• Diana M. Benz, Ph.D.

Are Large Land Packages Indicative of Poor Exploration Models?

Does this sound familiar:

  • Scanning and sorting regional samples for the highest values of copper, gold or zinc values

  • Narrowing in on the locations of mineral occurrences such as MINFILE reports

  • Pouring over old assessment reports

  • Following geology and lineaments from established mines

  • And staking large swaths of ground?

A lot has changed since prospectors walked around the bush taking grab samples and panning streams in the late 1800's searching for gold. Has our staking methods improved with the times?

Mineral staking and initial exploration activities have always been shrouded in mystery and extreme secrecy which makes sense since the likelihood of a grassroots project succeeding into a mine is 1:10,000.


The basic tenets of staking tend to be:

  • Always acquire more land than you think you need, particularly if it's cheap.

  • Select highly favourable geological environments and keep working until you find what you're looking for.

  • Sometimes you have to follow gut feelings as they may be better than black boxes, particularly when black boxes produce more data that could be usefully integrated and handled.


In 1977, a Northern Miner article on 'Exploration philosophy is the key: Why some find mines and some do not' by Stanley Holmes described exploration as:

  • The lifeblood of the natural resources industry.

  • Where imagination, ideas, money, perseverance, flexibility and luck coincide.

  • A gamble with geology being the only science that keeps it from being a lottery.

  • A fool with his money, a hole in the ground and a vendor lining its pocket.

And in 1978 Stanley Holmes furthered his research with another article in the Northern Miner on 'Methodology a must for efficient exploration' where he determined that Stage 1, the regional appraisal is "mainly office work in which research and compilation regarding the proposed project area is carried out." The most important points at this Stage are:

  1. The area to be explored is selected;

  2. The geological environment is established;

  3. The geological model is conceptualized.

He indicated that the latter two points, geological environment and model, were the most important.


He further surmised that the "modelling must be complete with respect to what may be found within that particular environment, i.e., size, attitude, tonnage, structure, alteration, grade, depth, configuration, mineralogy, metallurgy, mining and economics of the deposit."


In 2017, McCuaig et al. described exploration targeting as generally falling somewhere on the spectrum between empirical and conceptual targeting where an empirical target focusses on regions with known or analogue mineralization/geology to search for known patterns and conceptual targeting is finding regions with evidence pointing towards known mineral system processes.


The primary focus of these exploration tenets is on 'known' patterns and processes.


This begs the questions:


Do we know all the details of every type of mineable mineralization?

Cox, Barton and Singer recognize this very issue in their Introduction for the USGS Mineral Deposits Models (eds. Cox and Singer):

"A mineral deposit model is the systematically arranged information describing the essential attributes (properties) of a class of mineral deposits. The model may be empirical (descriptive), in which instance the various attributes are recognized as essential even though their relationships are unknown; or it may be theoretical (genetic), in which instance the attributes are interrelated through some fundamental concept.

One factor favoring the genetic model over the simply descriptive is the sheer volume of descriptive information needed to represent the many features of complex deposits. If all such information were to be included, the number of models would escalate until it approached the total number of individual deposits considered. Thus we should no longer have models, but simply descriptions of individual deposits. Therefore, the compilers must use whatever sophisticated or rudimentary genetic concepts are at their disposal to distinguish the critical from the incidental attributes. It is commonly necessary to carry some possibly superficial attributes in order not to preclude some permissible but not necessarily favored, multiple working concepts.

The following example illustrates the problem. One of the commonly accepted attributes of the model for the carbonate-hosted lead-zinc deposits of the Mississippi Valley type is the presence of secondary dolomite. But do we know that this is essential? Suppose a deposit were found in limestone; would we reject its assignment to the Mississippi Valley class?

Or could it be correct that the critical property is permeability and that the formation of dolomite either (1) enhances permeability (and thereby makes the ground more favorable), or (2) reflects pre-existing permeability that is exploited by both the dolomite and the ore? Perhaps the dolomite merely records a particular range of Ca/Mg ratio in the fluid which in turn is characteristic of the basinal brines that constitute the ore fluid."


If we explicitly followed deposit models then there would be no diamonds in Canada and no super-giant deposits representing overlapping mineralizing systems and/or geological environments at Escondida in Chile.


Can we effectively adapt exploration models to reflect changes in economical deposit values and advancements in metallurgy?

Mineral deposits are formed as parts of larger, complex geochemical systems. Over the past few years base metal prices have changed drastically to meet societal demands, particularly for green energy products, and the rise of the needs for critical minerals (like rare earth elements) has seen a rise in exploration. We have re-evaluated projects away from the former ideal concentration, like 1 % copper, to much lower values, like 0.2 % copper, and a lot of the by-products of some future mines have now become a significant portion of their current resource calculations. Many 'new' projects are situated on old mines with the hopes of re-working tailings as well as searching for lower grade ore off-shoots or higher grade, but smaller, resources that were not considered economical in the past.

Are our current biases on what is considered economical today limiting exploration for new deposits tomorrow?

In the 1880's , miners brought legal action against an assayer in Salt Lake City, Utah because they could not confirm, with a gold pan, the presence of gold the assayer had determined on their property. It wasn't until 80 years later, in 1960, when Ralph J. Roberts, along with his fellow United States Geological Survey (USGS) geologists, were able to deduce the relationships between metal mineralization and the regional geology (like major thrust faults) resulting in the first exploration models for Carlin Gold Deposits (the invisible gold). In the 1950's, open pit mining and relatively cheap, yet efficient, cyanide extraction came to the forefront of mining technology to allow for the economical extraction of metals from large tonnage, low grade deposits like copper porphyry. But applying the open pit-cyanide extraction technology needed to mine Carlin gold also took over a decade before it was applied.


Do all potential mines form in clusters?

There are numerous statements that 'deposits form in clusters in prolific belts and exploration occurs outwards from known mineralization' but rarely is there a number associated with the actual distance between deposits that form the cluster.

Looking at individual random deposits listed as 'clusters': The Pobeda massive sulfide hydrothermal cluster largest dimension is approximately 4 kilometres. The Toki cluster copper gold porphyries occur in an area of 5 by 6 kilometres. The Bathurst Mining Camp (does not include the area concealed by Carboniferous cover) consists of 45 known deposits, over 3,800 square kilometres, has 'zone' clusters between approximately 5 and less than 10 kilometres. Seabridge Gold's K-S-M project potentially hosts 4 deposits/styles over approximately 10 kilometres with next the nearest developed prospect, Eskay Creek, at approximately 20 kilometers away.

Advanced and grassroots exploration are estimated to encompass 1,000s (32 km lengths) to 10,000's (100 km lengths) square kilometers with deposit development up to 1,000 square kilometers, while many recent exploration projects boast land positions in excess of 20 to 200 kilometres in length. By contrast, the majority of prospectors claims are around 5 km in length which is largely due to financial constraints and the need to prove that surface mineralization is within the area they staked.

And not all deposits form in clusters: polymetallic nickel copper deposits.


Finally, are large land packages indicative of poor exploration models?

With fewer new deposits being discovered each year it may be time to look outside the box of traversing the ground searching for surface mineralization or following up that one anomalous regional sample or MINFILE location. There is a wealth of regional information, and numerous advanced techniques for remote data collection and processing, that could be effectively utilized to generate unique targets that would not have been considered, or thought of, in the past; however land packages have increased exponentially to cover the most area of a 'prospective' geological region because staking is 'cheap'.

While large land packages may be more interesting to investors as they may think more land equals more chances at finding mineralization, the offset is that without refined targets the large areas become more expensive and time consuming to explore.


There hasn't been a lot of development in the way we explore for minerals [or in the way we mine them]. We rely heavily on proving deposit models in the early stages of exploration which can be very much to the detriment of a junior exploration company if they spend time and investor money chasing the wrong model. Deposit models, which are meant to be generic descriptions, are great at helping explorers determine the most likely geological scenario in which to find an economic deposit but explicitly following known deposit models and having poor exploration models can lead to excessive staking resulting in unnecessary impact on local land users and the environment.


Ideally, exploration models can be data-driven and consist of the most basic principles required for deposition, emplacement and/or accumulation with overlapping data relating to geochemistry, lithology and structure (when available).


About the Author:

Dr. Diana Benz has over 25 years of experience working in the mineral exploration industry searching for diamonds and metals in a range of roles: from heavy minerals lab technician to till sampler, rig geologist, project manager and business owner/lead consultant. She has a Bachelor of Science in General Biology, a Master of Science in Earth Sciences researching diamond indicator mineral geochemistry and a PhD in Natural Resources and Environmental Studies using geochemical multivariate statistical analysis techniques to interpret biogeochemical data for mineral exploration. Diana has conducted field work in Canada (BC, NWT, YT and ON) as well as in Greenland. She has also been involved, remotely through a BC-based office, on mineral exploration projects located in South America, Africa, Eurasia, Australia and the Middle East. Currently, Diana is the owner of Takom Exploration Ltd., a small geological and environmental firm focused on metal exploration in BC and the Yukon.



16 views0 comments

Recent Posts

See All