Best Practices in the Generation of a Coal Resource Estimate. · Minex Central Asia 2015, Astana, Kazakhstan. Photo insets: Cerrejon open pit mine, Typical Underground Longwall equipment

1

© SRK Consulting (UK) Ltd 2015. All rights reserved.

Presenter:

Location:

1


Best Practices in the Generation of a Coal Resource Estimate.

David Lawrence

Minex Central Asia 2015, Astana, Kazakhstan.

Photo insets: Cerrejon open pit mine, Typical Underground Longwall equipment

2


SRK Office Locations

>1,600 Professionals, 50 offices, 22 countries, 6 continents

3


SRK Project Experience in Kazakhstan and the Russian Federation.

Project Client Year Country Project Title Discipline

Project Blackrock Coal Musana Plus Services Ltd 2010 Kazakhstan An Independent Technical Study on the Coal Assets of

Comco, Kazakhstan Competent Person's Report

on Developed Property

Nikolsky Option Study OJSC SUEK 2011 Russian Federation A Scoping Level Option Study for the Nikolsky Greenfield Site Multi Discipline Technical

Study (Scoping Study)

RU0246 Elegest Project Review

Mitsui & Co. Ltd (SRK Russia) 2011 Russian Federation Review of Elegest Feasibility Study geology

Independent Technical Review

SUEK 2011 OJSC Siberian Coal

Energy Company (SUEK)

2011 Russian Federation A Competent Persons Report on The Coal Mining Assets of SUEK Competent Person's Report

on Developed Property

Shubarkol Due Diligence

ENRC Management (UK) Ltd 2011 Kazakhstan

Project Rohan II An Independent Technical Summary Report on The Coal Assets of JSC Shubarkol Komir,

Republic of Kazakhstan

Independent Technical Review

Kuzbass Ugol Arcelor Mittal Mining 2011 Russian Federation Independent Report and Valuation of Severniy Kuzbass Independent Technical

Audit

RU00313 Coal Model Expertise SRK Russia 2012 Russian Federation Coal Modelling and Training Exercise to SRK Russia

Technical Training on Geology

Karaganda Mines Arcelor Mittal Mining 2012 Russian Federation Independent Coal R&R Audit, audit of group of eight underground mines and associated wash plants

Independent Technical Audit

Severniy Kuzbass Review

Arcelor Mittal Mining UK Ltd 2013 Russian Federation Severniy Kuzbass Review

Operational and closure costs review.

ENRC 2014 Eurasian Natural

Resources Corporation PLC

2014 Kazakhstan Technical Report on the Mineral Assets of Shubarkol Komir JSC, Kazakhstan Due Diligence Study

(multidiscipline)

Shurbakol South Arbat.LLP 2014 Kazakhstan A Competent Persons Report of the Shurbakol South Coal Deposit, Kazakhstan MRE on a undeveloped

deposit.

4


A Resource Statement is a Fundamental Requirement for Public Reporting.

• JORC 2012 Code is the Australasian Code for the Public Reporting of Exploration Results, Mineral Resources and Ore Reserves. (2004 code on longer valid)

• It’s guiding principles are Transparency, Materiality and Competence. • It is NOT a document for Mining Professionals which tells one how to estimate Resources and

Reserves but gives guidelines on technical matters. • It sets minimum standards for public disclosure and provides a subjective classification

system for tonnage and coal quality estimates which relies on the judgement of the Competent Person. Requires completion of ‘Table 1’ and is on the basis of ‘If not, why not?’

• Stakeholders include: Technical Resource and Reserve Estimators Mining Company Management Investment Community Financing Community

• Stock Exchanges and Professional Bodies regulate the content of the Public Reports, not the Joint Ore Reserves Committee (“JORC”)

• The term ‘JORC compliant’ refers to the manner of reporting/disclosure and not to the estimates. Use of the words ‘JORC compliant’ to describe resources or estimates is potentially misleading.

• Public Reports - are reports prepared for the purpose of informing investors or potential investors and their advisers on Exploration Results, Mineral Resources or Ore Reserves

A well presented and accurate Resource Statement is vital to secure investment funding

5


Generic Workflow For a Mineral Resource Estimate

Firm understanding of the Geology and

controls of Mineralisation

Data Quality Assessment and

Validation

Geological & Mineralisation

Modelling

Selection of Appropriate

Estimation Method Model Validation

Mineral Resource Classification with

Economic Potential

Compliant Mineral Resource Statement

and Sign-off

Workflow Can be applied to CP Sign-off process Exact Steps will be defined by Geology, Deposit type, commodity, etc..

6


Compliant Mineral Resource Statement and Sign-off

Mineral Resource Classification with Economic Potential.

Model Validation

Selection of Appropriate Estimation Method

Geological & Mineralisation Modelling

Data Quality Assessment and Validation

Firm understanding of the Geology and controls of Mineralisation

• Regional and Local scale geological and structural environment

• Phases and style of deposition (Complexity/Seam splitting and Washout)

• Location and throw on faults • Deformational history • 3D Continuity and correlation of coal seams and barren

intersections • Post deposition alteration from intrusions, weathering, in-situ

combustion, previous extraction and erosion • Nature of Seam contacts and Roof/Floor strata • Geological and Coal Quality Variation.

CP should visit site personally, should have experience in the style of mineralization and understand fully the geological and mineralization setting

Firm Geological and Mineralisation Understanding:

“Poor Geological understanding = Poor Mineral Resource estimates”

7


“Poor Data Quality= Poor Mineral Resource estimates”

CP must review historical data and make conclusions on the data quality which should influence the Mineral Resource Classification


Mineral Resource Classification with Economic Potential

Model Validation





• Is the Data Quality fit for purpose? • Survey/topographic data Quality? • Sampling Methodology appropriate and unbiased (Split Core)? • Drilling recovery acceptable (95%)? • Have Quality Assurance/Quality Control (QAQC) procedures

been followed, and are the results acceptable? • Sample preparation appropriate including immediate sealing? • Sample Analysis by reputable/accredited laboratory? • Analysis Precision/accuracy/repeatability? • Sample Security? • Has data been collected following Industry standards and best

practices with Quality Assurance in place, i.e. documented protocols?

Data Quality: Introduction

8


“The CP is responsible for the data whenever it was collected if signing-off”

CP must be comfortable that the data has been validated CP must be completely sure the data is true and real and representative of what

was actually collected



Model Validation





• Does the data provided accurately represent the data originally collected-Check?

• Is there drilling core stored to check with the data and in what condition is it?

• Does the electronic data match the raw data? • Does the assay data match the laboratory transcripts? • Is the electronic data error free and in a usable format? • Is ALL of the data included, even bad holes? • Have absent/Null values been dealt with correctly in the

electronic data? • Has there been any Independent check sampling and

verification? • Any twinned holes to verify historical data?

Data Quality: Validation

9

© SRK Consulting (UK) Ltd 2015. All rights reserved. “Geological and structural controls must be incorporated in 3D modeling”

• Good quality core of sufficient drilling diameter, which has been logged by competent coal specialist is a vital factor to obtaining good quality data.

Core Size, Measurement, Recovery, Storage and Coal Sampling.

10


CP must ensure QAQC Protocols are in place and adequate CP must decide if the data meets JORC 2012 Data Quality Standards



Model Validation





• Several phases of drilling and sampling using different techniques with different Quality

• Lack of Quality Control information • Core has been lost or in bad condition

• Therefore no re-sampling or re-logging can be done • Coarse Rejects and pulps not retained • Missing Core logs (multiple reasons) • Assays missing, incomplete or suspicious • Missing Collar and survey information • Co-ordinate system problems: Soviet/Local/UTM • Core Recovery not recorded or too low • Inappropriate seam intersection angles and lack of orientated

core • Compatibility of mixed and old and new data • Limited SG/Density Data • Lack of Twin drilling of different drilling methods

“Data Quality Issues will influence Mineral Resource Classification”

Data Quality: Examples of Common Issues

11


“Geological and structural controls must be incorporated in 3D modeling”

CP must understand fully the geological and structural controls and ensure the modeling honors it



Model Validation





• Incorporate the geological and structural controls and complexity in the process

• Combine geological knowledge and analytical results during modelling

• Apply appropriate parameters for the boundary between mineralised and unmineralised with internal waste and whether hard/soft boundaries are appropriate

• Common sense approach and experience required….ask for another opinion

• Use of appropriate Geostats. • Ensure interpretations are not heavily influenced by need to

produce geometrically simple shapes for 2D estimation • 3D Continuity is essential! • An appreciation of likely method and sequence of mining

Geological & Mineralisation Modelling: Introduction

12




Model Validation





“Once errors have been introduced and not corrected, they remain to the Resource Statement”

CP must understand and ensure reduction where possible of the impact of error sources prior to finalizing geological models

Geological & Mineralisation Modelling: Introduction (Cont)

• Failure to recognise/interpret key structures such as faulting and folding.

• Incorrect correlation of borehole lithologies and coal seam intersections

• Poor or imprecise definition of mineralised envelopes and Hanging wall/footwall contacts

• Failure to recognise and define internal barren and poor quality horizons.

• Inconsistent/overly complicated geological logs without summary codes

• Excessive core loss or poor recoveries

13


“Deposits can get more complex with additional data, and show little geological/grade continuity”

CP must understand 3D Geological and Mineralization Continuity, which should influence the Mineral Resource Classification

• Complex Geology, Structures and Geometry. • Gradational or steep seam contacts • Lack of physical continuity of coal seams • Close fault spacing relative to sample spacing • Rapid fluctuations in coal qualities. • Ability to update geological models relatively easily when new

data is collected. • 2D Approach for Polygonal estimates and 3D sectional

interpretations • Displaying the data on Cross-sections and Plans. • 2D and 3D Geological and Grade continuity

• Build 3D computerised geological models



Model Validation





Geological & Mineralisation Modelling: Reliability of Models

14


“Estimation methodology is not an exact science or answer and must be tailored to deposit”

CP must ensure the most appropriate grade/quality estimation methodology and parameters have been selected and applied



Model Validation





• 2D or 3D methodology which is dependent on the complexity of the model

• Some of the Advantages of 2D methods: • Simple, clear methodology, • Consistent, repeatable and auditable approach • Easy to apply in simple geometry deposits

• Some of the Disadvantages of 2D methods: • Difficult to apply in Complex geometry/geology deposits • Unsuitable models for mine design and detailed mine planning • Cannot apply cut-off grade to separate economic areas

• Some of the Advantages of 3D methods: • 3D Spatial Continuity of the deposit geology and grade. • Provides an unbiased coal quality estimate • Allows the estimation of mining-scale blocks/panels, suitable

for mine design/planning • Cut-off grades and economic criteria can easily be applied

• Some of the Disadvantages of 3D methods: • Complex methodologies requiring many inputs and training • Scepticism as to reliability of results which are interpreted as

being “Black Box” • Tendency to smooth/smear qualities

Estimation Method Selection: Introduction

15


Block Faulting Modelling in a Complex Coal deposit.

Example of Block faulting modelling within a Structurally complex Coal Deposit.

16


Coal seam modelled with Reverse Faulting.

There is a distinct advantage to using 3D modelling in areas with multiple seams and complex faulting that allows multiple options to be evaluated quickly.

17


Complex cross sections based on a single borehole and no boreholes to verify faulted blocks.

Examples of poor quality cross section from a public report.

18


Example of cross sections of multiple seams with associated splits.

19


Validation of Models

“An un-validated model could be an invalid model”

CP responsibility to ensure the estimate is valid and represents adequately the sample data it is based upon


Mineral Resource Classification with Economic potential

Model Validation




Firm understanding of the Geology and controls of Mineralisation • Validation and checks should be undertaken on

all estimates regardless of estimation methodology or confidence

• Superimpose sample data coloured by qualities over the model/polygons and check

• Check visually that the model grade distributions match the expected/geological distributions

• Check visually for evidence of grade smoothing and smearing

• Statistical comparison of sample grades v model/polygon grades, and produce histograms

• Comparison using alternative methods: 2D v 3D. • Validation/ Plots of sample vs model qualities

20


“Classification = Confidence”

Classification is influenced by a number of factors which the CP must take into balanced consideration of confidence, using experience to determine the relative

materiality of each



Model Validation





• The CP must take a balanced judgement and assess the materiality of a number of different factors and there are no hard and fast prescriptive rules or exact degrees of confidence limits

• Currently too much emphasis placed on sample spacing, density and distribution

• Quality of data • Quantity/spacing of Data • Geological and Grade continuity • Quality of grade/panel/block estimates • Confidence with which a mining plan could be generated

from the resource model

A resource should be downgraded if there is evidence of poor quality data regardless of complexity, data spacing, methodology, etc.

Mineral Resource Classification: Considerations of the CP

21

© SRK Consulting (UK) Ltd 2015. All rights reserved. “Resource Classification should not just be based on Borehole Distance”

Resource classification based on borehole distance only.

Example of poor quality resource classification from a public report in Colombia The boreholes show no lateral extent with wide borehole spacing.

22

© SRK Consulting (UK) Ltd 2015. All rights reserved. “Combining the CP experience with the geological observations”

Generating a Resource Classification

First stage is to review the borehole density taking into account the number of cored and open holes.

Over the borehole density the structural, seismic and any mapping data is overlain.

23

© SRK Consulting (UK) Ltd 2015. All rights reserved. “Combining the CP experience with the geological observations”

Generating a Resource Classification (Cont.)

Finally the CP will review each area based on his knowledge of the deposit and similar styles of deposition to ensure the resource classification reflects the knowledge of the deposit.

24


“Mining considerations must be made even at the resource stage”

The variability and suitability of the resource model for generating a mine plan should be considered



Model Validation




Firm understanding of the Geology and controls of Mineralisation • The CP must consider how the estimate can be used in mine

planning • How does the model “break-up” when operating cut-off grades

are applied and do they form contiguous mineable areas? • A deposit must have “…reasonable prospect for eventual

economic extraction” according to JORC. • It is not acceptable to report just in-situ tonnage and grade

without economic/mining consideration • Must separate open-pit from underground • Calculation of an appropriate cut-off grade which represents

realistic technical parameters based on mining and processing methods with optimistic revenue parameters

Mineral Resource Classification: Mining Considerations and Economic Potential

25


“Clear Statement of Mineral Resource NOT to be confused with Exploration Potential”

A Mineral Resource Statement is NOT a mineral Inventory of all material, must be clear and unambiguous, must clearly state reporting parameters and economic criteria



Model Validation


Sample Data Coding, Statistics and Geostatistics



Firm understanding of the Geology and controls of Mineralisation • The CP is responsible for the statement

• Report in accordance with a CODE, disclaimers of “NON-compliance” are not acceptable

• Split per mineralisation type and mining method • Single statement at fixed reporting criteria, not multiple cut-off

grades • Clear, transparent statement • All major economic reporting criteria should be clearly stated • Split into confidence categories and sub-totalled appropriately

(Inferred separate) • Exploration Potential should be clearly stated separate from

Mineral Resource Statement

Mineral Resource Statements

26


Mineral Resource Statements and SRK.

• The ability to report within all the major international reporting codes (Jorc 2012, NI 43-101 and CRIRSCO)

• Geological models built in a range of computer software to meet clients requirements.

• Extensive experience in all the Major Coal Basins of the World.

• Mixture of technical excellence with practical experience from working in some of the largest opencast and underground operations in the world.

• Proven track record of completing projects on time and to a high technical excellence.

27


COPYRIGHT AND DISCLAIMER

Copyright (and any other applicable intellectual property rights) in this document and any accompanying data or models which are created by SRK Consulting (UK) Limited ("SRK") is reserved by SRK and is protected by international copyright and other laws. Copyright in any component parts of this document such as images is owned and reserved by the copyright owner so noted within this document. The use of this document is strictly subject to terms licensed by SRK to the named recipient or recipients of this document or persons to whom SRK has agreed that it may be transferred to (the “Recipients”). Unless otherwise agreed by SRK, this does not grant rights to any third party. This document shall only be distributed to any third party in full as provided by SRK and may not be reproduced or circulated in the public domain (in whole or in part) or in any edited, abridged or otherwise amended form unless expressly agreed by SRK. Any other copyright owner’s work may not be separated from this document, used or reproduced for any other purpose other than with this document in full as licensed by SRK. In the event that this document is disclosed or distributed to any third party, no such third party shall be entitled to place reliance upon any information, warranties or representations which may be contained within this document and the Recipients of this document shall indemnify SRK against all and any claims, losses and costs which may be incurred by SRK relating to such third parties. This document is issued subject to the confidentiality provisions in SRK’s Terms and Conditions, which are included in the Commercial Appendices and contain mutual confidentiality obligations. Accordingly, any references in the confidentiality provisions in SRK’s Terms and Conditions to the “Client” should be read as “Recipients”. SRK respects the general confidentiality of its potential clients’ confidential information whether formally agreed with them or not and SRK therefore expects the contents of this document to be treated as confidential by the Recipients. The Recipients may not release the technical and pricing information contained in this document or any other documents submitted by SRK to the Recipients, or otherwise make it or them available to any third party without the express written consent of SRK. © SRK Consulting (UK) Limited 2015 version: Jan 2015

Slide Number 1Slide Number 2SRK Project Experience in Kazakhstan and the Russian Federation.A Resource Statement is a Fundamental Requirement for Public Reporting.Generic Workflow For a Mineral Resource EstimateSlide Number 6Slide Number 7Slide Number 8Slide Number 9Slide Number 10Slide Number 11Slide Number 12Slide Number 13Slide Number 14Slide Number 15Slide Number 16Slide Number 17Slide Number 18Validation of Models�Slide Number 20Slide Number 21Slide Number 22Slide Number 23Slide Number 24Slide Number 25Mineral Resource Statements and SRK.�Slide Number 27

Best Practices in the Generation of a Coal Resource Estimate. · Minex Central Asia 2015, Astana, Kazakhstan. Photo insets: Cerrejon open pit mine, Typical Underground Longwall equipment

Documents