is quaking right now).

Exploration professionals need to anticipate future trends and challenges in this space and invest in versatile tools and processes for a digitised future. One of which is ditching proprietary formats in favour of open systems.

Here is a list of other things that exploration managers are doing right now to prepare their teams for success in mining’s changing landscape, and a guide on what to look for (such as open systems) when evaluating exploration software to avoid buyer’s remorse.

‍

Exploration teams are ditching PDFs.

We’re calling it: the age of the PDF in exploration drilling data exchange is over.

A growing number of exploration teams are embracing the power of data across the entire exploration process, including the drilling phase. It makes a lot of sense - drilling is the most expensive part of exploration, so they want to extract as much information from the process to make the most informed decisions possible.

And so they’re saying sayonara to PDFs and asking their drilling contractors to supply them with access to the raw data to conduct deeper analyses and run data matches with their drill hole metadata.

They’re also focusing on quality control and data validity.

With a PDF, there’s no audit trail and no ability to verify the chain of custody of the summary data that made its way onto the PDF. This makes it awfully difficult to come back and make changes, or to review the drilling data down the track once the details of that shift are gone from recent memory.

CSVs are a far more enduring file type that can store masses of raw data. Plus, they’re compatible with most mining software and can be imported rather than transcribed, saving your team’s valuable time and energy.

Here’s some more reasons why you should consider choosing a drilling contractor with digital capabilities for your next drill program.

‍

The challenge

It takes a looooot of systems to run an exploration project, and data needs to go here, there and everywhere to get specific jobs done.

Take just this small part of the workflow: the daily drilling report. The process looks something like this:

It goes through the drilling contractor’s procedures before it gets to you
It gets signed off on by the senior geo (or sent back to the driller if there are errors)
A geo copies it manually into the database (let’s hope there’s no typos)
Your geos use it to manually compile weekly, and monthly drilling activity reports
Someone realises there is an error and has to go back into the database to make changes and update the relevant reports
The exploration manager uses it to reconcile drilling invoices (and send it back to the drillers again if more errors emerge)
Your DBA uses it to compile drilling performance reports

and so on.

‍

How it affects you under the code

Undoubtedly, the data needs to go through this process. But it’s time consuming and risk-prone due to all the manual handling. Is there an easier way?

Yes.

‍

The strategy

Data automation, or in the above instance, plod automation, is your friend. It can immediately push the data through all of these tasks for you, removing the chance of human error at each of these instances, and giving you instant access to your data across the areas where you need it.

It’s a much more efficient way to work, so you can spend more time interpreting the data than wrangling it. It also means you can be more confident in your results under the JORC code requirements because there is a reduced risk of human error and increased database integrity.

Think streamlining your exploration data management processes sounds complex and is only achievable at the top end of town with big budgets?

Think again!

In fact, many Junior and small mining companies are making the switch to digital in order to optimise every dollar of their drilling budgets.

‍

‍‍The suggested four strategies are great in theory, but how do you implement them and succeed?

You need a digital strategy.

A digital strategy outlines how your organisation intends to leverage digital tools and technologies to remain competitive and adapt to a changing industry. This may involve adopting new technologies, refining existing solutions, or integrating tools into current workflows and processes.

Having a written strategy enables your team to prioritise the bigger picture by considering all aspects of your operations and avoiding the distractions of daily challenges. It offers a framework for decision-making, ensuring that each decision aligns with your long-term objectives and your requirements under the JORC code.

By doing things right in the first instance, you’ll have more confidence in your data and interpretation. And, you won’t be left with regrets once it’s time to put that data into practice for inferring a mineral resource or communicating with stakeholders and/or investors.

‍

Tl;dr?

Great data management strategies have always been important when it comes to discovery and compliance under the JORC code. But as we move full speed toward mining 4.0 and beyond and using AI and machine learning become commonplace, the strategies discussed in this article will only become more critical. Implementing data capture controls, standardising data collection protocols and ensuring data format versatility will help future-proof your exploration operations and get the most out of your digital solutions.

Read more about how exploration managers are preparing for mining’s digital future and see how future-focused geology teams like Chalice Mining are streamlining data management in mineral exploration.

Download the checklist here

5 strategies geologists can use to ace data capture and management from exploration to JORC resource

Download the checklist here

Related Articles