Aplikasi Software untuk Perencanaan Tambang
Written by Boss Tambang Saturday, 11 September 2010 11:24
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Worldwide Network
Datamine Group menyediakan pelayanan dan support penuh dari 10 regional support offices ditambah dengan pelayanan terbatas dari 7 agencies yang tersebar di seluruh bagian dunia. Dilengkapi dengan staff yang terdiri lebih dari 80 professional engineers, geologists and programmers. Pelayanan yang kami tawarkan tersedia dalam berbagai bahasa sesuai dengan kebutuhan lokal.
Perth, Australia
Brisbane, Australia
Jakarta, Indonesia
South Africa
India
Canada
United States
Brazil
Chile
Peru
International
Cement / Industrial
Russia
China
Poland
Germany
Iran
Kazakhstan
Berikut ini Users dari Software Datamine dan Earthworks di Indonesia :
PT Aneka tambang, UBPE Pongkor
PT INCO, Soroako
PT Avocet, Kotamobagu
PT Pama Persada Nusantara
PT Timah
DJPU
PPTM, Bandung
PT Newcrest mineral
PT Semen Cibinong
PT Semen Gresik
Dalam pelayanan jasa data processing (consulting) ini, beberapa pekerjaan yang pernah ditangani menggunakan software Datamine dan Earthworks antara lain :
1. Metal mining :
a. Perhitungan cadangan nikel P. Gee, P. Pakal, P. Buli untuk PT aneka tambang
b. Perhitungan cadangan nikel blok P1, P2, P4, P5 dan P8 pulau Halmahera untuk PT Aneka Tambang
c. Pemodelan Cadangan emas, PT Dwi Tunggal Inti Sakti
d. Perancangan sistem kontrol kadar terintegrasi PT Aneka Tambang UBPE Pongkor
e. Perhitungan cadangan nikel blok A (Mornopo), pulau Halmahera untuk PT Kasuari Indonesia.
2. coal Mining :
a. Perhitungan Cadangan batubara daerah Binungan, untuk PT Pama Persada Nusantara
b. Perhitungan Cadangan Batubara Cirenti, PTBA
c. Perhitungan Cadangan Batubara (Checking), PT Arutmin Indonesia
d. Perhitungan Cadangan Batubara, PT Vietmindo Energitama
e. Perhitungan Cadangan Batubara dan Perancangan Pit Limit Daerah Simpang Pasir, PT Insani Bara Perkasa
f. Perhitungan Cadangan Batubara dan Perancangan Pit Limit Blok 2 Sungai Merdeka, PT Indocoal Pratama Jaya
g. Perencanaan eksplorasi detail batubara untuk PT SMJ
h. Sedang melaksanakan penyusunan dan review FS Batubara untuk PT SMJ, PT TMJ, dan PT Tambang Damai
3. Industrial Mining :
a. Eksplorasi detail dan perhitungan cadangan Bentonit, PT Gunung Sari Indah, Bogor.
b. Perhitungan Cadangan Batugamping, PT Semen Cibinong
c. Perhitungan Cadangan Batu Andesit, PT Bumi Cikeupeul Abadi
d. Perhitungan Cut and Fill (Proyek Sipil), PT Killborn Pakar Rekayasa
e. Dan beberapa jasa consulting yang lain
4. Training-training :
Beberapa training di Jakarta dan Bandung maupun di beberapa perusahaan tambang seperti :
Di Direktorat Jenderal pertambangan Umum (DJPU), PPTM Bandung, PT Timah Bangka, PT Aneka Tambang Pongkor, PT Semen Cibinong, PT Semen Gresik, PT Newcrest Minerals Halmahera.
Materi-materi training meliputi :
Pemodelan Badan Bijih, Pemodelan Batubara, Penaksiran Kualitas/Kadar dan Perhitungan Cadangan, Geostatistik serta Pit Design
The Datamine Solution From Deposit to mine Planning
Pengerjaan Data Tambang Data Processing
Data Processing
A. Validasi Data
Tujuan dari tahap ini adalah untuk memeriksa kualitas dan ketepatan data awal. Hal ini sangat penting untuk mendapatkan hasil/output yang akurat dan tepat.
Prinsip dasar data yang berlaku dalam Data Processing adalah :
Garbage In, Garbage Out >< Best In, Best Out
Sehandal apapun software yang digunakan, operator yang menjalankan, ataupun engineer yang menganalisa …
Jika data masukan yang digunakan tidak benar, maka hanya akan dihasilkan output yang tidak tepat pula
Oleh karena itu disamping kehandalan software, operator maupun engineer …
Data yang benar dan valid, sangat diperlukan untuk mendapatkan output yang tepat dan akurat
Beberapa contoh kasus/masalah yang sering muncul tentang validitas data tambang
a. Data topografi yang tidak sesuai dengan kondisi aktual di lapangan.
Hal ini biasanya disebabkan oleh teknik surveying yang kurang baik atau grid pemetaan yang kurang mewakili.
b. Ketidaksesuaian antara koordinat collar drillhole, outcrop dan topografi.
Seringkali disebabkan oleh koordinasi yang kurang baik antara tim survey, tim geologi dan tim pemboran pada tahap eksplorasi. Hal ini dapat menyebabkan terjadinya penyimpangan lokasi bor di mana jika tetap digunakan dalam pemodelan menghasilkan korelasi yang tidak tepat pula.
Kurang rapatnya spasi sampling/pemboran
c. Untuk tahap perencanaan dan perancangan tambang seharusnya didukung dengan data yang cukup/memadai agar didapatkan hasil perhitungan dan penaksiran dengan tingkat kepercayaan yang tinggi. Namun dengan alasan penghematan biaya, seringkali hal ini tidak dipenuhi.
d. Pola pemboran yang salah, dan sebagainya.
B. Korelasi Orebody atau Seam
Korelasi dilakukan untuk mendapatkan gambaran 3D dari orebody, seam ataupun layer dari suatu cebakan bahan galian tambang menggunakan data penembusan sampel/drillhole atau yang biasa disebut dengan assay log drillhole.
Data-data assay yang memiliki karakteristik dan zona yang sama dihubungkan secara interpolasi dan ekstrapolasi sampai batas pengaruh yang ditentukan. Dalam hal ini ketepatan zone mineralisasi ataupun kode seam/layer, yang biasanya didefinisikan oleh geologist yang berkompeten serta memahami pola mineralisasi ataupun struktur geologi setempat, merupakan kunci utama dalam menghubungkan boundary dari cebakan bahan galian terkait. Kesalahan interpretasi zona atau kode geologi akan menyebabkan terjadinya penyimpangan hasil korelasi terhadap kondisi aktual.
Korelasi String dan Wireframe pada Software Datamine berdasar drillhole
C. BLOK MODELLING
Dewasa ini teknik pemodelan blok banyak diterapkan dalam metode pemodelan dan perhitungan cadangan mineral pada industri pertambangan. Teknik ini pada umumnya telah dilakukan secara computerized.
Pembagian sumberdaya/cadangan dalam blok-blok ini mampu memudahkan kita dalam melakukan penaksiran kualitas dan kualitas sehingga dapat dihasilkan sebaran kualitas dengan detail lokasi (koordinat) dan volume satuan blok yang disesuaikan dengan dimensi penambangan
Pada umumnya ukuran blok merupakan fungsi geometri endapan dan disesuaikan dengan sistem penambangan yang digunakan.
Konstruksi Model Blok dalam Datamine
Hal-hal yang perlu diperhatikan dalam konstruksi model blok :
a. Batas-batas koordinat x, y dan z maksimum dan minimum.
b. Penerapan subcell, di mana suatu model blok akan dibagi menjadi beberapa unit yang lebih kecil. Hal ini biasa dilakukan pada dimensi cebakan yang kompleks.
c. Penentuan ukuran model blok.
Didasarkan pada geometri cebakan yang diselidiki dan disesuaikan dengan dimensi unit penambangan/blok penambangannya. Pada penerapan subcell, maka dimensi subcell ini harus disesuaikan dengan unit penambangan terkecil (smallest mining unit) yang bisa dirancang sesuai dengan metode penambangan yang diterapkan serta ukuran alat yang digunakan.
Parent Cell Splitting
Filling plane
Cell splitting can be done along any axis in the model. When you use a constraining boundary, such as a perimeter or wireframe, you can also define a filling plane to control the direction of the seam splitting.
For example, if you set the filling plane to 'XY' then the process will create the specified number of subcells in both the X and Y directions. In the third axis the cell size will be calculated using seam filling. With seam filling the cell dimension is set automatically so that it precisely fits the perimeter or wireframe boundary. Thus, careful selection of the filling plane is important in providing the best possible modeling of geological boundaries.
Rotated Block Models
A Rotated Model is one whose axes, and therefore cells, are rotated with respect to the coordinate system. It is particularly useful in the situation where you have a stratified orebody which is dipping and/or plunging. As you can see from the diagram Below the model cells provide a much better fit when the model Is rotated.
Using a rotated model aligned to one or more of the major axes used to model the structure or shape of a deposit has the following advantages:
a. a smaller number of subcells can be used;
b. the subcells provide a better fit to the boundary;
c. in particular circumstances there can be a small improvement in the grade evaluation.
PRINCIPAL OF SUPERPOSITION (William Smith)
“If one series of rocks lies above the other then the upper series was formed after the lower series unless it can be shown that the beds have been inverted as a result of tectonic action”.
a. Datamine Block modelling often mimics the key sequence of geological events which formed the deposit.
b. When one geological event overprints another they are modelled separately and the models are then later combined. The later event (model) is used to overprint the first.
c. Modelling structures separately means the cell dimensions and degree and style of subcelling can be optimised for each zone as required.
Geostatistics - Features
Variogram Calculation
Variogram calculation includes the following features:
a. Variograms and/or cross variograms for up to 24 different variables calculated in a single run.
b. Automatic calculation of indicator variograms based on cut-offs.
c. Key field option allows variogram calculation to be restricted by the specified key field eg rock type, or borehole identifier to give downhole variograms.
d. Optimization of sample search for fast calculation.
e. Variogram calculation includes normal, relative and lognormal variograms.
f. Directional variograms for up to 100 different azimuth/dip combinations calculated in a single run.
g. Optional rotated coordinate system ensures flexibility in definition of directions.
h. Smaller lag interval for smaller distances.
i. Options include angles of regularisation, cylindrical radius, lag tolerance, etc.
j. Output to a database file, and/or the print file together with summary statistics.
Mengapa digunakan Variogram?
Untuk mengetahui bobot pengaruh dari sample di sekitar terhadap blok yang ditaksir
The interactive variogram fitting process includes the following features:
a. Interactive model fitting, with mouse control
b. Multi-structure models
c. Choice of models: spherical, power (e.g. linear, exponential, gaussian or De Wijsian
d. Model parameters saved on file for direct input to kriging process
e. Graphical display of model parameters
Grade Estimation for Block Models
Grade interpolation into a block model includes the following functionality:
a. A choice of interpolation methods including Nearest Neighbour, Inverse Power of Distance, Ordinary Kriging, Simple Kriging, b. Lognormal Kriging and Multiple Indicator Kriging.
c. A consistent set of search volume and estimation parameters for all methods.
d. Optimization of sample searching to improve processing speed.
e. Multiple grades can be estimated in a single run.
f. The same grade can be estimated by different methods.
g. Different search volumes and estimation parameters can be used for the different grades.
h. Rectangular or ellipsoidal search volume with anisotropy.
i. A dynamic search volume allowing the volume to be increased if there are insufficient samples.
j. Restriction of the number of samples by octant.
k. Restriction of the number of samples by key field.
l. Estimation by zone, with separate parameters for each zone.
m. Wide selection of variogram model types for both normal and lognormal kriging.
n. Automatic transformation of data if the input model is a rotated model.
o. Unfolding option available for all estimation types.
p. Parent cell estimation.
q. Selective update of partial model.
Cross Validation - XVALID
The cross-validation process XVALID is designed to assist in the selection of parameters for grade estimation, using the cross-validation method. The input data file is the sample data which will later be used for estimating grades into a block model. For kriging it allows different model variograms to be tested and compared. For inverse power of distance it allows different powers to be compared.
The input to XVALID is consistent with the input required for the grade estimation process ESTIMA. In fact the three input parameter files are identical for the two processes.
The cross-validation method works by removing each point in turn from the data file and estimating its value from the remaining data. In this way a table of actual and estimated values is created. A detailed statistical analysis is then carried out comparing the actuals and estimates. One or more of the estimation parameters can then be changed and the process rerun to see whether the new parameters improve the results of the statistical analysis. The method is therefore iterative, requiring
several runs to establish the best set of parameters.
Cross Validation Optimization – XVOPT
Cross-validation is an iterative process – you make your first estimate, look at the stats, change one of the parameters, and try again to see if you improve the stats. XVOPT does all this for you.
You need to define an initial or base set of parameters as before, but you also specify a minimum and maximum for each parameter. Then you define a step size for discrete increments between the maximum and minimum. XVOPT then just loops round for all possible combination of parameters and calculates the statistics.
So what you also need to do is to define a sort of objective function. You specify weights for each statistic defining their relative importance, and penalty for the distance of the actual statistic from it’s target value. defining their relative importance, and a penalty for the distance of the actual statistic from its target value. The process then calculates the penalty for each run, weights them and finds the one with the lowest penalty points.
Interactive Variogram Fitting
a. The interactive variogram fitting process includes the following features:
b. Interactive model fitting, with mouse control
c. Multi-structure models
d. Choice of models: spherical, power (e.g. linear, exponential, gaussian or De Wijsian
e. Model parameters saved on file for direct input to kriging process
f. Display of model parameters on graphics screen
g. Auto scaling of display limits and grid interval as variograms are added or removed
h. Mouse selection of variograms to be shown or hidden
i. Automatic selection of perpendicular variograms
j. Legend control, including XYZ annotation of model axes
k. Legend includes cut-off grade for indicator variograms
l. User control of colour, line type and symbol for each variogram
m. Mouse selection of model axes
n. Optional display of number of sample pairs
o. Optional display of sample variance
p. Variogram point removed if insufficient pairs
q. Toggle between full grid and tick marks
r. Restructured menus for ease of use
s. Online help
Beberapa fasilitas yang lain dalam menu geostatistik Datamine Studio :
Multiple Indicator Kriging (MIK)
The only transform used in Multiple Indicator Kriging (MIK) is the transform from a grade to a 0 or 1. The Affine Correction Method is used to take the output file from ESTIMA and correct the grades for SMU size. Details of the Affine Correction Method are given in Applied Geostatistics by Isaaks and Srivastarva pages 471-472. (return to previous view)
Declustering Sample Data - DECLUST
Options:
a. Random Sample
b. Psuedo Random Sample
c. Sample Nearest Grid Center
d. Mean of Samples in Grid
Grade Estimation for Irregular Panels – PANELEST
The PANELEST command estimates the grade and variance of 2D or 3D panels. Panels are defined either as a set of strings, or as a set of 2D or 3D discretisation points. The interpolation methods available are nearest neighbour, inverse power of distance or kriging. In particular the process allows you to estimate a grade and a kriged variance for….
a. any perimeter, without the need to create a block model
b. a subset of cells from a block model.
c. an enclosed wireframe represented by a 3D array of points
The Datamine Solution From Deposit to mine planning
Pushback Design
Pushback design is typically an iterative process between NPV Scheduler and Datamine Studio. The initial pushback geometries are generated by NPV Scheduler and tested for feasibility in the optimizing scheduler. Once a suitable schedule and set of pushbacks have been generated, the pushback surfaces are exported to Datamine Studio for detailed design of benches and haul roads. The design surfaces can then be exported back to NPV Scheduler for scheduling. The cycle of pushback adjustments, scheduling and detailed design may be repeated several times before the design is finalized.
Strategic Open Pit Planning System
A. NPV Scheduler Overview
1. Ultimate Pit
2. Pushbacks
3. Schedules
4. Stockpiles
5. Cutoff Grade Optimization
6. Features
B. Methodology
C. Benefits
D. Cost Estimate
Earthworks NPV Scheduler comprises four main modules:
a. ultimate pit shell generator,
b. pushback generator,
c. optimizing scheduler, and
d. stockpile optimizer.
The optional Earthworks MineFlow Optimizer plug-in combines cut-off grade optimization seamlessly with these standard modules.
The user is guided through the operation of each module with a flow sheet style control panel which gives the user clear indication of the processing path and the options available at each step. These options include excellent 2D and 3D charting and contouring tools allowing the user to quickly validate and present the results of an optimization. NPV Scheduler is also supplied with the Earthworks Data Source Drivers for easy import and export of block models from Datamine, Vulcan, Medsystem, surpac, Micromine and generic text and SQL database files.
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Ultimate Pit
The ultimate pit optimizer is based on the industry standard Lerchs-Grossman method and features treatment of multiple ore types, multiple processing methods and multiple grades or products. Interactive tools are provided for creating slope region boundaries and surfaces, and definition of pit limit polygons. The user can specify a discount rate and mine production rate to generate a block extraction sequence which delivers the optimal net present value to the project.
Each block in the output model is individually numbered to show the theoretically best mining sequence. In a single optimization run, any number of pit phases can be generated using a value reduction factor. The pit phases provide a family of nested pits which indicate the sensitivity of the ultimate pit to cost-price variations. The sequence and phase numbers stored in the output model provide an excellent guide to any first pass manual design of interim pits.
Pushbacks
The pushback generator is used to build a practical series of interim pits or pushbacks which follow the optimum extraction sequence as closely as possible. The user can specify the size of each pushback in terms of cash value, or tons of ore and waste, or by recovered product.
Pushback runs can be unconstrained i.e. the program uses only the optimal extraction sequence to construct the pushbacks, or, the user can interactively force or restrict mining in specified pushbacks within polygonal limits or by depth.
Schedules
The optimizing scheduler module is controlled through a series of easy to follow dialog boxes in which the user specifies time flow, calendar, production and target parameters. Any attribute contained in the input model can be used to either measure time flow or define schedule targets. Targets may be defined in terms of either rates or ratios with user defined mathematical expressions. Targets such as mill feed, grade or stripping ratio can be quickly specified along with more complex expressions for ore blending, ore contamination and other multi-parameter targets.
Multiple targets can be specified and varied over the term of the schedule. The optimizer attempts to find the optimal schedule which satisfies all targets and, at the same time, maximizes the project NPV. If an optimal solution cannot be found, the scheduler will selectively relax targets until a viable schedule is obtained. Once obtained, schedules can be quickly charted or exported to a Windows spreadsheet program. The pit model generated contains the schedule period number for each block in the model. The model may also contain the sequence, phase and pushback numbers if these optional modules were used prior to scheduling. The output block model can finally be exported using the data source drivers as text or SQL tables, or in one of the many third party file formats available.
The Datamine Solution From Deposit to Mine Planning
Open Pit Design
Open Pit Design
There are many approaches to the task of surface mine design. Like Other functions within DATAMINE there is no fixed way in which you are forced to complete your design work. Rather, there are many general and specific tools for designing both surface mines, dumps and other types of surface excavations.
Preparing for a Detailed Pit Design
Before you can begin a detailed pit design in GUIDE you need to set up a few control parameters. These will allow you to specify the wall angles and berm widths.
There are several ways you can define the wall angles around a pit design.Which method you choose depends on the complexity of your design. These can be controlled by
a. Global Settings which sets constant values on the parameters
b. By reading values of a SLOPE field directly from a block model
c. Rosettes - a rosette is simply a 3-D point in space on which you have specified wall angles and berm widths on different azimuths. Each rosette controls the parameters for a specified minimum and maximum elevation range. Outside the range of influence of the rosette the global setting take effect.
Toe + Crest + Ramp Design Method
Alternative Pit Design Methods
Toe + Ramp Design Method
Contour Design Method
The Datamine Solution From Deposit to Mine Planning
Mine Schedule
Short Term Planning
Scheduling in Datamine Studio
The scheduling function in Datamine consists of three main parts:
a. Scheduling - allows manual scheduling
b. Face Advance - simulates mining ‘cuts’
c. Blending - automates both scheduling methods
Scheduling and Face Advance can be used independently or together and the Blending menu adds sophisticated linear programming optimization functionality to both Scheduling and Face Advance.
Scheduling – Setup
Classification of Material
The block model is classified into a number of categories. These categories can be based on grade, material type or a both. For example, waste, low grade, marginal etc.
The material for each category is then allocated a default destination. For example, waste sent to dump and low grade to the leach pad. Up to 10 different destinations can be defined and multiple targets can be defined for each destination
Calendar
A user defined calendar can be setup to represent the time unit of the schedule – daily, weekly, monthly etc.
Field Treatment
This sets the way in which fields are treated – for example, grades are tonnage weighted, while volume is accumulated.
Annotation
User defined annotation fields for example, time period in which a block is mined, or % of material mined from a particular mining block
Exposure Limits
Can be used to highlight areas of unscheduled blocks where material has still to be removed. This is extremely useful in an open pit, to ensure that material that has not yet been exposed, is scheduled.
Scheduling – Interactively
The scheduling panel can be broken into the following components:
The blocks panel on the left displays the tonnes and grade of the block to be scheduled
The panel along the top represents the time period that the mining takes place
The SCHEDULE panel, to the right of the blocks panel, displays the data in the schedule file. There are three ways of representing the data and this is controlled by the panel just above the SCHEDULE panel. This panel contains three buttons labeled DESTN, SCHEDULE and ATTRIBS. The default display is by destination. As in the BLOCKS panel different fields can be selected for display.
Scheduling - Face Advance
Datamine’s Face Advance can be used to simulate the advance of production faces or mining units to build up alternative mining schedules. The module can be applied to a wide range of mining situations.
Sources of material other than production faces, such as stockpiles can also be included in the simulation.
The schedule is generated within a user defined calendar, enabling the system to be used for short, medium and long term scheduling.
Starting from a set of overall mine design perimeters, segments are defined on these perimeters which represent production faces. There may be more than one face on a perimeter, and a face may contain more than one segment. Faces are selected and given an advance rate. When scheduling is done the mining face is advanced forward and is used to generate two new perimeters - the mined portion and the unmined remnant. The mined portion is evaluated against a block model, if one is open, and the results stored in a database results file.
Some of the main features are :
a. Automatic evaluation of units as they are mined.
b. Automatic advance of multiple faces as time units are changed.
c. Stop mining on any unit at any time to simulate face or equipment shutdown for example.
d. Production rates variable within time periods.
e. Faces advanced perpendicular to the original face, or in a direction parallel to the side of the parent perimeter.
f. Advance by target distance or target tonnage.
g. Many undo facilities.
h. On screen annotation of fields such as time period in which unit was mined and percentage draw from tonnage zones gives easy to visualize current status of schedule.
i. Mine a single unit over a multiple number of time periods.
j. Highly customizable for individual requirements.
k. All results and schedules written to file for listing and reporting purposes.
l. Variable calendar definition.
Scheduling – Blending
Targets
Targets can be set on destinations, attributes or variables. In the example below, a target has been set on the tonnage and grade of material being sent to the plant.
Dependencies
Dependencies can be defined between pairs of blocks to indicate that one must be fully mined out before extraction can commence from the other one. The “red” arrows indicate the dependencies between the mining blocks
Blending
The results of the blending can be seen graphically on the schedule panel. The tonnage and grade targets are being met while honoring the dependencies on the mining blocks.
The Datamine Solution From Deposit to Mine Planning
Operational Mine Plan
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Makasih dan salam,
HR
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