Please note that, in accordance with Vektore’s Data Anonymization (DA) protocols, certain details about the deposit have been withheld or generalized to protect our clients.

Our mission was clear: revisit the discovery hole and extract structural insights – both those tied to mineralization and those defining the broader architecture. The challenge? Working with non-oriented core while still delivering a reliable structural framework to guide follow-up drilling. We took it head-on. This is where Orebody Knowledge (OBK) plays a critical role (Maptek, 2018). A robust OBK framework ensures that early-stage structural insights are captured, reducing uncertainty and increasing the efficiency of subsequent drilling decisions. Without it, every hole risks being just another guess.

Our approach leveraged Structural Inversion™, which together with Structural Convergence™ comprises the concept of Structural Quality Optimization™ (QO) proposed by Monteiro (2005) and Vektore (2012–2025). We set a reference mark on the mineralized core and collected structural data using the Structural Vectoring® Log (SVL – Vektore, 2012). To strengthen our dataset, we worked with the client to open a trench along the dip-direction of the discovery hole – an essential step in validating our reconstructed architecture (see Figure 2).

Structural Inversion™ is a cutting-edge method that reconstructs the likely orientations of key mineralization-related structures, using a robust algebraic algorithm in 3D (see Figure 3). By directly harmonizing the inversion set with a reference dataset obtained from within the same structural domain, it reveals geometrical relationships that would otherwise remain hidden. This powerful approach unlocks new structural insights, giving geologists a clearer picture of the mineralization architecture early on. With this knowledge, drilling strategies can be redefined with precision – maximizing efficiency and reducing costly guesswork.

Based on our Structural Inversion™ study, we provided a clear prescription for optimized drilling: the next borehole should be drilled from W-WNW to E-ESE to properly intersect the mineralization projected from the discovery hole. To ensure precise execution, we supplied the client with a recommended drill site (N-E-Elevation coordinates) and the exact dip/dip-direction for the verification (proposed) hole: 50°/115° (see Figure 4). This approach is designed to maximize mineralization intersection, reducing uncertainty and improving targeting efficiency.

Initially, the client explored alternative drilling strategies, opting to test continuity through a series of additional boreholes rather than immediately following the prescribed validation hole. While this approach provided valuable data, the sought-after mineralization was ultimately intersected only after implementing the Structural Inversion™-based recommendations (see Figure 5). In hindsight, had the prescribed approach been followed earlier, the discovery could have been made more efficiently, with fewer drill holes and lower costs. A post-campaign assessment determined that the follow up non-intersecting holes accounted for approximately 45% of the drilling budget allocated to this target – highlighting the potential for significant resource optimization in future exploration programs.

This highlights the Value of Information (VoI) in mineral exploration (Lawie, 2024). Spending early on high-confidence structural data – such as that derived from Structural Inversion™ – reduces wasted drilling and maximizes the return on every meter drilled. In the end, the cost of not having the right information far outweighs the investment in obtaining it.

This case highlights a fundamental challenge in exploration: drilling without a clear structural framework leads to unnecessary cost and uncertainty. The Second Borehole Problem is real—without proper orientation, even promising discoveries can become difficult to follow up. By applying Structural Inversion™ on non-oriented core, we reconstructed the mineralization architecture, providing a data-driven drilling prescription that ultimately led to success. However, the delay in adopting this approach resulted in significant resource losses, with non-intersecting holes consuming 45% of the drilling budget. The key takeaways are:

• Orebody Knowledge (OBK) is critical. Without a solid understanding of structural controls, every drill hole is a high risk.
• The right information at the right time saves resources. The Value of Information (VoI) in structural analysis is undeniable – early investment in high-confidence data prevents wasted drilling.
• Precision and smart drilling is the future. Methods like Structural Inversion™, Structural Quality Optimization and Structural Vectoring® Log (SVL) provide geologists with better tools to define geometry and continuity—before wasting meters.

This case offers a clear lesson: structural insights are not just useful – they are essential. The cost of guessing is too high, and the path forward is clear: integrate structural intelligence early and drill smarter.

It’s time to move beyond guesswork in exploration. The Second Borehole Problem is avoidable. With the right structural insights, you can drill smarter, faster, and with higher confidence. Let’s discuss in the comments or reach out to us – let’s talk about your next drilling campaign.

   References

Lawie, D. (2024) Valuating Ore Body Knowledge – The Financial Keystone for Mining Success in: Geohug podcast -https://www.youtube.com/watch?v=IFxtRdoVE6c

Maptek. (2018). Maptek Roy Hill smart mining partnership. Retrieved from:

https://www.maptek.com/forge/september_2018/roy_hill_smart_mining_partnership/

Monteiro, R. N. (2005) Structural Inversion: Concepts, Procedures and Implications to Mineral Exploration/Exploitation. Internal ITSL Memorandum. December 20, 2005. 5 pgs.

Vektore (2012–2025) various references: Structural Geology in Mineral Exploration – various short courses to University of Western Ontario and clients; Structural Vectoring Log – SVL; Best Practices in Structural Exploration Geology and Standard Operating Procedures; Software development: Ore.node, vSTAR and vSTAR App.

The post From Uncertainty to Discovery: Structural Quality Optimization in Action appeared first on Vektore Structural Geology and Technology.

Although we had geophysical data, much of it was overwhelmed by a strong and dispersed magnetic signature, making it ineffective for pinpointing new targets, particularly those with complex geometries. Copper-gold soil anomalies suggested a possible extension of a known IOCG deposit, leading us to design a drilling program to test a horizontal mineralization model across a recently acquired tenement. However, at the time, our core orientation set was limited, and crucial structural information was not extracted during the first round of logging. This meant we lacked insight into the internal features of the stratabound-style mineralization, leaving us uninformed of the true grade distribution, structural controls, and the existence of potential ore shoots. As a result, we were working with an incomplete picture, one that could significantly impact on our client’s drilling decisions.

We were tasked with reprocessing the available oriented core within the known mineralization, focusing on extracting structural features related to both mineralization and deposit architecture. Our goal was to assess whether the prescribed drilling pattern was appropriate, process the data, and define the internal structure of the mineralized system. Since grade distribution and structural features often share geometric patterns (Monteiro, 1996; Monteiro, 2004), we set out to identify and validate these relationships.

Our toolbox included the Structural Vectoring® Log, used to systematically capture and classify structural features observed in core, alongside with vPCD^TM (Vektore – point cloud deletion, 2012). Together, these methods enabled us to query, filter, and assign grade values to structural features, providing an initial assessment of grade-structure correlations. While our process involved stepwise deletion of lower-grade samples, our primary objective was to remove boreholes that did not align with mineralization geometry to refine the mineral intersection geometry (MIG). Further insights on mineralization- and architecture-related structural features can be found here: Exploration Success … What’s the Drill? 

Over several months, we conducted detailed structural logging, focusing first on characterizing the structural controls on the mineralization system. This included sulphide lineations (see Figure 1), as well as the shape orientation of minerals and inclusions within sulphide stringers. In addition, we gave particular attention to mineralization-related structural features. To gain a better understanding of the geological framework, we also recorded architectural-related structural features, capturing the geometry in which mineralization was embedded. Our goal was to monitor the orientation distribution of these structural features under the working hypothesis that grades and lineations were spatially correlated. If validated, this relationship could be leveraged to optimize our drilling pattern and improve targeting efficiency.

As a result of the exploration team’s bold approach, the decision to revise the prescribed drilling pattern – guided by our structural analysis and deliverables – led to the discovery of a new Breccia Ore zone, returning approximately 95 Mt of copper-gold ore at 0.7% CuEq of inferred resources (communication from client). The deposit remains open to the north, and our work also identified additional ore shoot orientations that require further verification.

Ore shoot spatial orientations and their locations were determined, validating the hypothesis that mineralization-related structural features are directly linked to grade distribution (see Figure 2 and Figure 3). This structural insight also explains the bulls-eye anomaly in soil geochemistry, which aligns with the projection of north-dipping ore shoots (see Figure 4)

The Value of Information (VoI – Lawie, 2024 and Gillis at al., 2024), which is the estimated worth of acquiring additional knowledge before making critical decisions, was clearly demonstrated through our work, significantly enhancing Orebody Knowledge (OBK – Maptek, 2018). By integrating newly gathered structural data, particularly from oriented core logging, our team gained a far clearer perspective on the geometry and continuity of the deposit, leading to the recognition of inclined ore shoots where none had previously been identified. This deeper understanding exemplifies the core principle of OBK, where every insight into a deposit’s architecture refines exploration strategies, reduces geological uncertainty, and enhances economic decision-making.

Through the application of Structural Vectoring, the prescribed drilling pattern was revised, allowing for the verification of grade distribution data and the validation of its relationship with mineralization-related structural features. This refinement directly influenced mineralization continuity, ensuring a more data-driven and geologically informed exploration strategy. The recognition of ore shoots introduced the possibility of underground mining, challenging the initial assumption that open-pit exploitation was the only viable option. This shift exemplifies the power of OBK-driven decision-making, where understanding the internal architecture of a deposit enables more efficient, cost-effective, and sustainable resource extraction. The VoI in this case is evident – not only did it reduce geological uncertainty, but it also unveiled an entirely new economic pathway for resource development. Furthermore, these findings extend beyond this single deposit. Other IOCG sites in the region could benefit from this enhanced Orebody Knowledge, refining their exploration models, reducing risk, and improving drill targeting efficiency. Armed with such detailed structural knowledge, we can design more precisely drilling campaigns, model resources more accurately, and make better-informed decisions that directly shape our approach to discovering and developing IOCG deposits and other deposit types.

This case study exemplifies how high-value geological information transforms decision-making, optimizes resource strategies, and ultimately increases financial and operational efficiency. Investing in a VoI-driven approach to Orebody Knowledge is not just about collecting data – it’s about empowering smarter, more profitable decisions that maximize resource potential.

What if your best target is still hidden – this discovery was possible because we challenged assumptions and let geology lead the way. What’s your experience with structural geology in mineral exploration? What are your thoughts on this approach? Have you faced similar challenges? Let’s discuss!

     References

Gillis, A., Steen, J., Dunbar, S.  and Nordenflycht, A. (2024) What causes mining asset impairments? Resources Policy 90, pg 1-10.

Lawie, D. (2024) Valuating Ore Body Knowledge – The Financial Keystone for Mining Success in: Geohug podcast – https://www.youtube.com/watch?v=IFxtRdoVE6c

Maptek. (2018). Maptek Roy Hill smart mining partnership. Retrieved from:

https://www.maptek.com/forge/september_2018/roy_hill_smart_mining_partnership/

Monteiro, R. N. (1996). Gold Mineralization at Ouro Fino Mine, Brazil (Doctoral dissertation). University of Western Ontario, London, Canada.

Monteiro, R. N., Fyfe, W. S., & Chemale, F. Jr. (2004). The impact of the linkage between grade distribution and petrofabric on the understanding of structurally controlled mineral deposits: Ouro Fino Gold Mine, Brazil. Journal of Structural Geology, 26(6), 1195–1214.

Monteiro, R. N. (2014) Structural Controls of Mineral Deposits …. How to Get it! SIMEXMIN 2014, 39 slides

Vektore (2012) Point Cloud Deletion (vPCD^TM) – Standard Operating Procedure.

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Indeed, your post has sparked a range of insightful responses from the community, spanning concerns about potential misuses to the challenges of ensuring robust QA/QC in core orientation programs and related structural readings. The emphasis on assessing measurement-net deviation – encompassing all steps from core orientation to the final application of the structural dataset, is both relevant and critical. As highlighted by Brett Davis and others, this issue extends far beyond the technicality of structural readings if we consider the final and usable product for the three-dimensional modeling of mineral targets (measurement-net accuracy and precision). These reactions highlight longstanding worries over the reliability and value of structural data, particularly since the introduction of the BallMarkTM core orientation tool, in the late 1990s. This innovation not only advanced the core orientation industry but also introduced a range of new workflows and challenges, including the critical issue of core misorientation. Effectively addressing these challenges is crucial for establishing stronger industry standards and reinforcing trust in the structural datasets that underpin three-dimensional modeling of mineral targets and orebodies.

The reliability of the core orientation program itself emerges as the foundation upon which all subsequent structural data depends on. Without robust, end-to-end QA/QC measures, even the most sophisticated structural reading method can fall short of providing the dependable datasets essential for geological modeling and mineral resource assessments. Therefore, as an industry, we must address the measurement-net accuracy and precision of structural readings in oriented core programs to overcome these significant and impactful issues. Key works like Ragan (1973), Nelson et al. (1987), Vearncombe & Vearncombe (1998), Marjoribanks (2010), Holcombe (2013), Stigsson and Munierand (2013), Davis (2014), and Myers et al. (2016), among others, address some these challenges and serve as essential reading for professionals in the field, and we highly recommend reading them.

In 2002, while working in the Thompson Nickel Belt in Canada, I encountered significant challenges measuring out-of-plane lineations of pentlandite, biotite, and inclusions within massive sulfides, including fault kinematics and fold asymmetry studies from oriented core (Figure 1). My objective was simple but crucial: correlate such lineations and fold asymmetry domains with nickel grade distribution to determine the mineralization structural controls and thus enhance predictability in short-term and near-mine drilling. Existing structural extraction methods, such as readings from core restoration rigs (commonly known as ‘rocket launchers’), which require adjustments for the influence of magnetic pyrrhotite, or Alpha-Beta-Gamma readings, which are inherently incapable of capturing out-of-plane lineations, have proven inadequate for meeting the stated requirements. While these limitations extend beyond your question, Federico, they remain fundamentally important in achieving reliable structural analysis and establishing connections with the spatial distribution of grades and the characterization of ore shoots (Figure 2). For a deeper understanding of the complexities of the nickel sulphide deposits in the Thompson Nickel Belt and the importance of developing a robust, lineation-rich structural database, I recommend consulting McDowell et al. (2007), Lightfoot et al. (2017), and Monteiro (2017).

Figure 1 Pentlandite-rich massive sulphide bodies as observed in underground openings at the Thompson mines – Thompson Nickel Belt, Canada. The left image shows a dashed lineation of biotite (dark elliptical spots), while the right image features strings and lineation of pentlandite (lighter dots embedded within a pyrrhotite matrix). It is important to note that these lines represent the traces of the lineation, which exists in three-dimensional space and extends beyond the photographed surface.

Figure 2 Projected trace of the folded ore shoots onto the Thompson Mine footwall, highlighting the critical link between structural architecture of the deposit and grade distribution. Modified from Lightfoot et al. (2017).

In response to this challenge, I developed a cylindrical coordinate-based reading system to independently measure lines and planes with high precision (Monteiro, 2002), now known as the Structural Vectoring® Log or SVL. By leveraging vector calculus and creating a custom Visual Basic code for Excel®, this system offered a robust solution to address the structural reading inconsistencies of other methods. It provided a reliable and straightforward way to collect kinematic and asymmetry data for a more complete structural readings and analysis of mineral targets. Simply put, any structural feature – planar or linear – and associated attributes that can be measured in an outcrop with a compass, can be also measured using the SVL method, whether from oriented and non-oriented core. This innovation and its intellectual property were safeguarded under Inco Ltd and Vale until their transfer to Vektore in 2012, following my retirement. Since then, we have been improving its readings and associated processes, and over time, this innovation evolved into the Structural Vectoring Log (SVL) – a module of the Ore.node software [Link to Ore.node], which has been adopted by leading companies to streamline their structural measurements (Vektore 2, 2012-2025). Building upon the SVL, we developed in 2023 the vSTAR™, an augmented-reality structural reader that prioritizes instrument-level accuracy, precision, speed, visualization and processing in real-time [Link to vSTAR]. These tools have the potential to transform how structural data is collected, analyzed, and integrated into mineral exploration workflows, driving significant efficiency and decision-making confidence (Vektore 1, 2012-2025).

Misoriented cores remains a major challenge, undermining entire datasets, rendering a very low measurement-net accuracy and precision. Aware of this issue, we began developing a suite of processes in 2005 to enhance the strength of both oriented and non-oriented core programs – the Structural Inversion and Structural Convergence methods (Monteiro, 2005 and Vektore 1&2, 2012-2025), which are part of the Quality Optimization process we are deploying in the industry.

Leading companies like Ero Copper, Centaurus Metals, Alvo Minerals, and OZ Minerals have embraced these workflows, by certifying their teams as Structural Optimization Specialists [Link to Post]. Through a hands-on 40-hour course, these Vektore-certified specialist gain the skills and knowledge needed to address core orientation misorientation challenges and elevate the measurement-net accuracy and precision of the structural data delivered to the geological modeling and resources teams.

We look forward to sharing more about these integrated solutions in future posts, where we will dive deeper into the techniques and open the conversation about how they can improve and simplify workflows to deliver robust datasets for analysis and integration to 3D models.

Consulted References

Davis, B. (2014). Use and abuse of oriented core; in: Mineral Resource and Ore Reserve Estimation. Second Edition;Publisher: AusIMM.

Holcombe, R. J. (2014). Oriented Drillcore: Measurement, Conversion, and QA/QC Procedures for Structural and Exploiration Geologists – last updated in May 2023. https://www.holcombe.net.au/downloads/HCOVG_oriented_core_procedures.pdf.

Lightfoot, P. C. et al. (2017) Relative contribution of magmatic and post-magmatic processes in the genesis of the Thompson Mine Ni-Co sulfide ores, Manitoba, Canada. Ore Geology Reviews 83 (2017).

Marjoribanks, R. (2010) Geological Methods in Mineral Exploration and Mining. Second Edition, Springer-Verlag, Berlin, 238 pp. https://link.springer.com/book/10.1007/978-3-540-74375-0.

McDowell, G. M., Stewart, R. & Monteiro, R. M. (2007) In-mine Exploration and Delineation Using an Integrated Approach. Advances in Mine Site Exploration and Ore Delineation in: Proceedings of Exploration 07: Fifth Decennial International Conference on Mineral Exploration edited by B. Milkereit, 2007, p. 571-589.

Monteiro, R. N. (2002). Structural Analysis of Borehole Data and Structural Scenario Design. Inco Internal Peer Reviewed Report.

Monteiro, R.N. (2005) Structural Inversion: Concepts, Procedures and Implications to Mineral Exploration/Exploitation. Internal ITSL Memorandum. December 20, 2005.

Monteiro, R. N. (2017) Structural Controls of the Thompson Nickel Belt Mineral Deposits. SIMEXMIN 2017 (VIII Simpósio Brasileiro de Exploração Mineral) – 34 slides.

Myers, R. at al (2016) An Inexpensive Way to Maximize and Preserve the Value of Oriented Core: The Orientation Log. SEG Discovery (107): 1–19.

Nelson, R. A.; Lenox, L. C.; Ward, B. J. (1987). Oriented Core: Its Use, Error, and Uncertainty1AAPG Bulletin 71 (4): 357–367.

Ragan, D. (1973) Structural Geology: An Introduction to Geometrical Techniques. Second Edition, published by John Wiley & Sons Inc. 232 pages.

Stigsson, M. and Munierand, R. (2013) Orientation uncertainty goes bananas: An algorithm to visualise the uncertainty sample space on stereonets for oriented objects measured in boreholes. Computers & Geosciences, Volume 56, July 2013, Pages 56-61.

Vearncombe, J. and Vearncombe, S. (1998). Structural data from drill core. Australian Institute of Geoscientists, Bulletin. 22. 67-82.

Vektore 1 (2012-2025) Vektore Webpage at www.vektore.com

Vektore 2 (2012-2025) Best Practices in Structural Geology applied to Mineral Exploration.

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I prefer to describe them as sulphide body lineations. In other instances, in nickel-sulphide exploration, we might see sulphide blebs or droplets that, by flattening or imposing flow, or both, develop an ellipsoidal shape. Occasionally, these blebs connect themselves along opposite faces of the core. In this case, I prefer to call them droplets-blebs sulphide lineations.

Despite their formational origin, we should first try to understand their shape, orientation and distribution. They are vectors! They are the most basic type of mineralization vectors at the core scale. Now we want to know what are they aiming at? How pervasive are they? These are questions that can be simply addressed at the drill site and validated as drilling progresses.

Indeed, if many of these mineralization vectors are distributed within or nearby mineralization envelops, they can distinctively show grade distribution and its continuity in space. They have the inherent capacity to direct towards the best locations for new drilling, which saves you time and money in your budget.

Continuity, in these cases, is pre-emptively determined by using multimeters – as indicated in the following images. Normally these lineations are not particularly constrained into planes, therefore we use the vSET Method© to fully read their parameters from the core. In this way our 3D models give the most robust picture possible.

ROGERIO MONTEIRO OCTOBER 23, 2014

The post How conductivity is highlighted through vectoring of sulphide lineations appeared first on Vektore Structural Geology and Technology.

Nevertheless, if you want to consistently drill for exploration success, take note of the following: drill into the mineral body, not the mineral target!

The discovery hole and the holes that follow must reveal the most reliable information to allow for an accurate valuation of a mineral property. The collection of mineral intersections created by drilling is the result of the interplay between two distinct geometries: the drilling configuration and the mineral body. I call this cloud of piercing-points mineral intersection geometry or MIG. MIG is not to be confused with the mineral envelope. MIG is about the orientation, distribution, quantity and quality of the mineral intersections provided by a drilling campaign. MIG is the set of mineral intersections used to produce a mineral envelope. Different exploration teams will surely come up with diverse MIGs and therefore they would be susceptible to create different mineral envelopes. Some mineral envelopes will be very good and some others will require additional drilling to approach a reasonable MIG. The best MIGs are the result of a real-time and dynamic review of each borehole that cuts through the mineral envelope. Necessary changes should be carried out to the next borehole and so forth – so the drilling geometry must be highly interactive, otherwise the MIGs will be poor. Well configured MIGs are more predictive and less expensive than the poor ones and will speak volumes about the experience and strengths of the exploration team. A mineral body with a reliable estimate of grade distribution and geometry is a required product to raise interest and investments.

How can one accomplish an effective drilling workflow task, which allows the drilling results to generate the best MIG possible, in a timely manner, within budget and thereby deliver value to investors?

In order to tackle this question one must recognize the power of drilling into the mineral body – a three-dimensional entity, to understand the grade distribution in the context of a particular geometry. This may seem simple and straightforward, but good exploration practices need to be followed to maximize value and minimize risk. The broad framework of such workflow is already out there in the industry (Vearncombe, J. & Vearncombe, S., 1998; Marjoribanks, R., 2010; Davis, B., 2012; Holcombe, R., 2014; and Monteiro, R.N., 2015).  However, it needs to be reconfigured in such a way that it would allow for early predictionsabout the shape of the mineralization, and its continuity and grade distribution. In this context, I expect that if the current industry XYZG Exploration System is augmented with the addition of mineralization-related structural vectors to build the concept of the XYZGV Exploration System the reward should be significant – as it will be explained ahead. By adopting this practice, and optimizing the MIG, exploration geologists should be able to better manage their exploration time and budget, while reducing risk and controlling uncertainties.

The XYZG stands for (x, y, z) coordinates of a sample that returns G, which is the grade. The G of the XYZG is just a scalar property! This is the traditional geochemical or assay sample we collect from core. It is a one-dimensional value that has no directional information to be projected into the three-dimensional space – unless, for instance, it can be vectorized by variography; however, such vectorization requires a large amount of mineral intersections – increasing time and investments – before spatial inferences can be drawn.

On the other hand, XYZGV is geometry-based at each sample site. XYZGV stands for (x, y, z) coordinates that returns not only G but also V, which is a type of vector (Allemendinger, Cardozo and Fisher, 2012) – a structural vector! The XYZGV implies that a grade value, obtained from a sample at (x, y, z) coordinates can be described as a vector or axis.Therefore, this grade can be projected along the mineralization-related structural vector. It not only empowers the exploration geologists to early detect and understand the hidden architecture of the mineralization and continuity, but also prompts them to fast redirect drilling to better intersect the mineral body (Figure 1). Vektore has improved such practices (Monteiro, 2013a and c) with proven record of significant successful applications.

Figure 1 The XYZGV Exploration System allows us to predict the mineralization architecture and its continuity in early stages of exploration by vectorizing the mineralization-related structural features. Note that “V” represents the structural mineralization vector symbolized by the sulphide lineation in this nickel sulphide intersection. The red vector likely describes the flow direction during the mineralization event at this point in space with high probability of pointing towards the mineralization center. Grade and mineralization vectors are fully harmonized and as such they are powerful geometrical predictors.

How can grades and related structural vectors boost efficiency of exploration projects and improve the use of exploration resources?

The best possible path from target to deposit can become apparent and acted on, early in the exploration process, if V is considered; otherwise investments can be denied and discovery postponed. As it is indicated on Figure 1, structural mineralization vectors can effectively influence the decision-making process and its exploration path. The XYZGV Exploration System has the potential for providing explorers with a robust exploration workflow that should enable success! So, how can one move from XYZG to XYZGV? By adding two key players to the current exploration practices: oriented core and structural economic geology analysis. One needs to find and characterize the mineralization-related structural features and place them into a reference frame – 3D space, for further projections and predictions; and this is the basis for structural vectoring within the mineralization space. Structural vectoring leads us to better MIGs and more accurate mineral envelopes.

In order to justify the shift towards the XYZGV Exploration System one needs to recognize its potential benefits. Although the use of oriented core and structural geology has increased recently, the current industry practice needs to be improved. Very few companies use core-orientation as part of their best practices, and some of those that have implemented it in the past are still challenged by its workflow and QAQC – fortunately, such issues can be resolved and streamlined if good practices and methods are applied (Monteiro, R. N., 2015 – vektore.com/services/technology-transfer/).

The mining sector is in its critical downturn at the moment. Investments are sparse and investors are carefully scrutinizing potential projects based on their well demonstrated value. Perception of project value and timing are critical! It is vital we extract the maximum amount of relevant information from core and quickly react to avoid costs that do not add value and are detrimental to the project. Such costs could potentially drive us to dead ends. By adopting the XYZGV Exploration System, one is able to capture and understand the broad architecture and structural controls of the mineral body in the early stages of its exploration, with fewer intersections. Adding V to the exploration geologist’s toolbox should provide sufficient and robust information to direct drilling with the goal of solving geometrical uncertainties as soon as they appear – improving efficiency. For this reason, the XYZGV Exploration System empowers us to act earlier and more effectively in the decision making process. Its inherent capacity of quickly determine the most reliable MIG is substantial and it brings excellent backing for an effective press release.

Exploration companies that incorporate V into their current practices would be able to generate better MIGs and interactively and effectively better dissect a mineral body. Therefore, it is not difficult to predict that the XYZGV Exploration System and its capacity to work with structural mineralization vectors will become a valuable requirement in the mineral exploration business in the near future. The current industry situation represents a great opportunity to test the value of implementing the XYZGV Exploration System. Within this context, in a recent interview published by the Northern Miner Daily News (2015), Mr. Cochrane, a senior research analyst at the Metals and Mining Consultancy in London, stated that if gold price fall below US$1,000/oz., miners will have to raise their cut-off grades and focus on richer zones. In this case the understanding of the internal features of their mineral bodies (patterns, linkages, oreshoots’ geometry and continuities) are paramount – adding “V” to the XYZG most definitively helps addressing this need. Today’s mantra is to be fast, within budget and to efficiently deliver results to your investors.

So, why should one drill into the mineral body and not into the mineral target?

The mineral body is a three-dimensional entity, while the mineral target is usually expressed in two dimensions – the surface. Although related, the mineral body and the mineral target have very distinctive features. By adding the structural vector component to the XYZG we are able to better individualize and set them apart. As such, if one vectorizes the mineralization-related geometrical features observed at each drilling intersection, and progressively takes it into account on subsequent drilling, one is definitively drilling into the mineral body, which is far more effective and rewarding than drilling the mineral target. Interactive drilling and dynamic assessment of the exploration drilling based on the diligent vectorization of the mineralization-related structures is the key concept I am conveying! Since drilling into the mineral body requires a distinct and organized deployment of tools, methods and exploration drive in tune with the concepts presented above, it is very important to understand the roles and values of the following big players: MIG, XYZG, XYZGV, mineral target, mineral body and mineralization-related structures. Such drilling campaign definitely requires a well-designed oriented core program combined with a comprehensive structural economic geology analysis! This proposition is presented in

Figure 2, (based on the Blue Ocean Strategy – Kim and Mauborgne, 2005) where we present some of the main players or competing factors that best describe the differences between the two exploration approaches in consideration – XYZG and XYZGV. The competing factors grouped under “create” are critical for structural vectoring and efficiency of an exploration approach, and they are only available in the XYZGV Exploration System. This diagram provides another dimension to our discussion.

Figure 2 Strategy canvas comparing the XYZG (red line) and XYZGV (blue line) exploration systems based on competing factors. Eleven competing factors are considered in this diagram – scores are from low to high at each competing factor. These factors are grouped into “Reduce”, “Raise” and “Create”, which should be lowered, increased or added, respectively, to create a more efficient exploration approach. Note that the competing factors grouped under “Create” are only available to the XYZGV Exploration System. The XYZGV Exploration System outperforms its industry standard competitor, and adds desirable capacities to our toolbox.

Do you to have intersected mineralization without oriented core? Where to drill next?

Instead of using the trial-and-error drilling approach, with the hope of intersecting mineralization, one should test ways of figuring out the architecture of the target. In this regard, various methods to resolve this problem have been proposed in the literature. More recently, Holcombe (2010 and references herein) reinstated the idea of using the known orientation of a particular reference structure to re-position non-oriented core intervals in its likely original orientation. He called this procedure partially oriented core technique. As a different approach, the Structural Inversion© Method, devised in 2005, is a significant development in the field of processing structural data from non-oriented core. It uses a robust algebraic algorithm to recast the likely orientation of key structural mineralization vectors, which allows significant geometrical predictions (Monteiro, R.N., 2005; Monteiro, R.N. and Koronovich, J., 2006; and Monteiro, R.N., 2013b). This method was single-blind tested before it was deployed for use (Monteiro, 2013b and d and references herein). Since then, it has been used in various exploration sites with significant results by re-directing drilling towards unknown mineral body extensions; notably: IOCGs in Carajas and copper-related mineral targets in the Vale do Curaçá (Brazil). This method should not only conveniently help you to quickly understand the mineral body geometry, but also to acquire sufficient information to predict its extensions and to design a better drilling geometry. Indeed, such application should show you the benefits of capturing the structural mineralization vectors of your mineral target, even before you have been able to implement your own XYZGV program with oriented core.

As a final point, if we drill into the mineral body guided by vectoring the mineralization-related structural features we will significantly augment the probability of an exploration success outcome. This statement comes from our experience derived from different deposit types and exploration sites in a diverse range of mineral districts (nickel sulphides in the Thompson Nickel Belt and in the Sudbury Igneous Complex in Canada; IOCGs in the Carajas Mineral District, gold mineralization in the Iron Quadrangle, copper mineralization in the Vale do Curaçá in Brazil; and copper mineralization in the Copper Belt in Africa). The XYZGV Exploration System has the potential of being one of the much-needed changes in our industry! So, let us drill into the mineral body, not the mineral target! This action will not only potentially increase the return of exploration investments but also strengthen the credibility of the exploration team. Serious investors are on the look for that!

Consulted References:

Allemendinger, R.W., Cardozo, N. and Fisher, D.M. (2012) – Structural Geology Algorithms: Vectors and Tensors. Cambridge University Press. 289 pp.

Davis, B. (2012) Drill core orientation – An Inconvenient Truth – Parts 1, 2 and 3. http://www.orefind.com/

Holcombe, R. (2010) Oriented Drillcore: Measurement, Conversion, and QA/QC procedures for Structural and Exploration Geologists. 36 pp.

Kim, W.C., Mauborgne, R. (2005). Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant. Boston: Harvard Business School Press. ISBN 978-1591396192.

Marjoribanks, R. (2010) Geological Methods in Mineral Exploration and Mining. Springer-Verlag Berlin Heidelberg, 2nd Edition. 238 pp.

Monteiro, R. N. (2003). Structural Analysis of Borehole Data and Structural Scenario Design. Inco Internal Peer Reviewed Report.

Monteiro, R.N. (2005) Structural Inversion: Concepts, Procedures and Implications to Mineral Exploration/Exploitation. Internal ITSL Memorandum. December 20, 2005.

Monteiro, R.N. and Koronovich, J. (2006). Structural Inversion. Vale’s Technical Journal, OreShape Vol. 2, Issue 2, pg. 1..20-24. Inco Technical Services Structural Economic Geology Quarterly Newsletter.

Monteiro, R.N. (2011) Best Practices in Applied Structural Geology – Exploration and Exploitation of Mineral Deposits. Vale Global Exploration Technical Services.

Monteiro, R.N. (2013d) – Structural Economic Geology in Mineral Exploration – Day Three, Short Course, 51 slides.

Monteiro, R.N. (2013c) – The V-SET© Method. Vektore Exploration Consulting Corporation internal report.

Monteiro, R.N. (2013b) – The Structural Inversion© Method. Vektore Exploration Consulting Corporation internal report.

Monteiro, R.N. (2013a) Best Practices in Applied Structural Economic Geology – Mineral Exploration. Vektore Exploration Consulting Corporation internal report.

Monteiro, R.N. (2015) Vektore Webpage at www.vektore.com

Northern Miner Daily News (2015) Gold price fall may trigger another round of write-downs – interview with Cochrane, R. on July 24th, 2015. http://www.northernminer.com/news/gold-price-fall-may-trigger-another-round-of-write-downs/1003695595/sv64s8vMxvwq48svWo4zqvs4M2vx/?ref=enews_NM&utm_source=NM&utm_medium=email&utm_campaign=NM-EN07272015. Accessed on July 27th, 2015.

Vearncombe, J. & Vearncombe, S. (1998) Structural Data from Drill Core. In: More meaningful data in the mining industry. AIG Bulleting 22, pp 67-82.

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