Designing resource drilling as an investment decision and not a cost

June 8, 2021

by Andrew Dasys, CEO at

If you could, would you take the opportunity to de-risk a mineral property faster:

  • without changing the qualified person’s sampling requirements,
  • without affecting existing drilling accuracy,
  • without adding new constraints to the production department,
  • without needing any new capital investment, and
  • while decreasing in-field risks at the rigs.

Not only does it sound like a no-brainer it is also an objective that mining has to be able to reach. Bringing mineral resources into production quicker is critical to improving how the investment world sees the mineral industry. In 2019, a study by MineEx Consulting summarized that between 2005 to 2017 the cost of finding and bringing a Tier-1 property into production increased 3.8 times, while the meters drilled increased 2.8 times. Even more interesting is that the value of metal found between 2008 – 2018 is less than the cost required to find it giving the industry a ‘bang per buck’ of 0.55. is trying to help solve part of this problem by focusing on increasing the efficiency of drilling and de-risking a late-stage mineral property. What we have found across a range of projects is that Artificial Intelligence (AI) software and changing practices can make a bigger improvement than faster drills.

Since being selected as a semi-finalist in the Integra/Goldcorp’s Disrupt mining challenge, Objectivity’s resource optimization system (DRX), which stands for ‘Drilling, Reporting, and Targeting, where X marks the spot’, has been used globally to improve drilling efficiency on a wide range of resource drilling projects. DRX is an AI tool that addresses industry needs and maximizes the use of limited capital and human resources to improve project execution.

When compared to existing drill layouts, DRX’s AI algorithms increased resource conversion efficiency by more than 20% in 95% of the cases. These projects included underground drilling, surface drilling, combinations of the two, with and without actively deviated drilling. Improved efficiencies were obtained regardless of the drill plan and deposit type.

The efficiency improvement, calculated as the number of meters required to upgrade a cubic meter of resource from inferred to indicated to measured, can either:

  • decrease drilling time,
  • reassign budgeted meters to discovery or step-out drilling, and/or,
  • increase the tonnes/Oz of metal being de-risked for a given amount of drilling.

Having the capability of quickly generating complete drill programs meeting all site constraints, provides the project teams with improved confidence in their drilling designs and in the program’s expected deliverables. This significantly reduces the risk of delineating or upgrading any project.

You already own ‘clean’ data

DRX graphUnlike many machine-learning-based exploration targeting systems, DRX does not rely on finding multi-dimensional relationships within historically collected geoscience data. Instead, DRX focuses on maximizing the value of the drilling investment based on information available in most technical reports. This means that all projects that have an initial resource have ‘clean’ data that can be immediately used to improve the next phase of resource development – data quality and quantity are far less of an issue.

The technical report also provides a clear description of the QP/CP-required estimation and classification requirements. Combined with the site’s geometry and volumetric information, the objectives to optimize the detailed drilling plans moving from inferred through measured resources also exist.

Adapting to changes

DRX provides project teams with options and the confidence that they are drilling the best possible plans given the information that they currently have. Varying the objectives allows the teams to explore the value/cost of maximizing sampling for specific geoscience information: e.g., metallurgy, structure confirmation, continuity etc.

Unlike most drill hole planning tools, DRX does not require drill holes to be individually planned and drawn. This frees up geology staff time to focus on more complex tasks, such as interpretation.

Unlike many resource optimization methods, DRX does not change the search parameters to decrease drilling costs. Instead, DRX uses a unique targeting model that combines both quantified data and qualified interpretation. In conjunction with field constraints, DRX can produce specific drill plans to meet the immediate planning needs and update in near-real-time as new information is produced by the drills (location) and by project geologists (assay, interpretation).

It’s about integration

Planning produces efficiency. Production generates value. DRX is designed for IOT connectivity, allowing data channels, when available, to feed directly into the targeting algorithm. Times are changing, drills are producing more data, assaying time is decreasing and becoming more accurate, and this increases the amount of data that a geologist has to process. By allowing geologists to focus on strategy, DRX’s IOT-ready design deals with the detailed data streams to optimize drilling campaigns.

It’s about money

DRX uses AI and optimization algorithms empowering project teams to make informed decisions on how drilling budgets can be maximized to increase resource conversion while also improving orebody knowledge (geochemistry, geotechnical, geology structures).

Because DRX produces a variety of plans across a range of budgets, it uniquely provides an investment curve (see Figure 1). Project teams can make informed, objective decisions as each point on the investment curve corresponds to a full drill plan.

DRX provides sensitivity analysis for drilling programs. And since the investment curve is non-linear, the more you drill, the less incremental value you are generating. You can allocate drilling capacity to maximize resource/ reserve drilling to meet production requirements if you have multiple zones available.

DRX Investment Curve
Figure 1: DRX investment curve at Jacobina project

Underground project – Yamana Gold’s Jacobina mine

Yamana Gold Drill Plan
Figure 2: Jacobina 85 hole baseline plan (green) and DRX 45 hole plan (orange)

Figure 2 shows the drill hole locations for a baseline plan (green) and one of the DRX generated plans (orange). The drill plan is designed for a highly constrained stope and in-fill drilling program at Yamana Gold’s Jacobina mine.

In this case, the drill program is being designed to de-risk stopes a final step before moving to production. The working environment is highly constrained by the fact that drill rigs setup is dependent on production timing. Additionally, safety offsets from the existing and planned drifts/crosscuts greatly limit the location where holes can be ‘threaded’ to hit the deposit.

Having been given the mine’s detailed sampling criteria for the planned stopes, DRX generated a number of plans meeting the availability and geometric constraints. Each of the DRX plans also reported on how each of the required KPIs was being met.

Although drill plans are three-dimensional, DRX results are initially presented as a 2D investment curve. Because each point on the curve corresponds to calculations made on an AI-generated drill program that meets all project specific constraints the team can quickly decide how many meters should be invested in each drilling program.

The aforementioned Figure 1 shows the DRX investment curve where the 17.5 km (10.9 mi) 85-hole baseline plan is shown in green. Plans that plot to the upper left produce higher volumetric conversion for less drilling. Each point on the curve corresponds to a complete drill hole program incorporating natural deviation, meeting all constraints and adapting to new data. The project team can decide what is of higher priority given their current constraints: decreasing drilling meters, and time, for the same conversion or increasing the volume being de-risked.

The DRX curve also shows how increasing the percentage of a volume that is de-risk, properly drilled off to meet a sampling requirement, demands a non-linear amount of drilling. Getting the last 5% of the volume de-risked will always require many more meters than de-risking the first 5%.

With a number of plans and their associated KPIs, mine staff can objectively access the plans and decide whether continuing to drill is adding significant value. If you consider that all mines have more volumes to explore and de-risk than drilling capacity, ensuring that each volume is drilled efficiently allows drill capacity to be re-allocated elsewhere in the mine. This increases the opportunity to grow the resource (step out drilling) or drill new exploration holes.

Many of the emerging geoscience-based Machine Learning AI tools focus on exploration and discovery, they will help you decide where to drill. DRX will tell you when to stop drilling.

Ultimately, DRX is a business decision support tool that integrates drill hole layouts to maximize the value of each meter drilled.

Open pit project – Royal Nickel Corporation’s (RNC) Dumont project

Royal Nickel Corporation applied DRX to their Dumont open pit project, located 25 km (15.5 mi) northwest of Amos, Quebec, Canada, to evaluate our technology. The Dumont project posed many challenges, such as minimum drill hole spacing, limited surface drill setup locations due to waterway exclusions, limited dip angles, potential structural exclusion zones etc. This meant expensive drilling setups, so RNC needed significant improvements to conversion efficiency of a volume of ground from the indicated to the measured category while meeting all project constraints.

RNC was interested in DRX’s capability of producing multiple drilling plans based on varying budgets. Creating multiple valid options enabled the company to select the appropriate plan that best aligns with its strategic goals and budgets.

When compared to the manual layout, the DRX-3 solution decreased the total number of drill holes from 64 (in manual) to 54, by finding locations where two or more drill holes could be drilled from the same drill setup. Not only that, but it also produced a 48% increase in conversion rate (2975 cubic m/m in manual versus 4394 with DRX-3). Such an increase in resource conversion efficiency saved money, but more importantly, it saved time.

In conclusion, maximizing the value of each meter drilled increases the value of each limited drilling season or may decrease the time required to bring a resource to market. Notwithstanding the optimizing capability, DRX provides real choice flexing rapidly changing economic, operational, geologic, and even social/political conditions.

Increasing operating time while decreasing operator risk

Another outcome from optimizing a resource drilling operation, such as the Dumont project, is that the algorithm can often decrease the number of drill pads/stations required to complete a program.

In Figure 3, we compare a DRX generated program to a baseline ‘optimized’ program. The decrease in drill pads does not affect conversion efficiency, in fact, the DRX program increases de-risked metal, while also decreasing the total meters drilled. The decrease in meters drilled proportionately decreases the time required to complete the program.

The most interesting point in this program is that the DRX plan almost halves the number of setups required. This has several positive outcomes.

The overall environmental footprint and ground disturbance are reduced. Fewer pads mean fewer access roads. If existing pads can be used, then there is no additional ground disturbance and a potential reduction in permitting requirements.

Operator risk and exposure are reduced by eliminating the need to mobilize and demobilize the drill rigs.

And finally, because there are fewer drill rig moves the rig spends a larger proportion of its time drilling producing valuable data.

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