Embed Size (px)
Citation preview
KOTZE, A. P.L. and BRINK, V. d S. Computer support in schedulin g the heor Grootegeluk coal min e ~ · A case ~tudy. APCOM 87. Proceedings of the Twentiet h International Symposium on the AI)plication or Compulers a nd Mathematics in the Mineral Industries. Volume I: Mining. J ohan nesburg, SA IMM, 1987. pp. 221 -· 229.
Computer Support in Scheduling the Iscor Grootegeluk Coal Mine A Case Study
A.P.L. KOTZE and V. d S. BRINK
l scor Limited, Pretoria, Soulh Africa
Modelling and scheduling for Grootegeluk coal mine, situated in the northwestern Transvaal, is by means of a series of modular systems. Modelling of the multilayered body, which is part of the Waterberg coalfield , was based on a detailed study o f the behaviour o f coal and waste qualitie.s and the subsequent use of standard geostatistical techniques. A notable improvement on previous methods was attained. Scheduling procedures and systems were developed to model a multi bench pit producing coal for several mctallurgical plants as well as a power-station. Schedu ling was done by producing a series of longitudinal cuts, the cuts being subdivided inlo increments. By a llocating cuts to (.:ertain periods, the resulting calculated product tonnages were compared with production targets, and by iteration a final scheduling sequence
was determined.
lntroduction The Grootegeluk coal mine is situated in the Waterberg coalfield in the north-western Transvaal (see Figure 1). The mine is owned and operated by The South African Iron and Steel industrial Corporation, Limited (Iscor). !scar is the largest producer of steel in South Africa. The Grootegeluk coal mine is an opencast mine currently mining a succession of thin coa l and shale layers to produce blend coking coal for hcor and coal suitable for use in a power-station as a secondary product (see Figure2). The mining is presently confmed to the top 50 m of a total 120 m succession of thin coal and shale layers.
The Electricity Supply Commission (Escom) operates a number of power-stations in South Africa as well as the national eJe<:tdcity supply network. Esconi awarded Iscor the contract to supply coal fo r its new Matimba power-station. The fact that the contract had been given to Iscar, as well as changing technology in steel-making processes, necessitated the re-evaluation of the GrootegeIuk mine plan and the development of a method which would facilitate the rapid updating of the plan.
At full production approximately 29 x 106 tons ROM will be mined per year at the Grootegeluk coal mine from which 1,976 x 106 tons of coking coal and approximately 12 x 106 tons of power- station coal will be produced. In add ition, approximately 12.5 x Ht' tons of overburden and internal waste will be mined. Tables I and 2 show some of the parameters that had to be taken into account in the scheduling of the pit development.
The purpose of this paper is to illustrate how a straightforward approach to the computational aspects of the problem can lead to good results at low cost. Computer-
ization of the problem proved to be a valuable tool in attaining sound geological models and for creating detailed short- and long-term plans.
Geological modeUing The coal at the mine is part of the Upper and Middle Ecca groups. The Upper Eeea consists of approximately 60 Ol of thin (2 - 3 cm) bright coal layers interbedded with shale, sandstone and carbonate lenses, and is referred to as zones 1 t - 5. The Middle Bcca coal consists o f fi ve separate seams and is referred to as zones 4, 4a, 3, 2 and 1 (see Figure 3).
In general the zones 11 - 6 are coal of blend coking quality and of a low P20S content. Zone 5 is al~o blend coking coal, but the P~O, content renders it unsuitable for metallurgical use. Zones 4-1 are non-coking coal, occurring as thick coal seams with a calorific value relatively higher than that of zones 11 - 5 (see Figure 3). A potential use for the coal in direct reduction processes may also exist.
A few major faults occur in the Waterberg coalfie ld, Th e most important is the Daarby fault with a displacement of 350 m to the east, This fault forms a natural boundary for mine operations. All surface structures are therefore located on the eastern side of the fault. Numerous small fau.lts occur within the mine area with displacement of less than lO m. The mapping and prediction of these faults in the unmined areas is very difficult owing to the lack of surface exposure.
!scor maintains an extensive geological da ta base. The data base is c.reated and updated by means of micro-
SC HEDULING THE ISCOR OROOTEGELUK COAL MINE 221
,
ZIMBABWE I
BOTSWANA MOCAMBIQUE
SOUTH WEST
AFRICA
CAPE PROVINCE
TRANSVAAL
O.F.S.
_ _ ~r-~-,-,~ Port Elizabet h
F IGU IH:! I. I.ocatio n map of (hI: Wlltcrbcrg coalfield
computers which arc used [0 input and validate the approximately J 500 geological descriptions and 300 proximate ash and petrographic analyses for each borehole. Data on cornpi clcd boreholes are transferred to the data base resid ent in a mainframe computer. The data base for the mine area alon e consists of 128 400 geological descriptions and 82 000 proximate analyses.
Geological modelling is a man-machine process. The CDC SEAMSYS system is used, the modelling process being ill this case accomplished in two phases. The first phase is to define und model mine benches. This is followed by a second phase aimed a t modelling the coal product values for each bench.
Modelling mine benches To model mine benche.~ mining ho rizons must be selected. The mining horizons are selected mannally and, togethcr with the current structural interpretation, entered into the mainframe computer. As a first step structural modelling is done with the CPS/ I system by mean~ of fine gridding using the faults as boundaries. Numerous dummy boreholes are added 10 facilitate the construction of an accurate structural model. After a series of gridding, contouring, section' plotting and re-updating runs the final acceptable grids of lhe mining horizons are stored.
Modelling coul product values The mining horizo ns are applied to each borehole and the analysis for each horizon is extracted. A direct loga-
222
rithmic cu rve fitting method was developed to replace the previously used lagrangian method. This new, more acceptable interpolation technique is used to interpolate the composite washability curves. The aim is to obtain a product with an ash value of lO,4O"Jo for benches 2, 3 and 4.
Files are created with products of each horizon for each borehole. A block seam structural model is then created by loading the structural grids into the predefined seam model.
The biggest single obstacle in the past proved to be the interpoiaLion of product yield values (see Figures 4,5 and 6). The predicted values did not correlate well with the actual results achieved. The problem, especially for bench 2, proved to be related to the drastic effect of the interbedded waste, where thicknesses vary dramatically over short dista nces.
The yield variabilit y of the coal fraction alone is very low. The interpolat ion o f single samples or the separation of coal and shale proved to be very cumbersome. The final resu lts were obtained by using a product yield value with all material compositcd for each bench and each borehole as a point value.
Experimental semivariograms were constructed and, after filtering values of uncenain quality, acceptable semivariograms were found. Spherical models were fitted and a remarkable improvement in the quality of prediction was noted. Res ults were tested by using the point kriging method. A ft er using these models the yield product values are kriged and interpolated into the seam block model.
M I NING: MINE PLANNING CASE STUDIES
;
en
Cl fii o c c: z Cl II m
c;; 8 '" Cl '" ~ o m
r C " ~ r ~
Z
m tl
Faul
t
+
• •
• +
•
+
• +
+
.-...
.. -
+
+
+
+
• +
+
+
+
+
...
+
... +
+
+
+
+
•
+
+
+
... +
+
+
+
+
+
+
+
...
+
+
+
+
+
+
+
+
+
+
+
t'
+
+
+
+t+
++
++
+,=,
++
++
++
+
++
++
++
++
-+
+
++
+,+
+
+t+
++
++
++
+
++
++
+
++
++
++
++
+
++
+
++
++
++
++
++
+
++
++
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
',
-.
+
+
... ...
+
+
+
+
+
+
+
+
+ .+-~
+
+
+
+
+
+
+
+
+
+
+
+
+ ......
. ~~---=-~
f +
+
+
+
+
+
+
+
+
+
+
+
~
--------
····r
·· ...-/~~
.;.:->
.. ~
+
+
+
+
+
+
+
+
+
+
+ /,.
...,
~---=--
-+
+
+
+
+
+
+
+
+/r
J"_
-_-_
-D
aarb
y Fa
ult
+
+
+
+
+
+
+
+/.
/I_
-_--
.,++
++
++
+
+
+
LEGE
NDE
Faul
t
.-r
FAU
LT
r/
r++
l ~
STO
RMBE
RG
GRO
UP
I'7
'l
~
~ ~
~
O· . .
• • ~ ~
BEAU
FOR
T
GRO
UP
UPP
ER
E(C
A
)
MIO
DL
E
[(C
A
E(C
A G
RO
UP
Low
ER [
(CA
WAT
ERBE
RG
SU
PER
G
ROUP
coat
m
ine
KARO
O S
UPER
G
ROUP
FIG
UR
E 2
. G
eolo
gy o
f tb
e W
ater
berg
co
alfi
eld
and
loca
tion
of
the
Gro
ote
gelu
k co
al m
ine
N
~ ;:
z z p ;: ~ ." >
Z Z - ~ ~ ~ " ffi
OVE
R6'
.1F'ID
EN
~v'IE't--
---'
:'~;~:~
::':~
'-
lO
NE
5
I 16
.5
'.", ",
I ,,'
"
6,53
I
~e.~
'" I
'1.6
2
39."
5.5
4
"."
13
,54
21
.97
7,82
"."
~,5~
GRO
OTE
GEL
UK
CO
AL M
INE
CO
AL
ZOt£
S UT
IOllG
Y
fCl
C:r~
!e
r>OO"'t~ t>r
o· ....
.. w
Ntr
.ero
d in
~ppI'!"
1'(>11
m
udst
"""
.... ~...-
1\,:
1
'!7>\
ego
t tw
tll'lO
V!
Sld
tri1i
'/ n
, .. ,.
.,lul
l<!
.... "
" ,p
ey r
nu6s
lont
.w<
bane
.le ""'
_! ~c
m ~::
..
«<
It "
;In
. LU
ll-S
lden
te-
int~"Iec: .
... t~
· I c
orb
aro
;:-.
s s
Mle
. car
booo
.\"
IPnM
S :
';(;e
m.
lClO
\ Ift
d<
cool
OO
nds
,1\
ION
"-tlG
l!
,,\
bQ$e
-
I ,.,t
erc.
o.:o
leo
""t~
C~
OCl'
''''''
"""
", \
hod<
eo
o. M
p,
n IQ
wer
tp
:!
arL~ CO
O;,~
'Cf'
L"""
I.sicier;tt
(1\
bJse
. 1'''.~Q
ted
"",1
\ co
..t.;.
n"' ....
""s
~~>
<H.
thi(.
~' e
» b
cM~ in
"""
..,-r.
d.1
Brig
I'!!
eOOl
l .,
dtn
!-':
I~t. ",
Wrc.
<1~t
<!'d
I OS n.~ I
nn
to
r4 "
"n'l
e",~.6
!hoIe
,~
,,;<I<
'1:,Ii
: Ix
n:t
al ba~
~"'I
'<"I
so
d ....
il<:
in I
""",
IId
f.
I nH
!f(.
(JO
\fod
OS ~ l
hor.
baM~ W
Ith
I C<lI't>
QO
OC!
!OlJS
v.o
:" w
ith
lr.n
t
OO
b(
lroc
s ,1
\
low
.,
10Y0
tN'~
5.'ider;\~ ..
...
pr~m
",..
"t
CO
Ol
" ...
.. bt
'1"
10
""""
" in
c-
1.6m
wt'lo
cr.
~\t.
Os
low
0$
1'1 s
lgh
ltv
(:Q~
,f'9
cm
.
1- ~~
61.5
$
31.:.
... 37
):'5
33.0
0
30.5
3 'lO
O
SCH
EM
A1I
C
PR
ES
EN
TA
T
OF
P
IT
BE
NC
HE
S
I .lV
EII
A(;
E
Hlf
Ji'IJ
AR
EA
)
1'5." I
BEN:
H 1
OV
fRB
UR
OfN
~O.
2.~
• B
EN
CH
2 ~
BR
IGH
T
(Ol<
l
• l~Sn
'10
RD
. 1.
74
!"""
")'''
'J, a
OTT
Ut1
zlU
: 10
<
I
t:J.t
N..:
M ~
;c,,,, ~
BPI
GH
l CO
Al.
Ztl
B1
"6
11D.I
.!It>
I,"" I ~
!,N:H
S ////
///1
H
I(iH
PI
lOSF
"HOR
ClIS
[0
,1.(.
~O.I
.S!
FlG
UR
E 3
. L
ith
olo
gy a
nd m
inin
g be
nche
s in
the
Gro
oteg
elu
k co
al m
ine
,-
[ ~OOOll
l 51000 ( ~ ~ooc l ~,00(l
<,;I ,
~ @:jo L<; ~.
-~ ""'.( 0 / .'
~ 10.~~
[ -:J 0 11,0 C @ .---/
Q 12,0
( "'\ • 1).'O.~
, ( 51~ E 54001)
FIGURE 4. Coking coni )'jdd isolines - bench 2
E SlGGO
o
o o Or;;,
LTI2.o
Qo
o /
12,0
15 ,0 __
(,,/
,,-
r - 16IJooo
I ~ ·2M~~ ,
i " ,
~
M-l6UOOO
•
1 N -261l1XlO
£ S10~
,---.- -~ _ _ ~_._+M - 2622000 , "", £ , 61)00 ,,-FIGURE S. Cok ing coal yield isol in~ - bench 3
SCHEDULING THE ISCOR GROOTEGELUK COAL MINE 22,
, ,, ... ,,-~-~--~-r-~---',--~-~~-~--+" · nllwo
o o
o
,
o
o
N _16111)1)0 o
!1.~
n.
o
FIGURE 6. Coking coa l yield isolines - bench 4
TABLE J Pmd ucu and average yield5 and qu alities fo r the Grootegeluk coni mine
Coking coal:
Middlings product:
Power-station product:
Bench Yield Yidd Ash % MIIkg CV Yield Ash % M1Ikg CV
The pit
1 2 )
4 , 6 7 8 ,
10 11 12
20,19 43,2 13 ,88 39,8 1) ,) 7 40,9
Scheduling
37 ,2 37,2 31 ,2
Based on. the geological model and operating considerations, a pit layout as depicted in Figure 8 was eventually chosen.
The scheduling problem. The pit shown indicates a scheduling sequence. The development of the pit must be scheduled in such a way
226
19,5 65, 1 28,2 22, 1 19,5 50,9 29,7 21 ,4 19,5 51, 1 32,2 20,5
53,2 38,7 IB.8 90,. 34,. 20,6 23,6 45,4 16,2 78,8 33,2 20,9
90,0 24,3 24,0
90,. 22,7 24,5
!hal account is taken of:
the material volumes 10 the d ifferent plams (illustrated in Figure 7);
- the geometrical constraints in the pits; - the planning and utilization of plant capacities as well
as the smoothing of run-or-mine peak volumes to the plants; aspects of waste dumping and backfilling; product quality requirements (see Table I for average
MI NING: MINE PLA NNING CASE STUDI ES
TYPICAL GEOLOGICAL SECTION MATERIAL FLOW
Benche s
- Backfill ing
Overburden
1
Coal Waste - Backfilllng Coking coal
2 Cokina coal Iscor
Coal ~IGrootegeluk 1 f
Coking coal Middlinas
3
Coal Steam Droduct coal plant
4
5
6
7 8
9
1
1
1
0
1
2
Coking coal
Coal I Steam
1 1 plant
Coal -..l 1\
Shale ,
Shale
Coal
Sandstone
Coa l
Waste - Backfilling
Waste Backfilling
coal~ Product
-------- -~ ------ f----
Crusher Power plant
FIGURE 7. Relationship between geology and material flo w
yields and qualities and Table 2 for quality require-ments). •
Computer support to the mine planner As mentioned earlier, a coal modelling system is available in the Corporation. A scheduling system was, however, lacking. To provide computer scheduling support to the planner, a low-cost scheduler was developed.
The basic principles of the scheduler are as follows:
(a) The total area of the final pit was divided into segments, each segment being assumed to consist of material of a homogeneous quality. Figure 8 represents a typical segment division.
(b) The segments were generated by making lIse of a facility in the SEAMSYS package, namely that a
SCHEDULING THE ISCOR GROOTEGELUK COAL MINE 227
E 50000 E 52000 E 51000
+---~--~--~--~-~--~--~--~--~--~--~--~--~--tN _2b17000 E 54000 E 560~
N -2620000
+---~ _ _ ~_~ __ ~ __ ~_~ __ ~ __ ~ __ ~ __ ~ __ -r __ -r __ ~ __ +-N_1622000
E 52000 E 56000 E 571)00
FIGURE 8. Pit layout showing plan view or one bench with segments and cuts
TABLE 2 Quality requirements
Iscor: 1,976 X 106 lons coking coal per year.
Escom: Energy: 40 GJ per year per set (a set produces 600 kW); 6 scts must be phased in for an eventual total of 240 MGJ pcr year.
Quality: 20 to 22 MJ/kg, with a penalty applying below 20 MJ/kg and a bonus applying above 22 MJ/kg; 30 to 350?o ash, with a penalty applyabJe to an ash content exceeding 350"/0 ash and a bonus applicable to an as content below 30iJo.
polygon can define a bench outline and that two lines intersecting the polygon define a segment (sce Figure 8). The system is capable of generating a user specified number of cuts subdividing a segment (see Figure 8). Each cut is generated by the system as a closed polygon.
(c) Such a cut (polygon) is then evaluated against the
(d)
model to determine the tonnages of the different material types and qualities in the segment. Each cut, uriiquely defined by bench, segment and cut number relative to the segment, is stored with the information on material volumes and qualities as input to the scheduler.
(e) To keep the number of cuts in the system to manageable proportions, while maintaining scheduling accu-
228
racy, the concept of increments was introduced. Each cut is considered to consist of a number of increments of equal value, say 1 ODD, as determined by the user.
(t) The data for the scheduler consist of the cut values and target values planned for each period.
(g) The scheduler is driven by a file specifying the number of increments to be used for each level for a specific period. From Figure 8 it can be seen that the cut sequence in scheduling is implied by the way the cuts are generated.
The logical working of the scheduler is as follows: For a specific period:
(h) Use the number of cuts and partial cuts as specified by the number of increments for the period.
(1) Accumulate matecial volumes and amage the qualities per material type. The material flow as depicted in Figure 7 was simulated in the accumulation process.
(j) Report the totals against target values for the period. (k) If the target value for coking coal for a specific period
is reached - allocate the material from the coking coal benches to the steam plant.
Repeat for all periods.
By modifying the number of increments to be used from a specific bench for a specific period, different schedules can be considered.
By means of this scheduling system the user can consider a large number of different schedules for opening the mine, and he is then in a position to choose the best schedule from the various alternatives generated.
MINING: MINE PLANNING CASE STUDIES
Conclusion The scheduling system was developed at a low cost - in the order of 400 man-hours over a period of about two months. T his was accomplished by determining the minimum practkal requirements or the system and full y utilizing modules of existing systems in the Corporat ion.
The approach as outlined in the paper was used to schedule at least two long-term mine plans fo r Grootegeluk and is still in use. It wa~ found that it gave good practical results, and the plan ning engineers were able to ::ichcdu le a num ber of alternatives in order to be able to determine a 'best evaluated optio n'. The facility to evaluate different options Cllso provided the planning engin-
eers with tlle opportunity to develop a feel fo r the characteristics of a good pit developmen t sequ ence.
T he solut ions finally accepted mct requirements as to pit geometry, material volumes and quality.
Based a ll the experience gained with this system bear is presently developing a scheduling system for both shortand long-term planning al Groategeluk.
Acknowledgement The auth ors wish to thank the Management of Iscor for their support and permi.-.sion to pu blish this paper, an d acknowledge the assistance and construct ive comments of their colleagues during its preparation.
SCHEDU LI NG THE ISCOR GROOTEGELUK COAL MINE 229
