Technical Report on the Ilgin Coal Project

Mineral Development, Exploration and Resources and Pit Design and Production Planning

Prepared as a Course Project Report for:

Mine Planning with the Aid of Computer

Bilgisayar Dest. Maden Planl. MAD 502

Date of Report:

14th

May, 2015

Prepared by:

Mohammad Lashgari

505141014

Advisor:

Dr. Prof. Selamet Gürbüz Erçelebi

Institute:

Istanbul Technical University (ITU)

Science Eng. & Tech.

Mining Engineering

TABLE OF CONTENTS

1. SUMMARY ........................................................................................................................... 1

1.1 INTRODUCTION .................................................................................................................... 1

1.2 PROPERTY DESCRIPTION ...................................................................................................... 1

1.3 PROPERTY LOCATION .......................................................................................................... 2

1.4 LOCAL GEOLOGY AND MINERALISATION ............................................................................ 3

1.5 EXPLORATION CONCEPT ...................................................................................................... 6

1.6 EXPLOITATION CONCEPT ..................................................................................................... 6

1.7 CONCLUSIONS ...................................................................................................................... 6

2. DRILLING ............................................................................................................................ 7

3. DATA ANALYSIS ................................................................................................................ 9

3.1 TOPOGRAPHY DATA............................................................................................................. 9

3.2 GEOLOGY DATA .................................................................................................................. 9

3.3 ORE DATA ......................................................................................................................... 10

3.4 REGRESSION ANALYSIS ..................................................................................................... 18

4. MINERAL RESOURCE AND ESTIMAZTIONS .......................................................... 19

4.1 RESOURCE REPORTING CODE AND CATEGORIZATION ......................................................... 19

4.2 KEY ESTIMATION ASSUMPTIONS AND PARAMETERS ........................................................... 20

4.3 DETAILS OF COAL RESOURCE ............................................................................................ 20

4.4 INFERRED RESOURCE ......................................................................................................... 20

4.5 INDICATED RESOURCE ....................................................................................................... 22

5. BLOCK MODELLING ...................................................................................................... 25

5.1 BLOCK DEFINITION ............................................................................................................ 25

5.2 KRIGING ............................................................................................................................. 25

5.3 ESTIMATION REPORTS ....................................................................................................... 30

5.4 CORRELATION OF ORE PARAMETERS .................................................................................. 33

6. MINING METHOD SELECTION ................................................................................... 37

6.1 INTRODUCTION .................................................................................................................. 37

6.2 DEVELOPMENT................................................................................................................... 38

6.3 COST COMPARISONS .......................................................................................................... 39

6.4 SELECTION OF A MINING METHOD .................................................................................... 40

6.5 SELECTED PROJECT MINING METHOD ............................................................................... 41

7. MINING METHOD ELEMENTS .................................................................................... 42

7.1 MINING OPERATIONS ......................................................................................................... 42

7.2 MINE DESIGN ..................................................................................................................... 42

7.3 PRODUCTION SCHEDULE .................................................................................................... 43

7.4 COAL RESERVE RECOVERY................................................................................................ 50

7.5 COAL QUALITY EXTRACTED .............................................................................................. 50

7.6 WASTE ROCK ..................................................................................................................... 51

7.7 STRIP RATIO ...................................................................................................................... 51

7.8 MINE EQUIPMENT .............................................................................................................. 51

8. CONCLUSION AND RECOMMENDATIONS .............................................................. 53

9. REFRENCES ...................................................................................................................... 54

TABLE OF FIGURES

FIGURE 1.GENERAL LOCATION OF ILGIN REGION COALFIELDS......................................................... 2

FIGURE 2. LOCATION MAP OF KONYA REGION COALFIELDS. (A.I. KARAYIGITAND ET AL 1998) ...... 4

FIGURE 3. SCHEMATIC STRATIGRAPHIC SECTION OF THE ÇAVUSÇU COALFIELD. .............................. 5

FIGURE 4: DRILLING PATTERN ......................................................................................................... 7

FIGURE 5: DRILLING PATTERN ON THE EARTH .................................................................................. 8

FIGURE 6: VISUALIZATION OF GEOLOGY LOGGING OF DRILL HOLES IN MICROMINE SOFTWARE ...... 8

FIGURE 7: BORE HOLE COLLARS ON TOPOGRAPHY ........................................................................... 8

FIGURE 8: CALORIFIC VALUE NORMAL HISTOGRAM ..................................................................... 10

FIGURE 9: CALORIFIC VALUE SEMIVARIOGERAM .......................................................................... 11

FIGURE 10: CALORIFIC VALUE CROSS-VALIDATION DIAGRAM DUE TO SEMIVARIOGRAM MODEL 11

FIGURE 11: ASH CONTENT NORMAL HISTOGRAM.......................................................................... 12

FIGURE 12: ASH CONTENT LOG-NORMAL HISTOGRAM ................................................................. 12

FIGURE 13: ASH CONTENT LOG-NORMAL VALUE SEMIVARIOGERAM ........................................... 13

FIGURE 14: ASH CONTENT CROSS-VALIDATION DIAGRAM DUE TO SEMIVARIOGRAM MODEL ..... 13

FIGURE 15: MOISTURE NORMAL HISTOGRAM ................................................................................ 14

FIGURE 16: MOISTURE SEMIVARIOGERAM ..................................................................................... 15

FIGURE 17: MOISTURE CROSS-VALIDATION DIAGRAM DUE TO SEMIVARIOGRAM MODEL ........... 15

FIGURE 18: SULPHUR NORMAL HISTOGRAM .................................................................................. 16

FIGURE 19: SULPHUR SEMIVARIOGERAM ....................................................................................... 17

FIGURE 20: SULPHUR CROSS-VALIDATION DIAGRAM DUE TO SEMIVARIOGRAM MODEL ............. 17

FIGURE 21: CROSS SECTION DRAWN IN MICROMINE ...................................................................... 21

FIGURE 22: DRILL HOLES AND DRAWN POLYGONS PLAN. ............................................................... 21

FIGURE23: WIREFRAME OF COAL SEAM BUILT THROUGH SECTIONS ............................................... 22

FIGURE 24: COAL SEAM BORDER.................................................................................................... 23

FIGURE25: COAL SEAM BORDER ON THE TOPOGRAPHY .................................................................. 23

FIGURE26: COAL SEAM WIREFRAME CREATED BY GRIDDING ......................................................... 24

FIGURE 27: THE COAL SEAM LOCATION IS SHOWN DUE TO TOPOGRAPHY. ...................................... 24

FIGURE 28: BLOCK MODELING VISUALIZATION BY MICROMINE SOFTWARE. ................................. 25

FIGURE 28: SEARCH ELLIPSOID ...................................................................................................... 26

FIGURE 29: CV MAP FOR THE COAL (KJ.KG-1

) ................................................................................ 27

FIGURE 30: ASH CONTENT OF COAL (%) ........................................................................................ 27

FIGURE 31: MOISTURE CONTENT OF COAL (%) .............................................................................. 28

FIGURE 32: THICHNESS OF COAL SEAM (M) .................................................................................... 28

FIGURE 33: SULPHUR CONTENT OF COAL SEAM (%) ...................................................................... 29

FIGURE 34: COAL ROOF ELEVATION (FROM SEA LEVEL, M) ............................................................ 29

FIGURE 35:CV DİSTRİBUTİON DUE TO ELEVATİON ......................................................................... 35

FIGURE 36:ASH DİSTRİBUTİON DUE TO ELEVATİON ....................................................................... 36

FIGURE 37:MOİSTURE DİSTRİBUTİON DUE TO ELEVATİON ............................................................. 36

FIGURE 38: ESTIMATED CAPITAL COSTS FOR SURFACE MINES AT FOUR STRIPPING RATIOS ............. 39

FIGURE 39: ESTIMATED CAPITAL COSTS FOR SIX TYPES OF UNDERGROUND MINES, ALL WITH SHAFT

ACCESS ................................................................................................................................... 39

FIGURE41: ESTIMATED OPERATING COSTS FOR SIX TYPES OF UNDERGROUND MINES, ALL WITH

SHAFT ACCESS ........................................................................................................................ 39

FIGURE 42: SCHEMATIC GEOMETRY OF A WORKING BENCH ........................................................... 43

FIGURE 43: 1ST

YEAR PIT ................................................................................................................ 44

FIGURE 44: 2ND

YEAR PIT ................................................................................................................ 45

FIGURE 45: 3RD

YEAR PIT ................................................................................................................ 46

FIGURE 46: 4TH YEAR PIT ............................................................................................................... 47

FIGURE 47: 5TH YEAR PIT ............................................................................................................... 48

FIGURE 48: FINAL PIT ..................................................................................................................... 49

LIST OF TABLES

TABLE1: STATISTICAL SUMMARY OF CALORIFIC VALUES OF COAL SAMPLES ............................... 10

TABLE 2: STATISTICAL SUMMARY OF ASH CONTENT OF COAL SAMPLES ...................................... 12

TABLE 3: STATISTICAL SUMMARY OF MOISTURE CONTENT OF COAL SAMPLES ............................ 14

TABLE 4: STATISTICAL SUMMARY OF SULPHUR CONTENT OF COAL SAMPLES .............................. 16

TABLE 5: STATISTICAL SUMMARY OF THICKNESS OF COAL SAMPLES ........................................... 18

TABLE 6: TOTAL ORE RESERVE ..................................................................................................... 30

TABLE 7: CALORIFIC-MASS DISTRIBUTION .................................................................................... 31

TABLE 8: ASH-MASS DISTRIBUTION............................................................................................... 31

TABLE 9: MOISTURE-MASS DISTRIBUTION..................................................................................... 32

TABLE 10: SULPHUR-MASS DISTRIBUTION ..................................................................................... 32

TABLE 11: LIGNITE THICKNESS-CV RESERVE DISTRIBUTION ........................................................ 33

TABLE 12: LIGNITE ASH AND MOISTURE CONTENT DUE TO CV INTERVALS .................................. 33

TABLE 13: LIGNITE ASH AND MOISTURE CONTENT AND CV DUE TO ELEVATION INTERVALS........ 34

TABLE 14: ILGIN LOM MINING SCHEDULE ................................................................................... 43

TABLE 15: WASTE AND COAL EXTRACTED IN THE 1ST

YEAR ......................................................... 44

TABLE 16: WASTE AND COAL EXTRACTED IN THE 2ND

YEAR ......................................................... 45

TABLE 17: WASTE AND COAL EXTRACTED IN THE 3RD

YEAR ......................................................... 46

TABLE 18: WASTE AND COAL EXTRACTED IN THE 4TH YEAR ........................................................ 47

TABLE 19: WASTE AND COAL EXTRACTED IN THE 5TH YEAR ........................................................ 48

TABLE 20: WASTE AND COAL EXTRACTED IN TOTAL LOM .......................................................... 49

TABLE 21: RESERVE RECOVERY OF ILGIN PIT................................................................................ 50

TABLE 22: ANNUAL EXTRACTED COAL PROPERTIES ..................................................................... 50

TABLE 23: YEARLY GAINED TOTAL CALORIE ............................................................................... 50

TABLE 24: STRIP RATIO DURING LOM .......................................................................................... 51

TABLE 25: ILGIN MINE EQUIPMENT ............................................................................................... 51

1

1. SUMMARY

1.1 Introduction

This technical report is course project for the MAD 502 Bilgisayar Dest. Maden Planl. Course

under the supervision of Dr. Prof. Selamet Gürbüz Erçelebi . This document has been prepared

by Mohammad Lashgari during educating Master of Science in Mining Engineering. Additional

informations, where warranted and deemed necessary, has been included in the report.

Turkey currently has about 8.4 Gt. Of lignite reserves -and most were formed in intermontane

basins (for example, in Soma, Cayirhan)(A.I. Karayigitand et al 1998) -, of which 3.9 Gt. are

exploitable. Most of the known lignite deposits in Turkey have low calorific valuesand high ash,

moisture, and total sulphur contents. Almost 80% of the total reserves have calorific values

below10.46 MJ . kg–1

. The lignites having calorific values lower than 10.46 MJ . kg–1

are

generally consumed in power plants, while those having calorific values higher than 10.46 MJ .

kg–1

are directed towards household and industrial uses. The majority of Turkish lignite deposits

are worked as open-pit mines, though there are also some underground operations. Miocene,

Pliocene, and Quaternary coals are formed in limnic and limnic fluvial environments with some

volcanogenic intercalations. The total extent of the coal-bearing Miocene (835.1 km2) and

Pliocene (526.9 km2) deposits is 1,362 km

2 (Tuncali et al. 2002).

1.2 Property Description

The Ilgin Coal Project is a moderate coal resource, largely opencastable, partly underlying

predominantly farming land, and elsewhere has historically supported mining operations

supplying coal to the local industry. The project area lies in the the Ilgin lignite field which

can be subdivided into the Haramiko¨y and Kurugo¨l areas which are separated by an area of

basement and a fault. The lignite-bearing sequence consists mainly offluvial and lacustrine

Neogene deposits, (A.I. Karayigitand et al 1998) the surrounding areas have supported a

number of mining operations, both historically and currently.

2

1.3 Property Location

The lignite potential of the Konya region, whose coals have low calorific values and high

moisture contents, can contribute to Turkey’s energy requirements (Fig. 1). (Inaner and

Nakoman1997).The has a small proportion of low-rank lignite reserves containing 22 Mt of

technically recoverable lignite. The lignite field can be subdivided into the Haramikoy and

Kurugo areas, which are separated by an area of basement outcrop and a fault _Fig. 2. It is

believed that no significant difference in palaeodepositional environment exists between the two

areas. Annual lignite production of the open-pit mine in the Haramikoy area is about 400 000 t,

whereas that of Kurugol is in the exploration stage (A.I. Karayigitand et al 1998) and is this

report the exploration results is being processed.

Figure 1.General Location of Ilgin region coalfields

3

1.4 Local Geology and Mineralisation

The Ilgin lignite field consists mainly of fluvial and lacustrine sediments (Ilgin Formation). of

Neogene age, that were deposited unconformably onto a basement which includes Palaeozoic

metamorphic rocks (Sizma Formation) and Mesozoic crystalline limestones (Loras Formation).

(Fig. 2. The Sizma Formation contains low grade metamorphic rocks including phyllite, sericite

schist and quartzite) (Caglar and Ayhan, 1991; Erol and Tufekci, 1993.)

The Ilgin Formation has been subdivided into three members, from the oldest to the youngest,

the Tekeler, Harmanyazi and Sebiller Members (Fig. 2). The Tekeler Member, with an average

thickness of 50 m, generally consists of red and brown fluvialsediments. These sediments grade

upward into the lignite-bearing Harmanyazi Member. A lignite seam occurs at the base of the

lacustrine sequence of the Harmanyazi Memberwhich mainly consists of whitish marls up to 180

m thick. Other lithologies includepoorly laminated yellow, grey and white claystone, clayey

limestone, siltstone and tuffite. The fauna includes gastropods (Planorbidae) and ostracods. X-

ray diffraction analysis of samples of this member indicate mainly calcite, dolomite, aragonite,

quartzand clay minerals (Tunoglu and Celik, 1995). The clay fraction consists mainly of

smectite, kaolinite, illite and pyrophyllite from reworking of the metamorphic rocks. The Sebiller

Member is composed of red–brown fluvial sediments (Caglar and Ayhan, 1991). Both the

basement and the Ilgin Formation have been covered by unconsolidated Quaternary sediments

composed of clay, silt, sand and gravel, that have a widespreaddistribution, especially in the

Kurugo¨l area (Fig. 2). The lignite seam in the open-pitmine has 50% bed moisture content, 11%

ash yield and 9.37 MJ kg-1

(2239 kcal kg-1

) net calorific value on an as-received basis (Gokmen et

al., 1993)- (A.I. Karayigitand et al 1998).

4

Figure 2. Location map of Konya region coalfields. (A.I. K arayigitand et al 1998)

5

Figure 3. Schematic strat igraphic section of the Çavusçu coalfield.

6

1.5 Exploration Concept

Exploration is carried out using 218 vertical diamond drilled fully cored boreholes . The cores

are logged and laboratory tests had been done for each samples and nearly 243000 points has

been read in surveying operation.

1.6 Exploitation Concept

Ilgin Coal Project pit design is based on approximately 4 million tonnes annually, starting from

the most shallow part (North Western part of the reserve.

1.7 Conclusions

A Gross In Situ Coal Resource of 181.6 Mt in which the mean values Calorific Value (CV), Ash

Content, Sulphur and Moisture are respectively 2115 kCal.kg-1

,15.1%,1.73% and 48.7% has

been estimated for the combined economic coal seam within the area of interest.

Due to what estimated in the exploration step some pits are designed in order to extract coal in

which the total coal recovery is 99.9% and mean values for CV, Ash, Sulphur and Moisture,

2114 kCal.kg-1

, 15.3%, 1.74% and 48.5% respectively.

A number of strategic decisions have been made which are going to be explained through this

report.

7

2. DRILLING

Extensive drilling has taken place and the collar coordinates has been surveyed covering

approximately 30 (km)2 of exploration area. Apparently there has not been a square drilling

pattern and as the geology logging of samples shows drilling pattern had been defined by results

of previous borehole. In total 218 boreholes have been drilled during 35 years (from 1977-2011)

of which 158 boreholes cut coal. The figure 4 shows the drilling points on the interested area and

the red points show the boreholes which did not cut any coal.

Figure 4: Drilling pattern

The average for borehole depth is approximately 159m and the maximum and minimum depth

are respectively 486m and 13.9m.

For core samples logging has been done and the lithology information has been gathered in an

Excel file. Drill holes which cut coal show that the average thickness for coal is 13.36m and the

maximum and minimum are respectively 45.4m and 0.4m.

8

Figure 5: Drilling pattern on the earth

Figure 6: Visualization of geology logging of drill holes in Micromine Software

Figure 7: Bore hole collars on topography

9

3. DATA ANALYSIS

Whole available data was collected in three Excel files; topography and geology which contained

surveying points and lithological data, respectively and the third file was collar which included

borehole collar coordinates, depth of bore hole, coal total thickness in bore holes cutting ore,

moisture, ash content, calorific value and Sulphur as main parameters.

Geostatistics is a branch of statistics concerned with analysis of not only data values but also the

positions of data samples and time-related data variations. Although originally devel-oped in the

mining industry, it is now widely applied in a range of disciplines.

The basic principles of geostatistics involve summary statistics, variance, variograms, and

kriging.

Normal analysis of any geological data usually starts with the production of summary statistics to

provide an initial view of the data ranges and distributions. Summary statistics include not only

the mean, standard deviation, variance, median, and mode, but also the coefficient of variation

(standard deviation/mean) and log estimates of the mean. Graphical analysis usu-ally includes

histograms, log histograms, and log probability plots that enable analysis of whether different

populations are present and whether some sort of domaining is necessary.

In comparisons of a large number of sample pairs, some differences are positive and some are

negative. Squaring these differences gives a new set of all-positive values. Differences measured

between samples separated by similar distances can then be averaged, giving a variance. A

graph called a variogram can be developed of variance versus distance of separation (lag)

between points. Figures 4.4-1 shows a sample variogram (strictly it should be called

semivariogram, as it is the variance/2), fitted with a spherical model variogram. The distance at

which the variogram levels off is called the range of influence; samples separated by more than

this distance are uncorrelated.

3.1 Topography Data

This files contains 243029 surveyed points with 3 dimensional coordinates covering the hole

probable exploration and mining area and also the lands which may be considered during mine

planning and excavations.

3.2 Geology Data

This file contains lithological data and depht of uccorance for each llithological set.

10

3.3 Ore Data

In this file which named “collar” all the quality and geometry of coal content of boreholes are

collected. Among 158 bore holes which cut coal 105 of them are analyzed and principal

properties of coal samples are measured. The statistical summary of these data are as follow;

a) Calorific Value Data

Table1: Statistical Summary of Calorific Values of Coal Samples

Calorie

Mean 1978.607524

Standard Error 37.5476869

Median 2025.87

Mode 2100

Standard Deviation 384.7492991

Sample Variance 148032.0231

Kurtosis 0.298794765

Skewness -0.668011078

Range 1884.84

Minimum 825.16

Maximum 2710

Sum 207753.79

Count 105

Confidence Level(95.0%) 74.45847216

Figure 8: Calorific Value Normal Histogram

11

Figure 9: Calorific Value Semivariogeram

Figure 10: Calorific Value Cross -Validation Diagram Due to Semivariogram Model

12

b) Ash Content

Table 2: Statistical Summary of Ash Content of Coal Samples

Ash

Mean 17.53371429

Standard Error 0.883464037

Median 14.91

Mode 14

Standard Deviation 9.052812489

Sample Variance 81.95341396

Kurtosis 2.024917698

Skewness 1.525120892

Range 42.7

Minimum 7.53

Maximum 50.23

Sum 1841.04

Count 105

Confidence Level(95.0%) 1.751942338

Figure 11: Ash Content Normal Histogram

Figure 12: Ash Content Log-Normal

Histogram

So the natural logarithmic transformed values are used for ash data.

13

Figure 13: Ash Content Log-Normal Value Semivariogeram

Figure 14: Ash Content Cross-Validation Diagram Due to Semivariogram Model

14

c) Moisture

Table 3: Statistical Summary of Moisture Content of Coal Samples

Moisture

Mean 46.66438095

Standard Error 0.636769461

Median 48.33

Mode 45

Standard Deviation 6.524945317

Sample Variance 42.57491139

Kurtosis 3.338017752

Skewness -1.591895225

Range 37.46

Minimum 18.48

Maximum 55.94

Sum 4899.76

Count 105

Confidence Level(95.0%) 1.262737737

Figure 15: Moisture Normal Histogram

15

Figure 16: Moisture Semivariogeram

Figure 17: Moisture Cross-Validation Diagram Due to Semivariogram Model

16

d) Sulphur

Table 4: Statistical Summary of Sulphur Content of Coal Samples

Sulphur

Mean 1.728333333

Standard Error 0.164452193

Median 1.435

Mode 1.42

Standard Deviation 0.986713158

Sample Variance 0.973602857

Kurtosis 5.837931516

Skewness 2.194677618

Range 5.02

Minimum 0.51

Maximum 5.53

Sum 62.22

Count 36

Confidence Level(95.0%) 0.333855701

Figure 18: Sulphur Normal Histogram

17

Figure 19: Sulphur Semivariogeram

Figure 20: Sulphur Cross-Validation Diagram Due to Semivariogram Model

18

e) Thickness

Table 5: Statistical Summary of Thickness of Coal Samples

Thickness

Mean 13.11304348

Standard Error 0.715198107

Median 12.9

Mode 1.7

Standard Deviation 8.401675416

Sample Variance 70.58814979

Kurtosis 0.245884504

Skewness 0.616938734

Range 40.3

Minimum 0.4

Maximum 40.9

Sum 1809.6

Count 138

Confidence Level(95.0%) 1.414255059

3.4 Regression Analysis

Regression Analysis for each two set of data shows there is no apparent correlation between each

two set. In the best case the R Square factor of regression for Ash Content and Calorific value is

0.66.

19

4. MINERAL RESOURCE AND ESTIMAZTIONS

4.1 Resource reporting code and categorization

The SAMREC Code and the Canadian Institute of Mining Metallurgy and Petroleum (“CIM”)

Standards on Mineral Resources and Reserves, Definitions and Guidelines, both recognize the

use of definitions of Mineral Resources and Mineral Reserves; furthermore, both codes make use

of the definitions of “Measured”, “Indicated” and “Inferred” Mineral Resources in decreasing

geological confidence.

An “Inferred Mineral Resource‟ is that part of a Mineral Resource for which quantity and grade

or quality can be estimated on the basis of geological evidence and limited sampling and

reasonably assumed, but not verified, geological and grade continuity. The estimate is based on

limited information and sampling gathered through appropriate techniques from locations such

as outcrops, trenches, pits, workings and drill holes.

An ‘Inferred Mineral Resource’ is that part of a Mineral Resource for which tonnage, grade and

mineral content can be estimated with a low level of confidence. It is inferred from geological

evidence and assumed but not verified geological and/or grade continuity. It is based on

information gathered through appropriate techniques from locations such as outcrops, trenches,

pits, workings and drill holes that may be limited or of uncertain quality and reliability.

An “Indicated Mineral Resource‟ is that part of a Mineral Resource for which quantity, grade or

quality, densities, shape and physical characteristics, can be estimated with a level of confidence

sufficient to allow the appropriate application of technical and economic parameters, to support

mine planning and evaluation of the economic viability of the deposit. The estimate is based on

detailed and reliable exploration and testing information gathered through appropriate techniques

from locations such as outcrops, trenches, pits, workings and drill holes that are spaced closely

enough for geological and grade continuity to be reasonably assumed.

An ‘Indicated Mineral Resource’ is that part of a Mineral Resource for which tonnage, densities,

shape, physical characteristics, grade and mineral content can be estimated with a reasonable

level of confidence. It is based on exploration, sampling and testing information gathered

through appropriate techniques from locations such as outcrops, trenches, pits, workings and

drill holes. The locations are too widely or inappropriately spaced to confirm geological and/or

grade continuity but are spaced closely enough for continuity to be assumed.

20

A “Measured Mineral Resource‟ is that part of a Mineral Resource for which quantity, grade or

quality, densities, shape, physical characteristics are so well established that they can be

estimated with confidence sufficient to allow the appropriate application of technical and

economic parameters, to support production planning and evaluation of the economic viability of

the deposit. The estimate is based on detailed and reliable exploration, sampling and testing

information gathered through appropriate techniques from locations such as outcrops, trenches,

pits, workings and drill holes that are spaced closely enough to confirm both geological and

grade continuity.

A ‘Measured Mineral Resource’ is that part of a Mineral Resource for which tonnage, densities,

shape, physical characteristics, grade and mineral content can be estimated with a high level of

confidence. It is based on detailed and reliable exploration, sampling and testing information

gathered through appropriate techniques from locations such as outcrops, trenches, pits,

workings and drill holes. The locations are spaced closely enough to confirm geological and

grade continuity.

In this document because of lack enough geological information and site investigation data and

more over because of undefined economical parameters, we manipulated the only Inferred and

Indicated Mineral Resource.

4.2 Key estimation assumptions and parameters

The appropriate key parameters used for this deposit to define the coal resource blocks are:

A minimum seam thickness of 0.5m;

A minimum overburden thickness of 4.0m.

And Specific gravity of coal of 1.27 tonne/m3

4.3 Details of Coal Resource estimators

Coal resources are estimated using Micromine (V. 2014) software.

4.4 Inferred Resource

In order to manipulate this resource 38 sections in the SW-NE (because the spread direction of

the seam was NW-SE) are taken, then polygons were drawn in each sections in order to

determine the cross section of coal seam as shown in the figure 8and 9. Furthermore, some bore

21

holes containing coal were ignored because they were far apart from main ore body and the

length of coal cuts were small enough to be neglected.

Figure 21: Cross section drawn in Micromine

Figure 22: Drill holes and drawn polygons plan.

Then these sections aligned together to form the wireframe of the estimated coal seam which is

shown in the figure 10.

22

Figure23: Wireframe of coal seam built through sections

By means this method total estimated wireframe volume is 145,041,567m3 and total coal

resource is 184,202,790 tonnes.

4.5 Indicated Resource

In order to have more accurate figures of volume and mass of coal and to be capable of fitting a

block model in the ore wireframe we created a grid model of coal seam roof and floor. Then

these grid surfaces are restricted to the border of coal seam. This border is drawn in a pessimistic

manner in which 1/3 distance between bore holes containing coal and no coal cutting bore holes

is assumed to contain coal(figure 11).

23

Figure 24: Coal seam border

Figure25: Coal seam border on the topography

24

Having restricted the coal roof and floor surfaces to the border these two are used to set as upper

and lower limits of wireframe. So the coal seam wireframe is determined and coal volume and

mass are manipulated respectively as 142,999,845 m3 and 181,609,803tonnes. This wireframe is

shown in the figure 13.

Figure26: Coal seam wireframe created by gridding

Figure 27: The coal seam location is shown due to topography.

25

5. BLOCK MODELLING

An ore reserve without a block model is nothing worthy because any of technical and

economical factors can be defined for a single block. In order to design mine operation plans and

define geometric and mass related figures and to predict run of mine quality parameters using a

block model is inevitable.

5.1 Block Definition

For the block size dimensions for x,y and z , 12,12 and 4m are defined respectively. Moreover

for the subblock definition these figures can be divided by 10 if needed. In some cases the coal

seam thickness is 0.4m in minimum state.

Figure 28: Block modeling visualiza tion by Micromine Software.

5.2 Kriging

The kriging algorithm estimates concentration over a regular grid across the site, and the sum of

the kriging weights are used to determine the overall weight assigned to each data point. For a

particular grid location, the surrounding data points within a specified search window are used to

calculate the estimated concentration. The kriging parameters define that grid and search

window, and determine how the kriged estimates are calculated. Search Ellipsoid parameters

determine how far out to search for data to support a particular kriged estimate. In order to

determine the search ellipsoid dimensions our data is processed by Micromine and the result are

shown in the section 3-3.

26

As the figures show the best fitting spherical model occurs in the minimum lag distance interval

of 840 m. The best fitting criteria was the r2>0.995 in the minimum status.

So the search ellipsoid dimensions were taken in x,y and directions as 840, 480 and 100 meters

respectively (for kriging Sulphur these values are 1200,800 and 100 because of lack of data in

some bore holes) to include all values of deferent quality parameters of coal and put them in

estimated blocks and also the azimuth is defined as 315 degrees to be correspondent to the coal

seam expansion direction.

Figure 28: Search Ellipsoid

Kriging application is run for all the quality parameters; Calorific Value (CV), Ash Content,

Sulphur Content, Moisture and also for Thickness of coal seam.

27

Figure 29: CV map for the coal (kJ.kg-1

)

Figure 30: Ash content of coal (%)

28

Figure 31: Moisture Content of coal (%)

Figure 32: Thichness of coal seam (m)

29

Figure 33: Sulphur Content of coal seam (%)

Figure 34: Coal roof elevation (from sea level, m)

30

5.3 Estimation Reports

Total coal volume and mass was calculated as follow;

Table 6: Total Ore Reserve

Ore Volume (m3) Density (tonne/m3) Ore Reserve (tonne)

142999844.8 1.27 181609802.9

In order to have a realistic concept of physical and chemical quality of whole ore body and also

have information about reserve amount for all characteristic intervals which may affect cut-off

grade determination below tables were prepared.

31

Table 7: Calorific-Mass distribution

From To Volume Tonnes Calorie

(kJ/kg)

Cumulative

volume

Cumulative

Tonne

Cumulative

Calorie

(kJ/kg)

-1.#INF 1018.94 879907.98 1117483.13 892.8641 879907.98 1117483.13 892.8641

1018.94 1081.51 195977.67 248891.64 1052.8398 1075885.64 1366374.77 922.0044

1081.51 1144.08 251359.49 319226.55 1113.1006 1327245.13 1685601.32 958.1951

1144.08 1206.66 420717.31 534310.99 1180.116 1747962.45 2219912.31 1011.6092

1206.66 1269.23 775955.53 985463.52 1239.7386 2523917.97 3205375.83 1081.7455

1269.23 1331.81 1294911.95 1644538.17 1294.755 3818829.92 4849914 1153.9741

1331.81 1394.38 1309275.66 1662780.09 1366.4201 5128105.58 6512694.09 1208.2145

1394.38 1456.96 1231763.92 1564340.18 1420.1457 6359869.5 8077034.27 1249.2608

1456.96 1519.53 778406.41 988576.14 1488.4545 7138275.91 9065610.41 1275.3441

1519.53 1582.1 1026047.25 1303080 1553.3272 8164323.16 10368690.41 1310.2795

1582.1 1644.68 2165520.99 2750211.65 1613.1438 10329844.14 13118902.06 1373.7712

1644.68 1.#INF 132672147.3 168493627.1 2172.5301 143001991.5 181612529.2 2114.8312

Ash content of coal is the non-combustible residue left after coal is burnt. It represents the bulk

mineral matter after carbon, oxygen, sulfur and water (including from clays) has been driven off

during combustion. Analysis is fairly straight forward, with the coal thoroughly burnt and the ash

material expressed as a percentage of the original weight. It can also give an indication about the

quality of coal.

Table 8: Ash-Mass distribution

From To Volume Tonnes Ash

(%)

Cumulative

volume

Cumulative

Tonne

Cumulative

Ash (%)

-1.#INF 7.65 0 0 0 0 0 0

7.65 11.91 47600021.19 60452026.91 10.591 47600021.19 60452026.91 10.5907

11.91 16.17 59121015.53 75083689.72 13.333 106721036.7 135535716.6 12.1101

16.17 20.42 16483396.19 20933913.16 18.102 123204432.9 156469629.8 12.9118

20.42 24.68 8000137.24 10160174.29 21.97 131204570.1 166629804.1 13.4641

24.68 28.94 4043203.83 5134868.86 26.773 135247774 171764672.9 13.862

28.94 33.2 2021315.93 2567071.23 31.189 137269089.9 174331744.2 14.1171

33.2 37.46 3295439.46 4185208.11 35.084 140564529.4 178516952.3 14.6087

37.46 41.71 1161403.21 1474982.08 39.376 141725932.6 179991934.4 14.8117

41.71 45.97 450976.32 572739.93 43.564 142176908.9 180564674.3 14.9029

45.97 50.23 757457.86 961971.49 48.565 142934366.8 181526645.8 15.0812

50.23 1.#INF 67624.7 85883.37 50.23 143001991.5 181612529.2 15.0979

32

Coal has a wide moisture content range, which affects its value as fuel and determines how

environmentally friendly it is to use. Without the proper handling and production processes, the

quality of coal is depleted, potentially causing increased pollution.

Table 9: Moisture-Mass distribution

From To Volume Tonnes Moisture

(%)

Cumulative

volume

Cumulative

Tonne

Cumulative

Moisture

(%) -1.#INF 18.99 0 0 0 0 0 0

18.99 22.69 2943.94 3738.8 21.097 2943.94 3738.8 21.097

22.69 26.38 6007.68 7629.75 24.9011 8951.62 11368.55 23.6501

26.38 30.07 22393.15 28439.3 28.6464 31344.77 39807.86 27.2195

30.07 33.76 1091953.74 1386781.25 31.7187 1123298.51 1426589.11 31.5932

33.76 37.46 1690818.07 2147338.95 36.0022 2814116.58 3573928.06 34.2423

37.46 41.15 6571957.9 8346386.53 39.445 9386074.48 11920314.59 37.8851

41.15 44.84 8849044.9 11238287.02 43.2702 18235119.38 23158601.61 40.4984

44.84 48.53 34882430.69 44300686.97 46.9212 53117550.06 67459288.58 44.7163

48.53 52.22 70565291.78 89617920.56 50.5411 123682841.8 157077209.1 48.0395

52.22 55.92 19319149.62 24535320.01 52.9206 143001991.5 181612529.2 48.6989

55.92 1.#INF 0 0 0 143001991.5 181612529.2 48.6989

Coal-fired power plants are the largest human-caused source of sulfur dioxide, a pollutant gas

that contributes to the production of acid rain and causes significant health problems, particularly

through its role in forming particulates. Sulfur dioxide contributes to the formation of acid rain,

which damages forests, crops, and buildings, and acidifies lakes, streams, and rivers, making

them unsuitable for aquatic plant and animal life.

Table 10: Sulphur-Mass distribution

From To Volume Tonnes Sulphur

(%)

Cumulative

volume

Cumulative

Tonne

Cumulative

Sulphur

(%)

-1.#INF 0.51 0 0 0 0 0 0

0.51 1.01 9180956.82 11659815.16 0.9001 9180956.82 11659815.16 0.9001

1.01 1.51 47244299.7 60000260.62 1.3046 56425256.52 71660075.78 1.2388

1.51 2.01 50017214.53 63521862.45 1.7501 106442471 135181938.2 1.4791

2.01 2.51 25988028.72 33004796.47 2.2039 132430499.8 168186734.7 1.6213

2.51 3.01 5884063.54 7472760.7 2.7212 138314563.3 175659495.4 1.6681

3.01 3.51 2681572.64 3405597.25 3.2271 140996135.9 179065092.7 1.6977

3.51 4.01 1241225.87 1576356.86 3.6836 142237361.8 180641449.5 1.7151

4.01 4.51 440009.86 558812.52 4.239 142677371.7 181200262 1.7229

4.51 5.01 239367.17 303996.31 4.7233 142916738.9 181504258.3 1.7279

5.01 5.51 85102.85 108080.62 5.2122 143001841.7 181612339 1.73

5.51 1.#INF 149.76 190.2 5.5132 143001991.5 181612529.2 1.73

33

5.4 Correlation of ore parameters

It would ideal if there is great thickness of lignite body, high calorific value, low moisture and

low Sulphur content simultaneously but to have a review on realistic information below tables

were made.

Table 11: Lignite Thickness-CV reserve distribution

Thickness

From (m)

Thickness

To (m) Volume Tonnes

Calorie

(kJ/kg)

Cumulative

volume

Cumulative

Tonne

-1.#INF 0.00 0.00 0.00 0.00 0.00 0.00

0.00 5.00 1914174.77 2431001.96 1694.02 1914174.77 2431001.96

5.00 10.00 16308236.39 20711460.21 1779.18 18222411.16 23142462.18

10.00 15.00 39905551.14 50680049.95 2045.70 58127962.30 73822512.12

15.00 20.00 54461663.84 69166313.08 2194.01 112589626.14 142988825.20

20.00 25.00 19264419.21 24465812.39 2249.45 131854045.35 167454637.59

25.00 30.00 9231276.72 11723721.43 2306.44 141085322.07 179178359.03

30.00 35.00 1690577.86 2147033.89 2323.93 142775899.93 181325392.92

35.00 40.00 192755.52 244799.51 2328.59 142968655.46 181570192.43

40.00 45.00 33162.05 42115.80 2282.97 143001817.50 181612308.23

45.00 1.#INF 173.95 220.92 2290.13 143001991.46 181612529.15

As the table show, much thickness amount approximately means much calorific value.

Table 12: Lignite Ash and Moisture content due to CV intervals

CV From(kJ/kg) CV To (kJ/kg) Ash (%) Moisture (%)

-1.#INF 825.2 50.2 30.7

825.2 1,012.6 48.5 31.4

1,012.6 1,199.9 42.0 34.8

1,199.9 1,387.3 36.2 38.1

1,387.3 1,574.7 31.3 40.1

1,574.7 1,762.1 24.2 42.9

1,762.1 1,949.5 18.4 46.5

1,949.5 2,136.9 14.4 49.0

2,136.9 2,324.3 12.1 50.5

2,324.3 2,511.6 11.2 51.2

2,511.6 2,699.0 11.9 47.4

2,699.0 1.#INF 22.2 25.7

As it was predictable calorific value has a reverse relation with ash content and as it is seen as a

total trend much CV shows much moisture.

34

In mine designing and production planning it is very important to have information about ore

body quality and resource tonnage estimation in each level (elevation) of mining. Therefore you

can predict the Run of Mine quantity and quality for each bench (in open pit mining). Due to this

fact a set of table and diagrams has been formed up to give a rough view of future production on

from this ore body.

Table 13: Lignite Ash and Moisture content and CV due to Elevation intervals

From To Volume Tonnes Calorie

(kJ/kg)

Ash

(%)

Moisture

(%)

Cumulative

Voulme (m3)

Cumulative

Tonne

-

1.#INF

750 0 0 0 0 0 0 0

750 754 28479.75 36169.28 2529.9583 12.0919 49.0788 28479.75 36169.28

754 758 115203.5 146308.39 2513.9381 12.1924 49.079 143683.2 182477.67

758 762 306160.7 388824.1 2486.417 12.1928 49.4522 449843.91 571301.77

762 766 770690.3 978776.7 2462.7927 12.2071 49.8001 1220534.23 1550078.47

766 770 1466724 1862738.89 2432.7241 12.4074 50.0406 2687257.76 3412817.36

770 774 2442617 3102123.24 2401.8014 12.5885 50.2547 5129874.49 6514940.6

774 778 3362440 4270299.24 2375.4352 12.7025 50.4637 8492314.84 10785239.84

778 782 4101587 5209014.97 2354.6609 12.6498 50.5976 12593901.43 15994254.81

782 786 4745822 6027194.49 2333.6918 12.5169 50.6419 17339723.86 22021449.3

786 790 5334030 6774217.6 2310.6835 12.3573 50.5876 22673753.47 28795666.9

790 794 5386284 6840581.1 2275.144 12.1899 50.3847 28060037.8 35636248.01

794 798 5270541 6693587.27 2259.0924 11.9476 50.3851 33330578.96 42329835.28

798 802 5152806 6544063.12 2254.0426 11.8646 50.4095 38483384.57 48873898.41

802 806 5061303 6427855.32 2255.1309 11.9713 50.2734 43544687.97 55301753.73

806 810 4930573 6261828.08 2282.2902 11.9523 50.2843 48475261.27 61563581.81

810 814 4991077 6338668.4 2304.5653 11.75 50.4324 53466338.75 67902250.21

814 818 4914893 6241914.64 2299.8303 11.8532 50.2564 58381232.17 74144164.85

818 822 4757562 6042103.61 2284.715 12.2406 49.8378 63138794.06 80186268.46

822 826 4666879 5926936.01 2265.8256 12.5397 49.508 67805672.81 86113204.47

826 830 4715492 5988674.84 2237.9814 12.7947 49.3576 72521164.81 92101879.31

830 834 4576340 5811951.31 2206.8971 13.1088 49.205 77097504.43 97913830.63

834 838 4134946 5251381.69 2171.6021 13.4756 49.1026 81232450.64 103165212.3

838 842 3628554 4608262.95 2127.3644 13.7624 49.2833 84861004.15 107773475.3

842 846 3479449 4418900.22 2117.144 13.6628 49.6236 88340453.13 112192375.5

846 850 3586204 4554479.41 2104.0698 13.5821 49.857 91926657.39 116746854.9

850 854 3679393 4672829.11 2083.8087 13.8512 49.9718 95606050.39 121419684

854 858 3774874 4794090.25 2056.0966 14.1809 49.9327 99380924.6 126213774.2

858 862 3499356 4444181.55 2029.3489 14.6913 49.5734 102880280.2 130657955.8

862 866 2788019 3540783.61 1989.5843 15.7671 48.9229 105668298.7 134198739.4

866 870 2515617 3194833.9 1929.86 17.0812 48.0595 108183916 137393573.3

870 874 2303841 2925878.13 1881.7616 18.0092 47.3741 110487757 140319451.4

874 878 2204053 2799147.41 1861.6814 18.6409 47.0533 112691810.1 143118598.9

878 882 2192969 2785070.77 1853.4652 19.2865 46.6207 114884779.2 145903669.6

882 886 2272151 2885632.1 1817.248 20.3695 46.0645 117156930.5 148789301.7

886 890 2372393 3012939.25 1763.9027 21.9237 45.3501 119529323.6 151802241

890 894 2583279 3280764.82 1717.287 23.2506 44.7326 122112603 155083005.8

894 898 2889395 3669531.12 1626.1242 25.9505 43.362 125001997.6 158752536.9

898 902 2910302 3696083.83 1587.4108 27.0798 42.6851 127912299.8 162448620.7

902 906 2517740 3197529.54 1621.0178 25.9792 43.0046 130430039.6 165646150.3

906 910 2077112 2637932.1 1710.0279 23.1445 44.2548 132507151.5 168284082.4

910 914 1621685 2059539.71 1752.8414 21.8423 44.7084 134128836.3 170343622.1

914 918 1264379 1605761.03 1811.0643 20.1945 45.4162 135393215.1 171949383.1

918 922 1101210 1398536.78 1843.5492 19.0791 45.9413 136494425.1 173347919.9

922 926 960221.4 1219481.16 1848.8723 18.7317 46.1026 137454646.5 174567401.1

926 930 740942.2 940996.62 1851.263 18.4719 46.2235 138195588.7 175508397.7

35

930 934 585050.7 743014.39 1859.1614 18.0987 46.4872 138780639.4 176251412.1

934 938 435370.8 552920.87 1863.0934 18.0299 46.4625 139216010.2 176804332.9

938 942 407475.7 517494.08 1868.9262 17.9585 46.1538 139623485.8 177321827

942 946 398329.4 505878.28 1844.2331 18.6255 45.5279 140021815.2 177827705.3

946 950 360173.4 457420.2 1796.2984 19.8888 44.6823 140381988.6 178285125.5

950 954 304794.4 387088.94 1744.9955 21.2058 43.915 140686783 178672214.4

954 958 269049.6 341693 1666.926 23.2352 42.7437 140955832.6 179013907.4

958 962 287249.5 364806.84 1669.1252 23.1302 42.7475 141243082.1 179378714.3

962 966 287458 365071.65 1698.0753 22.5556 42.963 141530540.1 179743785.9

966 970 299037.9 379778.13 1706.4908 22.7537 42.6274 141829578 180123564

970 974 236547.7 300415.52 1738.4158 22.9255 41.8335 142066125.6 180423979.6

974 978 185239.3 235253.91 1785.8842 23.0646 40.7245 142251364.9 180659233.5

978 982 131027.9 166405.44 1777.185 23.633 40.3365 142382392.8 180825638.9

982 986 97716.1 124099.45 1702.5908 25.8862 39.3375 142480108.9 180949738.4

986 990 74018.31 94003.25 1712.5811 29.9167 34.9468 142554127.3 181043741.6

990 994 69059.52 87705.59 1601.5107 31.6542 35.0865 142623186.8 181131447.2

994 998 93643.78 118927.6 1522.9787 32.4684 35.5885 142716830.6 181250374.8

998 1002 82876.61 105253.3 1687.975 29.791 35.4602 142799707.2 181355628.1

1002 1006 61593.41 78223.63 1958.565 26.1592 34.542 142861300.6 181433851.7

1006 1010 48393.79 61460.12 2003.2407 22.6962 37.4484 142909694.4 181495311.9

1010 1014 51379.78 65252.32 1940.353 20.9616 40.5461 142961074.1 181560564.2

1014 1018 35622.14 45240.12 1940.7995 20.4655 41.3938 142996696.3 181605804.3

1018 1022 5295.17 6724.86 1903.6151 19.89 42.8086 143001991.5 181612529.2

1022 1.#INF 0 0 0 0 0 143001991.5 181612529.2

Figure 35:CV distribution due to Elevation

R² = 0.8641

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

600 700 800 900 1000 1100

Cal

ori

e (

kJ/k

g)

Elevation (m)

Series1

Poly. (Series1)

36

Figure 36:Ash distribution due to Elevation

Figure 37:Moisture distribution due to Elevation

R² = 0.7704

0

5

10

15

20

25

30

35

600 700 800 900 1000 1100

ASh

(%

)

Elevation (m)

Series1

Expon. (Series1)

R² = 0.828

30

35

40

45

50

55

600 700 800 900 1000 1100

Mo

istu

re

Elevation (m)

Series1

Poly. (Series1)

37

6. MINING METHOD SELECTION

6.1 Introduction

The relative merits of surface and underground mining are widely discussed and frequently

debated. Some deposits can be mined entirely with surface methods, while others can only be

worked underground. With all other conditions equal, sur-face mining is normally regarded as

preferable, because of lower development costs, quicker start-up time, and lower accident

rates generally associated with surface mining. When choosing between surface and underground

meth-ods, some of the factors that must be considered include

• Size, shape, and depth of the deposit;

• Geologic structure and geomechanical conditions;

• Productivities and machinery capacities;

• Availability of experienced work force;

• Capital requirements and operating costs;

• Ore recoveries and revenues;

• Safety and injuries;

• Environmental impacts, during and after mining;

• Reclamation and restoration requirements and costs; and

• Societal and cultural expectations.

Some deposits may reasonably be mined entirely by sur-face methods. In general, such deposits

are close to the surface and have a relatively uniform geology. Similarly, some depos-its can

only be mined economically by underground methods. These deposits are usually deeper, with

geological and miner-alogical characteristics that require more selective ore extrac-tion. Finally,

other deposits are best mined initially as open pits, with production shifting to an underground

method as deeper portions of the ore body are extracted. An example of each type of deposit

follows. In suitable deposits, surface mining is more productive, more economic, and safer for

workers. However, changes in environmental regulations and societal expectations may lead to

fewer large open-pit mines, particularly if opera-tors are required to backfill open pits and

recontour waste dumps. These conditions may result in the development of small, high-grade

deposits by very shallow open pits or in the development of high-grade underground mines in

place of large open-pit mines. Where applicable, large, low-grade deposits may be mined by in-

situ methods (Hitzman 2005). In some cases, especially in built-up areas, it has become almost

impossible to obtain permits for new surface mines. This is the case for producers of crushed

38

stone and dimension stone in large metropolitan areas in many developed countries. For this

reason, several underground quarries have recently begun operating in the United States, and

many more are in the planning stages.( The 2014 SME Guide)

6.2 Development

Development for surface mining of coal and other bedded minerals involves the removing of

cover layers of soil and rock to expose the coal. Surface mining is used when the coal seam is

relatively close to the surface, usually within 60 m. The time between overburden removal and

the mining of the product mineral should be as short as possible to optimize overall cash flow.

However, for larger deposits covered by large amounts of overburden and waste, the amount of

pre-stripping will also be large, leading to high preproduction development costs. The time

required for pre-stripping can range from 2 to 6 years. Thus, interest costs during development

will be high and will represent a significant portion of the pre-mining capital requirement before

mining can start. When an ore body is steeply dipping and at or near the surface, open-pit mining

can start with a small amount of stripping. However, as mining of such a deposit progresses,

increasing amounts of waste rock must be removed. This must often be done many years before

mining of the corresponding amount of ore at deeper levels can take place. Thus, the ultimate pit

limits must be projected early in the mine planning process, and the investment cost for waste

rock removal in advance of mining must be included in the economic evaluation. Waste rock

stripping should be delayed as long as possible to avoid high interest cost for all the money spent

in waste stripping activities. The increasing cost of stripping at greater depths is one of the major

factors in deciding when to transition from surface to underground mining of a given deposit. In

an underground mine, a significant amount of infra-structure must be installed before mining

begins. This will include shafts, hoists, ventilation fans, underground shops, travel ways for

workers and machinery, ore storage bins, underground crushers, and so forth. This requires

detailed long-range planning from the very beginning so that the requirements of future

workings at deeper levels can be accommodated. A large capital investment is often necessary

before production can start.

Underground mining methods require a more careful design and planning process, because it is

difficult to make changes in a design after the infrastructure has been installed and the equipment

purchased. This condition is often exac-erbated when variables such as ore grade, mine water

make, and ground control conditions change or are different than expected. It is very important

that the underground mine design and the machinery capacities are properly chosen from the

beginning. For all of these reasons, it is often prudent to develop a small test mine to accurately

determine many of the unknown mine characteristics. A test mine and a properly conducted

feasibility study will minimize these risks.

The development of a large underground mine can take as many as 5 to 10 years. Interest costs

during development will therefore be high and may comprise 30% to 40% of the pre-mining

capital requirement before mining can start.

39

6.3 Cost Comparisons

Estimates of capital and operating costs for surface and under-ground mines of various sizes and

configurations are compiled regularly and in considerable detail by InfoMine, Inc. Those

estimates are provided to customers as the Mining Cost Service and can be purchased in printed

or electronic form, or accessed on-line. The cost estimates do not include permitting, environ-

mental analysis, reclamation, or closure costs.

The Mining Cost Service also provides estimates of capital and operating costs for underground

mining. The data are more extensive, with estimates for eight mining methods, and shaft and adit

access for each. Below Figures summarize selected data. While surface mining methods are

relatively simple and uniformly applied, there are many underground mining meth-ods, and

application of any given method will vary from mine to mine. Thus it is much more difficult to

accurately summarize costs for underground mining methods.

Figure 38: Estimated capital costs for surface

mines at four stripping ratios

Figure 39: Estimated capital costs for six

types of underground mines, all with shaft

access

Figure 40: Estimated operating costs for

surface mines at four stripping ratios

Figure41: Estimated operating costs for six

types of underground mines, all with shaft

access

• For small mines, capital and operating costs per metric ton of ore produced are lower for

surface methods. Of course, dilution and ore grade must also be considered in a full economic

analysis. For large tonnage produc-tion, capital and operating costs may be higher for surface

mines, depending on stripping ratio. In these cases, a dual feasibility study must be performed

comparing the open-pit option to the best underground mining option.

40

• In all cases, capital costs increase and operating costs decrease with increasing production

tonnage.

6.4 Selection of A Mining Method

Based on this brief introduction, it may appear that surface mining is preferable to

underground methods, particularly in regard to productivity and worker safety. However, as has

been pointed out, selection of the best mining method for any deposit requires analysis of many

factors besides the simple productivity in metric tons of ore per worker-hour.

Three aspects of a deposit’s geology relate to the choice of surface or underground mining: the

intrinsic value or grade, the morphology, and the structure. A material with a higher intrinsic

value will support a more expensive mining method. For example, Jim Walter Resources mines

high-quality metallurgical coal at its Blue Creek mine in Alabama (United States) under very

difficult conditions that include spontaneous combustion, deep cover (450 to 730 m), and high

methane levels (Howell et al. 1991).

Deposit morphology, including shape, extent, and depth, is also important. The economics of

most surface mining methods (and some underground methods) are based on high production

volume and low unit costs, and use of equip-ment that has high capital costs. These require

large deposits with relatively uniform grade and few irregularities in shape or extent.

Deposits that meet these criteria can often be mined profitably, even when the ore grade or

product value is relatively low. Good examples of such surface mines are large coal mines in

northeastern Wyoming, as described pre-viously; the large porphyry copper mines, such as

Bingham Canyon in Utah (United States) and Chuquicamata in Chile; and the large, low-grade

gold mines such as Round Mountain and Goldstrike in Nevada. Similarly, coal deposits that can

be mined by the underground longwall method must have large areas of coal with relatively

uniform thickness to allow the development and production of large panels that will support the

costs of development and purchase of equipment. The depth of a deposit also influences the

surface versus under-ground decision. The depth of the Blue Creek mine requires the use of

barrier pillars between longwall panels, at a cost that could probably not be supported by a

lower-value coal. In other cases, metal deposits are often mined initially by the open-pit method

but switch to an underground method when the costs of removing overburden become too high.

This has happened, for example, at Kiruna in Sweden, Northparkes in Australia, and Palabora in

South Africa.

Finally, the geologic structure of a deposit must be considered. Of course, open-pit mining was

unknown when opera-tions began at Homestake, but lacking other information, one might

conclude that this large, low-grade deposit was an ideal candidate for that method. However, the

deposit was highly folded and faulted, and required selective mining to extract the ore in a

manner that could only have been done by under-ground methods.

41

6.5 Selected Project Mining Method

Selection of the best mining method for a given deposit, including the choice between surface

and underground mining, is a complex process involving the analysis of many inter-related

variables. These variables are not just technical; they include consideration of environmental,

social, and political conditions and constraints, and of the time and expense required to obtain

the required government permits.

The process is usually iterative in nature, looking at many possible approaches and determining

how all the variables interact in each. Mining companies and consultants now use detailed and

sophisticated models that incorporate all the technical and financial data, and provide detailed

output showing mine and mill production, direct and indirect costs, taxes and royalties, cash

flows, internal rate of return, and net present value for each alternative considered. These models

often incorporate probabilistic routines for sensitivity analysis so that decision makers can look

at how the predicted outcomes for each alternative are affected by changes in the values of key

variables such as ore grade, labor and material costs, and commodity prices.

Due to all above and specially geological status Open Pit Mining is selected.

42

7. MINING METHOD ELEMENTS

7.1 Mining Operations

Ilgin Coal Project will supply the feed for a thermic power plant. This power plant is planned to

be fed by 4 million tons of coal each year in order to generate the scheduled electricity.

The estimated maximum total of US$2 billion in investments for each 1400 MWe TPP unit

designed to use the latest clean coal technology may pay off in approximately less than eight to

ten years with an overall 33% plant efficiency, with6500 hours of total operation per year.

That is electricity generation from your own resources.

CFB is possible but we also need enrichment up to 2000 kcal/kg LHV, or 3000 BTU/lb HHV.

Available references elsewhere are not compatible with the coal.(www.turkishweekly.net)

In order to supply the planned annual coal and to be close to access roads and waste dump area

pit opening and extraction from the ore reserve begins from northern part and pushnacks will be

in advance in the direction of Northwest-Southeast.

7.2 Mine Design

The design process for Ilgin pit is developed by Micromine 2014 by using ore body solid and is

not optimized for the bock model and cut off grade so the cut off grades of extracted ore are

approximately the same table 7 and also no economic optimization and assumption has been

taken into consideration.

It is assumed that one the biggest trucks CAT 793 trucks is used for ore and waste haulage.

Necessary information for designing the pit are assumed independently due to geotechnical and

equipment selection issues.

a) Working Bench Geometry

Width of bench: 50 m

Bench Face Slope: 75 degrees

b) Ramp

Ramp Width: 30 m

Ramp Slope: 10%

Switchback Internal Radius: 45m

c) Safety Benches: Due to Geomechanical Issues the specification is the same as working

benches

43

Figure 42: Schematic geometry of a working bench

7.3 Production Schedule

The mine operates 24 hours a day, 365 days a year. Production rates vary by material type.

Currently, ore is scheduled at a throughput rate of 4 Mt/a. The life-of-mine (LOM) schedule is

presented in Table 14. The LOM schedule in Table 14 shows that the final pit is depleted in

2060. The plant would continue to be fed from stockpiles in mine stoppage times. The total mine

life is 45 years as of the end of 2015. Table 15 presents the reserve recovery schedule for the

Project.

In order to have summary of mining operation status only first 5 years and the final pit design is

mentioned.

Table 14: Ilgin LOM Mining Schedule

Year Total Volume (m3) Coal Tonnage

1 66,360,775 4141682

2 43,569,113 4,110,508

3 48,357,308 3,991,299

4 45,190,880 3,966,606

5 37,899,164 4,081,788

Final 2,598,339,496 181350650

44

a) 1st year

Figure 43: 1s t

year pit

Table 15: Waste and Coal Extracted in the 1st Year

Bench Level

(m) Total Volume Waste (m

3)

Coal Volume

(m3)

Coal

Tonnage

1,070 332 332 0 0

1,055 30,771 30,771 0 0

1,040 325,434 325,434 0 0

1,025 7,049,160 7,049,160 0 0

1,010 18,156,963 18,064,738 92,225 117,126

995 15,893,488 15,628,772 264,715 336,188

980 12,095,286 11,775,589 319,697 406,015

965 8,570,805 7,753,985 816,819 1,037,361

950 5,193,929 4,394,736 799,194 1,014,976

935 2,519,265 1,720,888 798,377 1,013,938

920 761,137 590,998 170,140 216,077

TOTAL 66,360,775 63,099,608 3,261,167 4,141,682

45

b) 2nd

year

Figure 44: 2nd

year pit

Table 16: Waste and Coal Extracted in the 2nd

Year

Bench Level (m) Total

Volume Waste (m

3)

Coal Volume

(m3)

Coal

Tonnage

1,070 0 0 0 0

1,055 0 0 0 0

1,040 0 0 0 0

1,025 395,759 395,759 0 0

1,010 6,931,662 6,931,662 0 0

995 8,057,390 8,057,390 0 0

980 7,395,088 7,395,088 0 0

965 6,734,873 6,686,154 48,719 61,873

950 6,073,565 5,796,524 277,042 351,843

935 5,214,255 4,589,952 624,303 792,865

920 3,885,711 2,474,813 1,410,898 1,791,840

905 1,661,818 786,158 875,659 1,112,087

TOTAL 43,569,113 40,332,492 3,236,620 4,110,508

46

c) 3rd

Year

Figure 45: 3rd

year pit

Table 17: Waste and Coal Extracted in the 3rd

Year

Bench Level

(m) Total Volume Waste (m3)

Coal Volume

(m3)

Coal

Tonnage

1,070 0 0 0 0

1,055 0 0 0 0

1,040 0 0 0 0

1,025 96,582 96,582 0 0

1,010 6,467,743 6,467,743 0 0

995 8,393,978 8,393,978 0 0

980 7,670,305 7,670,305 0 0

965 6,942,601 6,942,601 0 0

950 6,209,805 6,209,805 0 0

935 5,467,426 5,408,291 59,135 79,608

920 4,679,262 3,983,240 696,022 936,985

905 3,651,419 2,195,952 1,455,467 1,959,350

890 1,864,822 1,102,573 762,250 1,026,140

TOTAL 48,357,308 45,214,552 3,142,755 3,991,299

47

d) 4th

Year

Figure 46: 4th year pit

Table 18: Waste and Coal Extracted in the 4th Year

Bench Level

(m) Total Volume Waste (m3)

Coal Volume

(m3)

Coal

Tonnage

1,070 0 0 0 0

1,055 0 0 0 0

1,040 518 0 0 0

1,025 158 158 0 0

1,010 4,540,901 4,540,901 0 0

995 6,304,591 6,304,591 0 0

980 5,894,085 5,894,085 0 0

965 5,484,534 5,484,534 0 0

950 5,077,302 5,077,302 0 0

935 4,676,368 4,675,342 1,026 1,303

920 4,287,050 4,011,851 275,199 335,522

905 3,928,370 3,127,846 800,524 975,998

890 3,409,386 1,859,448 1,549,938 1,889,685

875 1,688,956 1,038,787 650,169 792,686

TOTAL 45,190,880 42,067,569 3,123,312 3,966,606

48

e) 5th

Year

Figure 47: 5th year pit

Table 19: Waste and Coal Extracted in the 5th Year

Bench Level

(m) Total Volume Waste (m3)

Coal Volume

(m3)

Coal

Tonnage

1,070 0 0 0 0

1,055 0 0 0 0

1,040 0 0 0 0

1,025 0 0 0 0

1,010 3,198,132 3,006,244 0 0

995 4,521,655 4,250,356 0 0

980 4,332,341 4,072,401 0 0

965 4,147,528 3,898,676 0 0

950 3,955,749 3,718,404 0 0

935 3,768,780 3,542,653 0 0

920 3,571,325 3,291,050 70,208 89,164

905 3,375,615 2,736,182 464,783 590,274

890 3,115,660 1,673,425 1,335,421 1,695,984

875 2,752,450 1,493,278 1,163,856 1,478,098

860 1,233,965 1,062,545 171,420 217,704

TOTAL 37,899,164 34,685,158 3,214,006 4,081,788

49

f) Total LOM

Figure 48: Final pit

Table 20: Waste and Coal Extracted in Total LOM

Bench Level (m) Waste (m3) Coal Volume (m3) Coal Tonnage

1,070 332 0 0

1,055 30,771 0 0

1,040 325,985 0 0

1,025 137,891,469 0 0

1,010 211,114,213 92,225 117,126

995 258,586,560 264,715 336,188

980 244,675,701 319,697 406,015

965 230,948,023 865,538 1,099,233

950 217,245,150 1,076,235 1,366,819

935 203,862,753 1,479,816 1,879,367

920 190,667,691 2,944,010 3,738,892

905 177,183,203 6,106,629 7,755,419

890 163,652,872 10,310,084 13,093,807

875 147,056,359 8,481,911 10,772,027

860 130,043,141 9,872,330 12,537,860

845 111,639,706 13,711,474 17,413,572

830 91,179,458 14,940,195 18,974,047

815 75,995,274 17,795,280 22,600,006

800 60,276,761 18,789,897 23,863,169

785 41,716,045 19,811,583 25,160,710

770 23,816,428 13,392,214 17,008,112

755 7,152,162 2,541,953 3,228,281

TOTAL 2,598,339,496 142,795,787 181,350,650

50

7.4 Coal Reserve Recovery

The fundamental dilemma is that, if taken for granted that all mine design needs to result in a

safe working environment, a compromise may be required between reserve recovery and

rate/cost of production. Here due the reserve recovery rates for various years are as follow;

Table 21: Reserve Recovery of Ilgin Pit

Year Reserve (t) Excavated (t) Recovery (t)

1 4,154,001 4,141,682 99.70%

2 4,151,870 4,110,508 99.00%

3 4,041,496 3,991,299 98.76%

4 3,984,231 3,966,606 99.56%

5 4,101,302 4,081,788 99.52%

Final 181,609,803 181,350,650 99.86%

7.5 Coal Quality Extracted

In order to have information about the quality of extracted coal, the block model is considered in

each year production and following table is mean values of CV, Ash, Moisture and Sulphur

extracted coal.

Table 22: Annual Extracted Coal Properties

Annual Cumulative

Year Sulphur Calorie Ash Moisture Calorie Ash Moisture Sulphur

1 1766 22.93 41.77 1.91 1784 22.70 41.35 1.88

2 1871 19.51 43.21 1.62 1819 21.22 42.49 1.77

3 1824 20.75 43.59 1.77 1848 20.13 43.40 1.69

4 1927 17.89 44.58 1.55 1875 19.32 44.08 1.66

5 1863 19.66 44.82 1.72 1895 18.77 44.70 1.63

Final 2368 10.97 50.23 1.77 2114 15.33 47.52 1.74

Table 23: Yearly Gained Total Calorie

Year Total Calorie

(1012

*kCal)

1 7.3

2 7.7

3 7.3

4 7.6

5 7.6

Final 429.4

51

7.6 Waste Rock

There should be main waste dumps in the LOM plan which is not designed during this project. A

backfill analysis should be performed on the waste dump to evaluate the quantity of ore that

would be sterilized from the in-pit dumping.

7.7 Strip Ratio

The economic stripping limit is usually the first factor to be determined in establishing the mine

plan. The economic strip-ping ratio is defined as the cubic meters (yards) of waste mate-rial to be

removed to uncover one metric ton (short ton) of product. For illustration purposes in this

chapter, coal will be used as the resource. Developing maps that show the ratio of overburden

thickness to a mineable coal thickness is a good place to begin. This ratio can be converted to a

strip ratio map by mapping the thickness of the overburden and interburden converted to cubic

meters and divided by the thickness of the coal converted to metric tons (short tons). This ratio is

calculated using the cumulative thickness of both overburden/interburden and coal seams down

to and including the lowest mineable seam.

Table 24: Strip Ratio During LOM

Year Waste Volume (m3) Coal Tonnage W/O (m

3/t)

1 63,099,608 4141682 15.24

2 40,332,492 4,110,508 10.60

3 45,214,552 3,991,299 12.12

4 42,067,569 3,966,606 11.39

5 34,685,158 4,081,788 9.28

Final 2,455,543,708 181350650 13.33

7.8 Mine Equipment

The production fleet consists of twenty three Caterpillar 793 haul trucks. The loading fleet

consists five and one Bucyrus 495HD shovels.

A summary of the mine equipment currently in use is displayed in Table 17.

Table 25: Ilgin Mine Equipment

Equipment Quantity Model

Haul Truck 23 CAT 793

Wheel Loader 5 CAT 994K

Shovel 1 Bucyrus 495HD

Dozer 3 CAT D10R

Dozer 2 CAT D11R

52

Of course due clue we have in this project these kind of heavy equipment will have problem like

getting stock roads and benches because of low strength of ground condition.

53

8. CONCLUSION and RECOMMENDATIONS

Total estimated resource for Ilgin Coal is 181.6 Mt with mean quality of Calorific Value=2115

kJ/kg, Ash Content=15.1%, Moisture Content=48.7% and Sulphur Content=1.73%. These

figures show that the Ilgin Lignite reserve is of a moderate quality and mid-class of ore as a

matter of resource amount.

It is recommended to do more laboratory tests in order to have more information in both

chemical and physical aspects. For instance among 158 bore holes which cut lignite only for 105

bore holes CV, Ash and Moisture values are reported and for Sulphur this figure is 36 that is

approximately 20% of our samples. If this chemical tests are done the block model will reflect

more accurate values of ore body characteristics.

In order to determine cut-off grade for each quality figure of lignite, Histogram charts should be

made and by considering economical factors appropriate decision should be made. Although

more studies and analysis should be done to design an optimum pit design for the reserve, it is

recommended to begin over burden removing in the areas which lignite seam roof elevation is

between 800-900. In this areas by considering over burden thickness, lignite thickness, calorific

value and ash content the optimum spent time and cost to reach a minimum valuable ore

production is defined roughly.

Though high amount of W/O in this project a precise technical economical feasibility study must

be done in order to evaluate exploitation job before any other action this concept will get a

higher importance reminding that our reserve quality is not of a high CV coal.

54

9. REFRENCES

1. Geology seismotectonics and soil liquefaction susceptibility of Ilgin (west-central part of

Turkey) residential area Adnan Ozdemir, Ismail Ince , 2003

2. Quality, palynology, and palaeoenvironmental interpretation of the Ilgin lignite,

Turkey,A.I. Karayigit a,), F. Akgun b, R.A. Gayer c, A. Temel, 1998

3. Properties of lignite from the Konya-Ilgin-Çavuºçu deposit and its potential use in a

future power plant (Turkey), Hulya Inaner, 2005

4. The 2014 SME Guide

5. Australian Guidelines for the Estimation and Classification of Coal Resources, 2014

6. http://www.turkishweekly.net, HalukDireskeneli, Ankara-based energy Analyst