Process Help

INDEST - estimate grades into a block model using indicator estimation

 

Process Name

Menu Path

Link to Command Table

INDEST

Command line only

Click here

 

Introduction

 

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The INDEST process uses the Indicator Estimation (IE) method to estimate grades into a block model using the cumulative distribution function (CDF) of indicator transformed sample grades.

How to use

To operate, INDEST needs a series of threshold values between the smallest and largest grade values. These threshold values, referred to as cutoffs, are used to numerically build the CDF of each block in the model. For each cutoff, data in the search volume are transformed into 0s and 1s: 1s if the data are greater than the threshold, and 0s if they are less than or equal. It then estimates the probability that the block grade is greater than the threshold value, using one of the standard estimation methods. This is usually kriging, but INDEST allows other methods such as Nearest Neighbour or Inverse Power of Distance to be used. Performing this operation for each cutoff across the range of the sample data approximates the CDF for the model cell. After the CDF is built, it is post processed to calculate the indicator estimated grade.

INDESTuses theESTIMAprocess to do the estimation for each cutoff.  For further details ofESTIMArefer to the help file and the Grade Estimation User Guide.

If you are using Indicator Kriging (IK) then you must already have calculated a variogram for each cutoff, and stored the models in the Variogram Model file. TheVGRAMprocess has specific features for calculating indicator variograms.

For each cutoffINDESTcalculates the following data which can optionally be stored in the Output Model file:

  • the proportion (fraction) of the model subcell which is above cutoff.

  • the grade of the proportion of the subcell which lies above cutoff.

The main output fromINDESTis the grade above a cutoff of zero, ie the indicator estimated grade of the total subcell.

Estimation Parameter File

In order to useINDESTyou must specify one record in the Estimation Parameter File &ESTPARM for each cutoff.  This requires the numeric field CUTOFF to be included in the file.

The *VALUE_IN field is the grade in the input sample &IN file to which the cutoffs are applied.  Note that this is different from the use of the *VALUE_IN field when using ESTIMATE for Indicator Estimation.

If the *VALUE_OU field is not specified then the *VALUE_IN field will be created in the output model file to hold the indicator estimated grade.  If a *VALUE_OU field is specified in the first record of the Estimation Parameter File, then this value will be used for the indicator estimated grade in the output model file

You can only estimate one set of indicators in a single run.  In other words all the VALUE_IN fields must be the same.  Also when using INDEST you cannot estimate a grade using non indicator methods in the same run.

If you are using zone control then you must explicitly specify all combinations of zone field(s) in the Estimation Parameter File.  You cannot use the option that is available in ESTIMA that allows you to specify an absent data zone field value that then applies to all zones that are not explicitly identified in&ESTPARM.

If you are using zone control then you may use different cutoffs for different zones. However the PRABn and GRABn fields in the output model file must then be handled very carefully! The maximum number of cutoff values is 24.

Fields for indicator estimation:

  • BINGRADE: Used when GRMETHOD=4 to set the grade below the cutoff

  • ABVGRADE: Sets the grade above the cutoff (only used for the top bin)

Grade Above Cutoff

The calculation of the grade above each cutoff requires that the average grade between each successive pair of cutoffs be specified. For example if cutoff grades of 2, 5, 6.5 and 9.5g/t are selected then average grades are required for the ranges:

       From        

To

0

2

2

5

5

6.5

6.5

9.5

9.5

 

Four methods are available to specify the average grade for each range, controlled by parameter @GRMETHOD:

GRMETHOD       

Description

1

Average of minimum and maximum cutoff values.  The grade above the highest cutoff is calculated as the highest cutoff plus half the difference between the highest and second highest cutoffs.

2

Calculated by INDEST from the grades of the samples in the &INfile.

3

Calculated by INDEST from the grades of the samples in the &IN file. However for the top bin (above the highest cutoff) the median grade is calculated.

4

Values are specified by the user, using the BINGRADE and ABVGRADE fields in the &ESTPARMfile.  The  BINGRADE field contains the grade below the cutoff and the ABVGRADE field the grade above the cutoff.  The ABVGRADE field is therefore only used for the top bin.

 

GRMETHOD of 4 is illustrated in the following table:

       CUTOFF     

BINGRADE

    ABVGRADE     

2

1.3

-

5

3.6

-

6.5

5.7

 

9.5

7.8

11.1

The values used by INDEST can be recorded by specifying an output &AVGRADES file.

Indicators 

Indicator values are calculated for each sample in the input sample &IN file for each cutoff.  An indicator takes the value:

 0 ‑ the grade is less than or equal to the cutoff.

 1 ‑ the grade is above the cutoff.

 The indicator values can be saved by specifying an output &INDICATE file.

 Output Model 

Fields PRAB1 ... PRABn will be created in the Output Model file to store the proportion of the subcell above each cutoff.  These are calculated directly byESTIMA.  Then the fields GRAB1 ... GRABn are calculated during the post-processing to store the corresponding grade above each cutoff.  The grade above cutoff values (GRABn) are calculated from the proportion and average grade between each pair of cutoffs.  For example:

Cutoff Number  

    Cutoff     

   PRABn     

Calculation  

4

9.5

0.1

GRAB4= 11.1                (This figure is taken directly from the ABVGRADE field)

3

6.5

0.3

GRAB3= {0.1x11.1 + (0.3‑0.1)x7.8} / 0.3   =   8.9

2

5

0.6

GRAB2= {0.1x11.1 + (0.3‑0.1)x7.8 + (0.6‑0.3)x5.7} / 0.6   =   7.3

1

2

0.85

GRAB1= {0.1x11.1 + (0.3‑0.1)x7.8 + (0.6‑0.3)x5.7 + (0.85‑0.6)x3.6} / 0.85   =   6.21

0

0

1

Indicator Grade=0.1x11.1 + (0.3‑0.1)x7.8 + (0.6‑0.3)x5.7 + (0.85‑0.6)x3.6 + (1.0‑0.85)x1.3   =   5.30


The PRABn and GRABn fields will be stored in the output &MODEL file if parameter @PGFIELDS is set to 1.

Order Relation

One of the main drawbacks of the indicator estimation method is the Order Relation Problem.  This will occur if the proportion of the subcell above cutoff n is estimated to be less than the proportion above cutoff n+1.  ie PRAB(n) < PRAB(n+1).  Three options are available to correct for this, controlled by parameter ORDER:

=1: Downwards.
=2: Upwards.
=3: Average of methods 1 and 2.

 The recommended method (and default) is 3.


Files, Fields and Parameters

Input Files

Name

I/O Status

Required

Type

Description

PROTO

Input

Yes

Block_Model_File

Input model prototype. This is a standard block model file containing the 13 compulsory fields. It may also contain the rotated model fields. If it includes cells then it must be sorted on IJK.

IN

Input

Yes

Undefined

Input sample data. This must contain X,Y and Z fields and at least one grade field.

SRCPARM

Input

Yes

Undefined

Search volume parameter file. This contains 24 compulsory fields defining the search volume and the number of samples needed for grade estimation.

 More than one search volume may be defined. All fields are numeric:

  • SREFNUM: Search volume reference number.

  • SMETHOD: Search volume shape.

    • 1 = 3D rectangle

    • 2 = ellipsoid.

  • SDIST1: Max search distance in direction 1.

  • SDIST2: Max search distance in direction 2.

  • SDIST3: Max search distance in direction 3.

  • SANGLE1: First rotation angle for search vol.

  • SANGLE2: Second rotation angle.

  • SANGLE3: Third rotation angle.

  • SAXIS1: Axis for 1st rotation (1=X,2=Y,3=Z).

  • SAXIS2: Axis for 2nd rotation (1=X,2=Y,3=Z).

  • SAXIS3: Axis for 3rd rotation (1=X,2=Y,3=Z).

  • MINNUM1: Min number of samples, 1st search vol.

  • MAXNUM1: Max number of samples, 1st search vol.

  • SVOLFAC2: Axis multiplying factor,2nd search vol.

  • MINNUM2: Min number of samples, 2nd search vol.

  • MAXNUM2: Max number of samples, 2nd search vol.

  • SVOLFAC3: Axis multiplying factor,3rd search vol.

  • MINNUM3: Min number of samples, 3rd search vol.

  • MAXNUM3: Max number of samples, 3rd search vol.

  • OCTMETH: Octant method flag.

    • 0 = no octant search,

    • 1 = use octants.

  • MINOCT: Minimum number of octants to be filled.

  • MINPEROC: Minimum number of samples in an octant.

  • MAXPEROC: Maximum number of samples in an octant.

  • MAXKEY: Maximum number of samples with the same key value within an octant.

ESTPARM

Input

Yes

Undefined

Estimation parameter file.

Each record in the file describes an estimation method and its associated parameters. The fields are dependent on the estimation methods selected. All fields are optional except for VALUE_IN, SREFNUM and CUTOFF. General fields:

  • VALUE_IN: Grade field to be estimated.

  • SREFNUM: Search volume reference number.

  • CUTOFF: Cutoff grade for indicator calculation.

  • VALUE_OU: Output indicator estimated grade field to be created in MODEL (Default is VALUE_IN). The required field name must be specified in the first record of the Estimation Parameter file. Values in subsequent records will be ignored.

  • {ZONE1_F}: A/N 1st field for zonal estimation. The actual name of the field is given by the ZONE1_F field.  e.g. ZONE1_F(ROCK).

  •  {ZONE2_F}: A/N 2nd field for zonal estimation.

  • NUMSAM_F: Field to be created in MODEL for the number of samples.

  • SVOL_F: Field to be created in MODEL for dynamic search volume number.

  • VAR_F: Field to be created in MODEL for variance of estimate.

  • MINDIS_F: Field to be created in MODEL for distance to nearest sample.

  • IMETHOD: Estimation method.

    • 1 = Nearest neighbour (NN).

    • 2 = Inverse power of dist (IPD).

    • 3 = Ordinary kriging (OK).

    • 4 = Simple kriging (SK).

    • 5 = Sichel's t estimator.

Fields for IPD:

  • ANISO: Anisotropy method:

    • 0 = no anisotropy.

    • 1 = use search vol anisotropy.

    • 2 = use ANANGLEn.

  • ANANGLE1: N Anisotropy angle 1.

  • ANANGLE2: N Anisotropy angle 2.

  • ANANGLE3:N Anisotropy angle 3.

  • ANDIST1: N Anisotropy distance 1.

  • ANDIST2: N Anisotropy distance 2.

  • ANDIST3: N Anisotropy distance 3.

  • POWER: N Power of distance for weighting.

  • ADDCON: N Constant added to distance.

Fields for kriging:

  • VREFNUM: Variogram model reference number.

  • LOG: N Lognormal variogram flag. 0 = normal kriging. 1 = lognormal kriging.

  • KRIGNEGW: N Treatment of -ve weights: 0 = -ve weights kept and used. 1 = ignore samples with -ve weights

  • KRIGVARS: N Treatment of variance > sill: 0 = write variance to MODEL. 1 = set variance to sill. Fields for lognormal kriging:

  • GENCASE: N Calculation method: 0 = Rendu's method. 1 = General case.

  • DEPMEAN: N Deposit mean [If 0 then use kriged estimate]. Fields for general case:

  • TOL: N Tolerance for convergence.

  • MAXITER: N Maximum number of iterations. Fields for simple kriging:

  • LOCALMNP: N Method for calculation of local mean: 1 = use field defined in PROTO 2 = use mean within search vol.

  • LOCALM_F: Name of local mean field in PROTO; used if LOCALMNP=1

Fields for indicator estimation

  • BINGRADE: Used when GRMETHOD=4 to set the grade below the cutoff

  • ABVGRADE: Sets the grade above the cutoff (only used for the top bin)

VMODPARM

Input

No

Variogram - Model

Variogram model parameter file. Each record in this file defines a variogram model type and its parameters. Only the VREFNUM field is compulsory.

  • VREFNUM: Model variogram reference number.

  • VANGLE1: Variogram anisotropy angle 1.

  • VANGLE2: Variogram anisotropy angle 2.

  • VANGLE3: Variogram anisotropy angle 3.

  • VAXIS1: Model variogram rotation axis 1.

  • VAXIS2: Model variogram rotation axis 2.

  • VAXIS3: Model variogram rotation axis 3.

  • NUGGET: Nugget variance.

  • ST1: Variogram model type for structure 1.

    • 1 = Spherical.

    • 2 = Power [eg 1 - linear].

    • 3 = Exponential.

    • 4 = Gaussian.

    • 5 = De Wijsian.

  • ST1PAR1: 1st parameter of structure 1 [Range 1 for spherical model].

  • ST1PAR2: 2nd parameter of structure 1 [Range 2 for spherical model].

  • ST1PAR3: 3rd parameter of structure 1 [Range 3 for spherical model].

  • ST1PAR4: 4th parameter of structure 1 [C variance for spherical model].

  • STn: Variogram model type for structure n. STnPARp pth parameter for structure n, where n<=9.

Output Files

Name

I/O Status

Required

Type

Description

MODEL

Output

No

Block Model File

Output model containing estimated grades, variance etc.

AVGRADES

Output

No

Undefined

Output file containing cutoff grade ranges and average grade used for each range.  It will include zone field(s), if any, plus the following fields: BIN:  bin or grade range number LO_CUT:  lower cutoff grade UP_CUT:  upper cutoff grade NSAMPLES:  number of samples in IN file lying within the bin BINGRADE:  bin grade used for indicator kriging.  This is dependent on the GRMETHOD parameter . SAMPMEAN: mean grade of samples in IN file lying within the bin 

INDICATE

Output

No

Undefined

Output indicator file.  This is a copy of the sample input IN file, but also includes the 0/1 indicator values for each cutoff

SAMPOUT

Output

No

Undefined

Output sample file containing details of weights for each sample for each cell estimated.

Fields

Name

Description

Source

Required

Type

Default

X

X coordinate of sample data in IN file. If not specified, then X is assumed.

IN

No

Numeric

Undefined

Y

Y coordinate of sample data in IN file. If not specified, then Y is assumed.

IN

No

Numeric

Undefined

Z

Z coordinate of sample data in IN file. If not specified, then Z is assumed.

IN

No

Numeric

Undefined

ZONE1_F

First field for zonal control.

IN

No

Any

Undefined

ZONE2_F

Second field for zonal control.

IN

No

Any

Undefined

KEY

Key field used to specify the field limiting the number of samples for estimation. The field must exist in the IN file.

IN

No

Numeric

Undefined

LENGTH_F

Field used for length weighting in IPD. The field must exist in the IN file.

IN

No

Numeric

Undefined

DENS_F

Field used for density weighting in IPD. The field must exist in the IN file.

IN

No

Numeric

Undefined

Parameters

 

Name

Description

Required

Default

Range

Values

DISCMETH

Cell discretisation method:

Option

Description

1

- use XPOINTS , YPOINTS , ZPOINTS to define the number of points in the X,Y,Z directions.

2

- use XDSPACE , YDSPACE , ZDSPACE to define the distance between points. The default is method (1).

No

1

1,2

1,2

XPOINTS

Number of discretisation points in X. (1)

No

1

Undefined

Undefined

YPOINTS

Number of discretisation points in Y. (1)

No

1

Undefined

Undefined

ZPOINTS

Number of discretisation points in Z. (1)

No

1

Undefined

Undefined

XDSPACE

Distance between discretisation points in X if DISCMETH=2. The default gives just one point.

No

Undefined

Undefined

Undefined

YDSPACE

Distance between discretisation points in Y if DISCMETH=2. The default gives just one point.

No

Undefined

Undefined

Undefined

ZDSPACE

Distance between discretisation points in Z if DISCMETH=2. The default gives just one point.

No

Undefined

Undefined

Undefined

PARENT

Flag to control parent cell estimation:

Option

Description

0

- Estimate into individual subcells.

1

- Represent parent cell by a full 3D matrix of points.

2

- Represent parent cell by a 3D matrix of points, but select only points lying within subcells. The default is (0).

No

0

0,2

0,1,2

MINDISC

Minimum number of discretisation points. Only used if PARENT=2. The default is (1).

No

1

Undefined

Undefined

COPYVAL

Flag controlling copying of values from PROTO to MODEL if there is insufficient data to estimate them:

Option

Description

0

- Assign absent data value[s] in MODEL.

1

- Copy from PROTO to MODEL. The default is (0).

No

0

0,1

0,1

FVALTYPE

Flag for cell size approximation for F values:

Option

Description

1

- The exact dimensions of the cell are used

2

- Each cell is approximated by one of a discrete number of cell sizes. The default is (1).

No

1

1,2

1,2

FSTEP

Step size for cell approximation. This is only used if FVALTYPE=2.

No

Undefined

Undefined

Undefined

XMIN

Minimum X value for model updating. The default is the X model origin.

No

Undefined

Undefined

Undefined

XMAX

Maximum X value for model updating. The default is the maximum X value for PROTO.

No

Undefined

Undefined

Undefined

YMIN

Minimum Y value for model updating. The default is the Y model origin.

No

Undefined

Undefined

Undefined

YMAX

Maximum Y value for model updating. The default is the maximum Y value for PROTO.

No

Undefined

Undefined

Undefined

ZMIN

Minimum Z value for model updating. The default is the Z model origin.

No

Undefined

Undefined

Undefined

ZMAX

Maximum Z value for model updating. The default is the maximum Z value for PROTO.

No

Undefined

Undefined

Undefined

XSUBCELL

Number of subcells per parent cell in X if PROTO is empty. The default is (1).

No

1

Undefined

Undefined

YSUBCELL

Number of subcells per parent cell in Y if PROTO is empty. The default is (1).

No

1

Undefined

Undefined

ZSUBCELL

Number of subcells per parent cell in Z if PROTO is empty. The default is (1).

No

1

Undefined

Undefined

ORDER

Order relation correction method:

Option

Description

1

Downwards.

2

Upwards.

3

Average of methods 1 and 2.

No

3

1,3

1,2,3

GRMETHOD

Method for specifying average grade within each cutoff range:

Option

Description

1

Average of minimum and maximum cutoff values.

2

Average calculated from samples in IN file. Mean grade for top bin.

3

Average calculated from samples in IN file. Median grade for top bin.

4

Specify values using BINGRADE and ABVGRADE fields in ESTPARM file.

No

3

1,4

1,2,3,4

PGFIELDS

Flag to select whether the proportion above cutoff fields (PRABn) and the grade above cutoff fields (GRABn) should be included in the output MODEL file:

Option

Description

0

Do not include the PRABn and GRABn fields.

1

Include the PRABn and GRABn fields.

No

0

0,1

0,1



Notes

It is also used by ESTIMATE.


Example

!INDEST &PROTO(modelb1),&IN(sampleb1),&SRCPARM(spar4),&ESTPARM(eparind),
        &VMODPARM(vmodelb),&MODEL(modelind),&AVGRADES(gradeind),
        &INDICATE(indind),*X(XPT),*Y(YPT),*Z(ZPT),*ZONE1_F(ROCK),
        @DISCMETH=1.0,@XPOINTS=3.0,@YPOINTS=3.0,@ZPOINTS=3.0,
        @PARENT=0.0,@COPYVAL=0.0,@FVALTYPE=1.0,@ORDER=3.0,
        @GRMETHOD=3.0,@PGFIELDS=0.0

 

Output Window:

 

 INDEST

Pre-processing data and model
ESTIMA TIME >22:20:12
ESTIMA - Grade Estimation
-------------------------
Initialization: Checking input files .............................
Initialization: Checking estimation parameter file ...............
Initialization: Checking zone fields .............................
Initialization: Creating estimation table ........................
Initialization: Checking model file ..............................
Initialization: Creating virtual files ...........................
Initialization: Storing data in memory ...........................
Initialization: Completed.

Estimation Table
----------------
Estimations will be carried out for the following combinations of grade and
zone fields:
     Sample     Output    Zones ..................... Search  Est
     Data       Model                                Vol.Ref  Meth
     Grade      Grade
 1   PRAB1      PRAB1     101.000 .................... 1.0     3
 2   PRAB2      PRAB2     101.000 .................... 1.0     3
 3   PRAB3      PRAB3     101.000 .................... 1.0     3
 4   PRAB1      PRAB1     102.000 .................... 2.0     3
 5   PRAB2      PRAB2     102.000 .................... 2.0     3
 6   PRAB3      PRAB3     102.000 .................... 2.0     3
Number of records in the output model = 3970
Number of different grade fields      = 3
Maximum number of estimates           = 11910
This maximum number ignores retrieval criteria, selective updating, unestimated
zones etc, and so the % figure in the progress report may be too low.
>>> 10 estimates, 0.1% completed. Time 22:20:12 <<<
Number of records in the output model = 3970
Number of different grade fields      = 3
Maximum number of estimates           = 11910
This maximum number ignores retrieval criteria, selective updating, unestimated
zones etc, and so the % figure in the progress report may be too low.
>>>   11896 estimates, 100.0% completed.   Time 22:20:15 <<<
Total number of estimates 11896

Summary Statistics for Kriging
------------------------------
The total number of kriged estimates calculated is 11889
The number of kriged estimates with:
- one or more samples with zero covariance 1736
- error in solving kriging matrix 0
- negative kriging variance 0
- kriging variance greater than the sill 0
- one or more negative kriging weights 2134
- only one discretisation point 0
- maximum iterations in log kriging 0
>>> 3970 Records in File C:\database\geostats\course\_sp60.dm <<<

Post-processing model

Indicator estimation complete
- Model file modelind created with 3970 records
- Average grades file gradeind created with 8 records
- Indicator file indind created with 1077 records

 


Error and Warning Messages

Message

Description

Solution