Controlling the facies modeling method

With the Control Method form (model > Facies > Control Method) you define the modeling parameters for the method that you assigned to your Volume of Interest (VOI). Note that in case you are using MPS as a method, you must assign a training image first, see Assigning a Training Image.

To control the modeling method parameters

  1. Open the Control Method form and select the relevant facies model from the Model drop-down list.
  2. In the Volume of Interest table, select the Volume of Interest (VOI). Upon selection, the right side of the form updates with the parameters related to the modeling method of the selected VOI. It is of importance that you review the default settings and update them if required. For details on the modeling parameters and settings, see Parameters settings on Control Method form below.
    3. Using the context menu options Copy and Paste, you can copy-paste control method settings between the VOIs which have the same modeling method assigned. Once you have copied settings, you can select Paste Settings Options. This will open a separate form, which allows you to paste the settings to multiple VOIs at once. Note that checkbox selection can be done in bulk by holding down SHIFT while selecting a range of VOIs (they turn blue), then checking the box of one of them. All other VOIs in the selected range will get checked simultaneously.
  3. Click Apply to save the parameters to the VOI and keep the form open, or click OK to go to the last step of the modeling workflow Run Model.

Parameters settings on Control Method form

This selection assigns a single facies to all the grid cells within the VOI.

Constant  Select the facies class that you want to assign.

Do not reset well cells to upscaled values  Ordinarily, the stochastic simulation is overwritten by the well data in the upscaled cells, to ensure that the well data is reproduced. You can turn this behavior off by checking this check box. If the upscaled property is set to 'None' on the Create Model form, this box is checked by default.

Sequential Indicator Simulation (SIS) is a facies modeling technique, which allows assigning different indicator variogram-models to each facies. SIS provides multiple ways to condition the simulation to soft or secondary data, additional to the hard data (wells). Soft or secondary data can be obtained from geological interpretation or geophysical measurements. To run SIS, each facies requires one indicator variogram model to be created with the Assign Variogram form. Both the VPC and variogram models are automatically retrieved. SIS allows the user to specify the size of the search ellipsoid, the input proportions (either global or VPC proportions), the method for integrating soft or secondary data, the correlation coefficient between the to-be modeled data and the secondary data, and strength of the cleaning.

More information about SIS can be found in 'A sequential indicator simulation program for categorical variables with point and block data; BlockSIS' (Deutsch, 2006), see http://dx.doi.org/10.1016/j.cageo.2006.03.005.

The SIS parameter settings:

Search factor  The variogram model ranges that you defined on the Assign Variogram form (model > Facies > Assign Variogram) are multiplied with the search factor to obtain the size of the search ellipsoid, i.e. Search ellipsoid = Search factor x Variogram model range. The search factor is applied to all three ranges of the variogram model so that the shape of the search ellipsoid reflects the spatial anisotropy.

Example. Three different search factors applied to the same variogram model (major: 5000 m, minor: 3000 m, vertical: 500 m).

  • Search factor = 1: Search ellipsoid = 5000 m, 3000 m, 500 m
  • Search factor = 2: Search ellipsoid = 10000 m, 6000 m, 1000 m
  • Search factor = 3: Search ellipsoid = 15000 m, 9000 m, 1500 m

Cleaning / smoothing  Option to select whether the result should be cleaned and to what extent (the level of cleaning increases from 'None' to 'Super'). Cleaning allows for removal of small-scale variations (noise) which appear geologically unrealistic . Cleaning aims at retaining at each location the most probable lithofacies type based on the surrounding lithofacies types, the proximity to conditioning data, and the mismatch from the global target proportion, if any. Be careful when selecting a cleaning level; too much cleaning might lead to artificial continuity and unrealistic results. The details of this image cleaning operation are explained in Deutsch (2006).

Do not use upscaled values for conditioning  When this box is checked, the upscaled values are not used as control points (conditioning) in the stochastic simulation. You can use this option to generate an unconditional simulation that is not correlated with the well data.

Derive variogram from  The single indicator model variogram to be used as input. To assign a variogram to the VOI, see Variogram model.

Search factor  The variogram model ranges that you defined on the Assign Variogram form (model > Facies > Assign Variogram) are multiplied with the search factor to obtain the size of the search ellipsoid, i.e. Search ellipsoid = Search factor x Variogram model range. The search factor is applied to all three ranges of the variogram model so that the shape of the search ellipsoid reflects the spatial anisotropy.

Example. Three different search factors applied to the same variogram model (major: 5000m, minor: 3000m, vertical: 500m).

  • Search factor = 1: Search ellipsoid = 5000m, 3000m, 500m
  • Search factor = 2: Search ellipsoid = 10000m, 6000m, 1000m
  • Search factor = 3: Search ellipsoid = 15000m, 9000m, 1500m

Do not use upscaled values for conditioning  When this box is checked, the upscaled values are not used as control points (conditioning) in the stochastic simulation. You can use this option to generate an unconditional simulation that is not correlated with the well data.

Simulation Path

The parameters allow you to define a simulation path, appropriate to the depositional patterns observed in your training image. Beyond the standard 'random' simulation path (as applied by SIS and TGS), MPS allows to fine-tune the order grid cells are visited for population with simulated facies.

    Random  Purely random visitation order, similar to SIS and TGS.

    Random neighbor  Random visitation order within the vicinity of wells.

    Around data  Circular walks around and away from well locations.

    Stratified random  Grid cells are simulated in one k-layer after another (stratified). Within each k-layer one row is simulated after another. You can select in which direction the simulator progresses from one row to another. Within one row the order is random.

    Unilateral path  Grid cells are visited in a sequential, non-random order. By adjusting the k-, i- and j- direction, you can define the walking directions.

Do not use upscaled values for conditioning  When this box is checked, the upscaled values are not used as control points (conditioning) in the stochastic simulation. You can use this option to generate an unconditional simulation that is not correlated with the well data.