Maiden Iron Ore Resource at Mt Finnerty
December 15, 2009
Highlights
A maiden JORC Code compliant resource (Inferred) of 4.66 Mt (average grade 53.5% Fe) has been delineated at the Mt Finnerty iron ore project in Western Australia.
The resource contains significantly low levels of phosphorous and sulphur.
The Inferred resources at the Mt Finnerty prospects have provided sufficient encouragement to progress exploration of other targets, including some identified from a recent geophysical review
Mt Finnerty is held under a JV agreement with Cliffs Asia Pacific Iron Ore Pty Ltd holding 80% and Reed Resources Limited holding the remaining 20%.
Australian diversified resources company Reed Resources Ltd (ASX: RDR) (the “Company” or “Reed”) has, together with Joint Venture partner Cliffs Asia Pacific Iron Ore Pty Ltd (“Cliffs”), delineated a maiden JORC Code compliant resource at the Mt Finnerty project in Western Australian that gives sufficient encouragement to progress exploration of other targets at the project.
The Mt Finnerty iron ore project (Figure 1) is located 65 km east of the Koolyanobbing town and mine sites operated by Cliffs Natural Resources. Cliffs have earned an 80% interest in the iron rights at Mt Finnerty, with the remaining 20% stake held by Reed.
The combined Inferred Mineral Resources at the FIN9 and FIN10 prospects is 4.66 Mt at an average grade of 53.5% Fe, for a lower cut-off grade of 50% Fe, and with significantly low levels of phosphorous (P) and sulphur (S).
Cliffs have also completed a full geophysical review of the Mt Finnerty JV project, which has identified several new iron ore targets currently being assessed through field inspections.
Reported tonnes and grades of Minerals Resources at each of the prospects are listed in the following table at lower cut-off grades of 50% Fe and 58% Fe (details of Resource estimation is provided in Appendix):
| Prospect | Cut-off grade (% Fe) |
Tonnes (‘000) |
Fe % |
SiO2 % |
Al2O3 % |
P % |
S % |
Mn % |
LOI % |
|---|---|---|---|---|---|---|---|---|---|
| FIN9 | 50 | 2580 | 54.1 | 9.4 | 3.8 | 0.10 | 0.17 | 0.43 | 7.9 |
| 58 | 30 | 58.2 | 4.8 | 3.1 | 0.11 | 0.16 | 0.15 | 7.7 | |
| FIN10 | 50 | 2080 | 52.9 | 9.9 | 5.3 | 0.06 | 0.12 | 0.07 | 8.3 |
| 58 | 110 | 58.4 | 5.0 | 3.7 | 0.06 | 0.15 | 0.03 | 7.2 |
Resource tonnage and grade estimates comply with the JORC Code (2004) and are all assigned to the Inferred Resource category (Appendix).
Resources at each prospect are for goethitic mineralisation in supergene-enriched banded iron formation (BIF). The predominance of goethite is reflected by the relatively high LOI (loss on ignition) content of the resources. The resource at FIN10 is more complex than FIN9 with indications of hematite mineralisation.
The FIN9 resource is based on 34 Reverse Circulation (RC) drill holes and the FIN10 resource is based on 36 RC drill holes, both prospects drilled on a nominal 50m by 100m grid pattern.
The grade estimation model for FIN9 extends 700 metres along the north-northwest strike of the mineralisation over 10 to 50 metres in thickness and to a depth of up to 70 metres below surface. The FIN10 resource model extends for 800 metres along the north-northwest strike over a similar thickness and to a depth of up to 60 metres below surface.
Additional RC drilling at the FIN11 prospect (10 holes, 1269m) has indicated iron mineralisation (>50% Fe) is in narrow zones of shallow surface enrichment and does not warrant a Resource estimation at this stage.
Forward work program
The Inferred resources at the FIN9 and FIN10 prospects have provided Cliffs with sufficient encouragement to progress exploration of other targets, including some of those identified from the recent geophysical review. The initial target continues to be iron mineralisation comparable in size to the Carina deposit along strike to the north of the Mt Finnerty project.
Competent Person Statement
Geological aspects of this report that relate to exploration results have been compiled by Dr Peter Collins (MAIG), a Director of Reed Resources Ltd. Dr Collins has sufficient experience relevant to the style of mineralization and type of deposit under consideration and to the activity which is being reported on to qualify as a Competent Person as defined in the Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (2004). Dr Collins consents to the inclusion in this report to matters in the form and context in which it appears.
Mineral Resource estimation has been compiled in accordance with the guidelines outlined in the Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (JORC Code, 2004) by Leonora Hackman and Duncan Hackman of Hackman and Associates Pty Ltd. Leonora Hackman is a member of the Australasian Institute of Mining and Metallurgy and Duncan Hackman is a member of the Australian Institute of Geoscientists. Both have sufficient experience relevant to the style of mineralization and type of deposit under consideration and to the activity undertaken to qualify as Competent Persons as defined in the 2004 Edition of the Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves. Leonora Hackman and Duncan Hackman consent to the inclusion of the Mineral Resource estimations in the form and context in which it appears.
Although Reed remains optimistic about the potential of the Mt Finnerty project, any reference to the terms “ore” and “high-grade” in this report is conceptual in nature. Use of the term “grade(s)” is not intended to represent the grade of a Reserve.
Appendix: FIN9 and FIN10 Mineral Resource Estimation Parameters
Mineral Resource estimation has been compiled in accordance with the guidelines outlined in the Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (JORC Code, 2004) by Hackman and Associates Pty Ltd for Cliffs Asia Pacific Iron Ore Pty Ltd.
The resource model is based on a database and geological and mineralisation interpretation by Cliffs Natural Resources Pty Ltd (CNR), and TIN modelling Hackman and Associates Pty Ltd (H&A). Block model construction and grade estimation were undertaken by Duncan Hackman, in consultation with Leonora Hackman of H&A.
The FIN9 resource estimate is based on 1909 two-metre composite sample data from 34 Reverse Circulation (RC) drill holes on a nominal 50m by 100m grid pattern. 179 composites are located within the interpreted goethite mineralised domain and form the basis of the grade estimate. The grade estimation model extends 700m along the north-northwest strike of the mineralisation and full thickness of the interpreted mineralised domain (ranges between 10m and 50m in thickness).
The FIN10 resource estimate is based on 1751 two-metre composite sample data from 36 RC drill holes on a nominal 50m by 100m grid pattern. 185 composites are located within the interpreted goethite mineralised domain and form the basis of the grade estimate. The grade estimation model extends 800m along the northerly strike of the mineralisation and full thickness of the interpreted mineralised domain (ranges between 10m and 50m in thickness).
Analytical quality control data shows that the assay data is suitable for use in the resource estimates and that there are no limiting factors for consideration when classifying the resources under the JORC Code (2004). The inverse distance squared (ID2) estimation method was employed for grade interpolation. Composite and block grades reconcile adequately for the estimate to be considered robust at a global scale. Tonnage factors of 3.00 g/cc (Fe grade <58 %) and 3.35 g/cc (Fe grade >/=58%) were used for the estimation model.
Classification of the resource is based on data density, data quality, confidence in the geological interpretation and confidence in the estimation. Key factors considered in assigning an Inferred Resource classification under the JORC Code (2004) guidelines include confidence in geological and grade continuity (and extents) due to the underlying drilling configuration and method (RC), which impinge on logging reliability underpinning structural and geological interpretations; reliability of and method of applying the tonnage factors; and perceived low confidence in local estimates caused by the above factors and the interpolation parameters utilised in estimating grades from this data. The standard of input data and information is sufficient to classify the resource at the level of an Inferred category.
