1. 3DS Blog
  2. Brands
  3. GEOVIA
  4. The importance of accurate Resource Estimation

August 16, 2018

The importance of accurate Resource Estimation

    SURPAC ENABLES THE ACCURATE PREDICTION OF RESOURCE FOR MINING OPERATIONS…
header
Avatar Chris Bates

SURPAC ENABLES THE ACCURATE PREDICTION OF RESOURCE FOR MINING OPERATIONS OF ALL TYPES & SIZES

THE PROBLEM

A common problem for all mining operations, from the smallest quarry to the most complex underground polymetallic deposit mine sites, is the difficulty they face in accurately predicting the resource that can be mined at their sites.

The problem with resource estimation in the real world is the margins for error. Mining Professionals do everything possible to mitigate and reduce this margin, but an error will always exist. Where the error becomes large, the effect on the business is also large. The financial model could be grossly overstating the value of the actual resource, meaning the mine will never make money, or the estimation could understate the resource, and a viable and potentially very profitable deposit could be left in the ground.

A poorly executed estimation could also place the higher grade part of the orebody in the wrong place due to poor selection of estimation criteria, or increase or reduce its size due to poorly selected search distance parameters. The images below show a simple estimation completed four times with differing anisotropic parameters – just one of many factors affecting the estimation. Differences in estimated values can clearly be seen.

In simple terms, there are many things that can go wrong with a resource estimation, and the effects can be severe.

THE EFFECT

The biggest effect as mentioned above is that a project may simply be abandoned. The estimated resource may not satisfy financing requirements, and that will be the end of the project. Potentially millions of dollars in exploration, feasibility studies and associated work could be thrown away.

An example of the kind of capital costs involved in a mining project can be found in this report.

At the other end of the scale, a project that will simply not be profitable, may end up going into production and end up failing or closing without achieving profitability. As well as all of the costs mentioned previously, significant capital expenditure costs would also be added on top. Hopefully, this mistake would be identified early in production, but a lot of money could be wasted before this happens, and a decision is taken to stop mining.

Not as extreme as these results, is the following more likely scenario. The resource is under or over stated and actual production does not tally with predicted production.

This introduces uncertainty at all stages of the mining process, and large amounts of money can be spent on trying to identify where the error has been introduced. A desire to fix the mistake could even see further errors being introduced in trying to implement a quick-fix, and a cycle of errors costing millions could occur, and be very hard to break out of. This would impact the profitability of the entire project.

Human error and lack of training can also play a part in creating or enlarging errors. For example, Geologists may try and employ as complex a methodology as possible in their resource estimation methodology, and end up introducing errors as a part of this process. Just because it may be possible to use Indicator Kriging on a deposit does not necessarily mean that Inverse Distance may not have been a more appropriate method.

Correct evaluation of all data, and the nature of the deposit itself is key. If the geologist does not understand the deposit, and the method of emplacement/mineralisation, it will be very difficult to build a good estimation. Having access to enough relevant data, and to the required tools is of paramount importance. We must always remember that we are seeking to minimise error. We know the estimation will always be a guess, but we need to do everything we can to achieve the “best guess”.

An example of a basic statistical evaluation of sample data.

THE SURPAC SOLUTION

By using sampling data, drilling data, geological knowledge, informed interpretation and geostatistical evaluation, GEOVIA Surpac is able to provide accurate resource estimation, the results of which have many uses, including for Shareholder reports, to help raise finance, as the basis for a Whittle evaluation of the finances of the deposit, to help develop the long term mine planning schedule and for intermediate and short term tactical scheduling in a software package such as GEOVIA MineSched. All of these are critical to the success of the mine, and effective resource estimation is often recognized as being a critical factor for the success of a business.

Surpac contains a comprehensive suite of geostatistical evaluation and modelling tools which enable the user to carry out detailed and extensive estimation work on their data. A full range of estimation validation and evaluation tools are also available for assistance in checking the work completed, such as the box and whisker image below.

SURPAC ADVANCED RESOURCE ESTIMATION TRAINING COURSE – 1-4 Oct 2018, Paris

Surpac remains a robust, auditable and proven accurate method of resource estimation. In order to enable clients to fully utilise these tools and arrive at their “best guess”, GEOVIA offers Services solutions including project assistance and consulting. Perhaps of most relevance is the Surpac Advanced Resource and Geostatistics Training course. 

This four day, classroom course, taught by GEOVIA Surpac Mining Experts, runs from 1 – 4 October at the Dassault Systemes Head Office Campus near Paris.

The course covers everything from data validation and review, through to resource reporting and classification with in-depth sessions on geostatistics, estimation methodology, and Surpac block modelling. The course is designed to ensure that the user is fully equipped to utilise their Surpac software to improve their estimations.

Of course, as with all software usage, data quality is key. A poor dataset will always produce a poor estimation. The purpose of this course is to ensure that a good dataset can be utilised to produce a good, or robust, estimation. A robust estimation will be statistically sound, with clearly defined reasoning behind each of the decisions made surrounding estimation parameters and criteria. The estimation will stand up to scrutiny from a fellow geologist.

Course Guide

To learn more about the course and cost of participation, please view or download the Surpac Advanced Resource and Geostatistics course guide.

Stay up to date

Receive monthly updates on content you won’t want to miss

Subscribe

Register here to receive updates featuring our newest content.