Method for history matching a simulation model using self organizing maps to generate regions in the simulation model

Abstract

A method of history matching a simulation model is disclosed comprising: (a) defining regions exhibiting similar behavior in the model thereby generating the model having a plurality of regions, each of the plurality of regions exhibiting a similar behavior; (b) introducing historically known input data to the model; (c) generating output data from the model in response to the historically known input data; (d) comparing the output data from the model with a set of historically known output data; (e) adjusting the model when the output data from the model does not correspond to the set of historically known output data, the adjusting step including the step of arithmetically changing each of the regions of the model; and (f) repeating steps (b), (c), (d), and (e) until the output data from the model does correspond to the set of historically known output data.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

A full understanding will be obtained from the detailed description presented hereinbelow, and the accompanying drawings which are given by way of illustration only and are not intended to be limitative to any extent, and wherein:

FIG. 1 illustrates a workstation or other computer system wherein the numerical simulation model and the Self Organizing Map (SOM) software is stored;

FIG. 2 illustrates a grid block of the numerical simulation model which has a ‘parameter’ associated therewith;

FIG. 3 illustrates the numerical simulation model including a plurality of grid blocks and a method for history matching the numerical simulation model including the method as disclosed in this specification for history matching a simulation model using Self Organizing Maps to generate Regions in the simulation model;

FIG. 3A illustrates a realistic example of the numerical simulation model including the plurality of grid blocks;

FIG. 4 illustrates the numerical simulation model including a plurality of grid blocks, the model including a plurality of ‘regions’ where each ‘region’ of the model further includes one or more of the grid blocks of the numerical simulation model;

FIG. 5 illustrates how the ‘parameters’ (in addition to ‘all available information’) associated with each grid block of the numerical simulation model are introduced, as input data, to the Self Organizing Map (SOM) software, and the SOM software responds by defining the ‘regions’ of the numerical simulation model which are illustrated in FIG. 4;

FIG. 6 illustrates how ‘all available information’ associated with each of the grid blocks of the numerical simulation model is used by the SOM software to generate and define ‘regions’ of similar behavior among the grid blocks of the numerical simulation model, and, responsive thereto, the SOM software organizes the grid blocks of the numerical simulation model into one or more of the defined ‘regions’ as illustrated in FIG. 4; and

FIG. 7 illustrates a block diagram which describes how the SOM software will define ‘regions’ of similar behavior among the grid blocks of the numerical simulation model.

Claims

1. A method of history matching a simulation model, comprising: (a) defining regions exhibiting similar behavior in said model thereby generating said model having a plurality of regions, each of the plurality of regions exhibiting a similar behavior;(b) introducing historically known input data to said model;(c) generating output data from said model in response to said historically known input data;(d) comparing said output data from said model with a set of historically known output data;(e) adjusting said model when said output data from said model does not correspond to said set of historically known output data, the adjusting step including the step of arithmetically changing each of the regions of said model; and(f) repeating steps (b), (c), (d), and (e) until said output data from said model does correspond to said set of historically known output data.

2. The method of claim 1, wherein each region of said model includes a plurality of grid cells, each grid cell of each region having parameters associated therewith, and wherein the step of arithmetically changing each of the regions of said model comprises: multiplying said parameters of each grid cell in one or more regions of said model by a value.

3. The method of claim 2, wherein the step of defining regions exhibiting similar behavior in said model comprises: crossploting the parameters of the grid cells on a crossplot,identifying clusters of points within the crossplot, the points within a cluster representing grid cells having parameters exhibiting similar behavior,plotting the grid cells on a multidimensional plot while recalling the identity of those grid cells within the cluster which have similar behavior, andgrouping together those grid cells on the multidimensional plot which clustered together on the crossplot, each group defining a region exhibiting similar behavior.

4. A program storage device readable by a machine tangibly embodying a program of instructions executable by the machine to perform method steps for history matching a simulation model, said method steps comprising: (a) defining regions exhibiting similar behavior in said model thereby generating said model having a plurality of regions, each of the plurality of regions exhibiting a similar behavior;(b) introducing historically known input data to said model;(c) generating output data from said model in response to said historically known input data;(d) comparing said output data from said model with a set of historically known output data;(e) adjusting said model when said output data from said model does not correspond to said set of historically known output data, the adjusting step including the step of arithmetically changing each of the regions of said model; and(f) repeating steps (b), (c), (d), and (e) until said output data from said model does correspond to said set of historically known output data.

5. The program storage device of claim 4, wherein each region of said model includes a plurality of grid cells, each grid cell of each region having parameters associated therewith, and wherein the step of arithmetically changing each of the regions of said model comprises: multiplying said parameters of each grid cell in one or more regions of said model by a value.

6. The program storage device of claim 5, wherein the step of defining regions exhibiting similar behavior in said model comprises: crossploting the parameters of the grid cells on a crossplot,identifying clusters of points within the crossplot, the points within a cluster representing grid cells having parameters exhibiting similar behavior,plotting the grid cells on a multidimensional plot while recalling the identity of those grid cells within the cluster which have similar behavior, andgrouping together those grid cells on the multidimensional plot which clustered together on the crossplot, each group defining a region exhibiting similar behavior.

7. A computer program adapted to be executed by a processor, said computer program, when executed by said processor, conducting a process for history matching a simulation model, said process comprising: (a) defining regions exhibiting similar behavior in said model thereby generating said model having a plurality of regions, each of the plurality of regions exhibiting a similar behavior;(b) introducing historically known input data to said model;(c) generating output data from said model in response to said historically known input data;(d) comparing said output data from said model with a set of historically known output data;(e) adjusting said model when said output data from said model does not correspond to said set of historically known output data, the adjusting step including the step of arithmetically changing each of the regions of said model; and(f) repeating steps (b), (c), (d), and (e) until said output data from said model does correspond to said set of historically known output data.

8. The computer program of claim 7, wherein each region of said model includes a plurality of grid cells, each grid cell of each region having parameters associated therewith, and wherein the step of arithmetically changing each of the regions of said model comprises: multiplying said parameters of each grid cell in one or more regions of said model by a value.

9. The computer program of claim 8, wherein the step of defining regions exhibiting similar behavior in said model comprises: crossploting the parameters of the grid cells on a crossplot,identifying clusters of points within the crossplot, the points within a cluster representing grid cells having parameters exhibiting similar behavior,plotting the grid cells on a multidimensional plot while recalling the identity of those grid cells within the cluster which have similar behavior, andgrouping together those grid cells on the multidimensional plot which clustered together on the crossplot, each group defining a region exhibiting similar behavior.

10. A system adapted for history matching a simulation model, comprising: first apparatus adapted for defining regions exhibiting similar behavior in said model thereby generating said model having a plurality of regions, each of the plurality of regions exhibiting a similar behavior;second apparatus adapted for introducing historically known input data to said model;third apparatus adapted for generating output data from said model in response to said historically known input data;fourth apparatus adapted for comparing said output data from said model with a set of historically known output data;fifth apparatus adapted for adjusting said model when said output data from said model does not correspond to said set of historically known output data, the fifth apparatusincluding sixth apparatus adapted for arithmetically changing each of the regions of said model; andseventh apparatus adapted for repeating the functions performed by the second, third, fourth, fifth, and sixth apparatus until said output data from said model does correspond to said set of historically known output data.

11. The system of claim 10, wherein each region of said model includes a plurality of grid cells, each grid cell of each region having parameters associated therewith, and wherein the sixth apparatus adapted for arithmetically changing each of the regions of said model comprises: apparatus adapted for multiplying said parameters of each grid cell in one or more regions of said model by a value.

12. The system of claim 11, wherein the first apparatus adapted for defining regions exhibiting similar behavior in said model comprises: apparatus adapted for crossploting the parameters of the grid cells on a crossplot,apparatus adapted for identifying clusters of points within the crossplot, the points within a cluster representing grid cells having parameters exhibiting similar behavior,apparatus adapted for plotting the grid cells on a multidimensional plot while recalling the identity of those grid cells within the cluster which have similar behavior, andapparatus adapted for grouping together those grid cells on the multidimensional plot which clustered together on the crossplot, each group defining a region exhibiting similar behavior.