Slide 1: Indirect Distributions of Selective Mining Units for Recoverable Mineral Resources at Tarkwa
The use of Indirect Distributions of Selective Mining Units for Assessment of Recoverable Mineral Resources Designed for Mine Planning at Gold Fields Tarkwa Mine, Ghana August 2015 Winfred Assibey-Bonsu John Searra Matthew Aboagye 1
Slide 2: Content
Content • Introduction • Indirect Approach • Case Study – Tarkwa Gold Mine – Geology – SMUs – Estimation – Kriging Efficiencies vs Regression Slopes – Post-processing • Conclusions 2
Slide 3: Introduction
Introduction • At the exploration stage kriged estimates with a proper search routine will be conditionally unbiased, but will unavoidably be smooth because of the level of data available. • The smooth estimates will generally overstate the tonnage above economic cut-off and underestimate the corres
Slide 4: Introduction
Introduction • Various post-processing techniques have been proposed to correct for the smoothing effect where data is widely spaced and sparse: – Spectral-processor(Journel et all 2000) – Sequential Gaussain Conditional simulations (Deutsh and Journel, 1992) – Indirect post-processing (Assibey-Bons
Slide 5: Introduction
Introduction • Regardless of the theoretical soundness, from a practical point of view, actual follow-up comparisons are absolutely essential. • It should be realised that whatever post-processed technique is used, the result will depend on the efficiency of the technique and parameters used in the
Slide 6: Indirect Approach
Let us define: L = Large planning block S = Selective mining unit (SMU) of interest P = Entire population or global area being estimated B(§/_) = Variance of actual SMU grades within large planning blocks BV; = Variance of actual SMU grades within P BV. = Variance of large planning block grades with
Slide 7: Indirect Approach
Indirect Approach From Krige’s relationship; Variances of actual SMU grades: BVs= B(S/L) + BVL That is, B(s/.) = BVs - BV Dispersion variances of conditionally unbiased estimates within P for L (“D(‘/p)”) D(Yp) = BVL- oLe1 (at exploration stage). (1) =Bv_-0 (at final production stage) Similarly, dis
Slide 8: Indirect Approach
Indirect Approach • In all cases, the large panels must be conditionally unbiased and are adjusted accordingly (as per above) to reflect the average grade improvements and tonnage reductions expected on the basis of the additional information that will become available at the later production stage.
Slide 9: Case Study – Tarkwa Gold Mine, Ghana
Case Study – Tarkwa Gold Mine, Ghana • The Gold Fields’ Tarkwa operation exploits narrow auriferous conglomerates, similar to those mined in the Witwatersrand Basin of South Africa and currently mines from four open pits – Pepe- Mantraim, Teberebie, Akontansi and Kottraverchy. 9
Slide 10: Geology
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Slide 11: Geology
Geology • The Banket Series, which hosts the Tarkwa ore body, varies in thickness from 32m in the east at Pepe, up to 270 m in the west at Kottraverchy. • Sedimentological studies of detailed stratigraphy within individual footwall reef units have led to the recognition of both lateral and vertical
Slide 12: Geology
KOTTRAVERCHY AKONTANSI RIDGE AKONTANS! EAST TEBEREBIE - aw 6 ee Fe Fs fr F3 fir = ‘ = Cae AL CDE oY ONSULTING 12
Slide 13: SMU
SMU • Selective Mining Units – All Selective Mining Unit (SMU) sizes are as defined according to possible equipment, mining method, mining selectivity, together with the geology of the orebody. At Tarkwa, the SMU size is 10m x 5m x 3m with an assumed RC grade control drilling grid of 25m x 25m. Duri
Slide 14: Estimation
Estimation • Both Ordinary Kriging (OK) and Simple Kriging (SK) techniques are applied in developing the panel (50mx50mx3m) resource estimation grade models. SK used for post-processing. • The simple kriging process uses a local or “global” (Domain) mean in the kriging process depending on availabil
Slide 15: Analysis of Kriging Efficiency and Slope of Regression
Analysis of Kriging Efficiency and Slope of Regression • Kriging efficiency can be negative if KV>BV – It should be noted that unlike ordinary kriging, the minimum kriging efficiency under simple kriging is zero. • Regression Slope = (BV – KV + |LM|)/(BV-KV + 2|LM|) …(3) – In order to avoid negative
Slide 16: Analysis of Kriging Efficiency and Slope of Regression
Analysis of Kriging Efficiency and Slope of Regression • Thus, a regression slope less than 0.5 will always lead to a negative block kriging efficiency estimate. This highlights the danger of accepting block estimates which have slope of regression less than 0.5. • The critical regression slope limi
Slide 17: Typical OK Efficiencies and Slope of Regression – Tarkwa Gold Mine
Typical OK Efficiencies and Slope of Regression – Tarkwa Gold Mine 17
Slide 18: Typical OK Efficiencies and Slope of Regression – Tarkwa Gold Mine
Typical OK Efficiencies and Slope of Regression – Tarkwa Gold Mine • These significant conditional biases as observed with the OK estimates, particularly in areas with limited data have adverse consequences on ore and waste selection for mine planning, as well as financial planning. • As a result, r
Slide 19: Post-Processing – Indirect Approach
Post-Processing – Indirect Approach • The parent kriged blocks/panel (50mx50mx3m) are subjected to post-processing as per the indirect recoverable resource methodology • The methodology incorporates the information effect and change of support correction for the relevant Selective Mining Units (“SMU
Slide 20: Comparison of Resource and Grade Control Models
Comparison of Resource and Grade Control Models • The table shows good in-situ reconciliation of the resource model, which is based on the SK indirect post-processing technique, when compared to the grade control models. Reef Tonnes Grade (%) (%) A -0.70% -1.02% C -0.15% 3.30% E 3.88% 1.27% F2 2.10%
Slide 21: Reconciliation of Grade Control with Production
Reconciliation of Grade Control with Production • There is a good reconciliation between grade control and production. • As the Resource models and the grade control models reconcile well, it shows that a good reconciliation exists between the proportional post-processed recoverable resources estima
Slide 22: Grade Control vs production - Tonnes
Grade Control vs production - Tonnes 22
Slide 23: Grade Control vs production - Grade
Grade Control vs production - Grade 23
Slide 24: Conclusions
Conclusions • The study shows that appropriate application of indirect post- processing technique provides efficient recoverable resource estimates for mine planning and financial forecast. • The study further shows that it is critical that the conditioning panel estimates used for the post-processi
Slide 25: END
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