Automated parameterization for reservoir simulation

Abstract

The present invention provides a computer-implemented method (100), a computer program, and an apparatus for automated parameterization for reservoir simulation. The method comprises the steps of parsing initial input files (105) for a reservoir simulation model; identifying parameters to be modified from the initial input files (110); determining one or more additional parameters that are not included in the initial input files and are also to be modified (115); generating, for each of the one or more additional parameters, a respective new component (120); and updating the reservoir simulation model with the one or more new components (125).

Description

AUTOMATED PARAMETERIZATION FOR RESERVOIR SIMULATIONField[oooi] The present disclosure relates generally to reservoir simulation, and more specifically to automated parameterization for reservoir simulation.Background

[0002] Reservoir simulation is a computational tool used in the oil and gas industry to model and predict the behavior of oil and gas reservoirs over time. The process involves creating a mathematical model of the reservoir based on geological and engineering data. Once the model is created, it is used to simulate the behavior of the reservoir under different conditions.

[0003] For example, US 2021 / 0279593 Al describes using reactive transport modeling (RTM) techniques to generate computer models to predict distribution of chemical reactions. In another example, US 2018 / 0171761A1 describes a system for simulating a hydrocarbon-containing reservoir. Yet in another example, EP 3 938 815 Ai describes a computer-implemented method for generating a fractured reservoir model.

[0004] For uncertainty studies, it is important to generate a range of possible scenarios for the reservoir, considering uncertainty in the data and assumptions used to create the model. These scenarios can then be used to study the impact of different factors on the reservoir’s performance and to make informed decisions about how to manage the reservoir.

[0005] However, using known software solution, parameters that should be considered need to be defined manually by the user in the reservoir simulation model before the software can generate values for the parameters. The manual process can be time-consuming and error prone. First, the user needs to explore text files with large amount of data to find the relevant parameters. Second, the user spends more time to define the framework to vary parameters that are not yet defined in the reservoir model.[ooo6]Therefore, it is a goal for the present invention to provide techniques to improve the process of parameterization for reservoir simulation, so that time and resources can be saved.Summary

[0007] The invention is defined in the independent claims.[ooo8]The various embodiments detailed herein relate to a computer-implemented method, a computer program, a storage medium and an apparatus for automated parameterization for reservoir simulation. Additionally, the embodiments and aspects of the present invention provide other benefits that will become clear to those skilled in the art from the foregoing description.

[0009] An example computer-implemented method may comprise the steps of parsing initial input files for a reservoir simulation model; identifying parameters to be modified from the initial input files; determining one or more additional parameters that are not included in the initial input files and are also to be modified; generating, for each of the one or more additional parameters, a respective new component; and updating the reservoir simulation model with the one or more new components.

[0010] In some aspects, the computer-implemented method may further comprise the steps of generating different sets of values, each set of values to be applied for parameters to be modified in a reservoir simulation case; generating different simulation files, each simulation file including a respective set of values for the parameters to be modified, and each simulation file associated with a reservoir simulation case; and launching a reservoir simulator to simulate different reservoir simulation cases by using the different simulation files. In some cases, the step of generating different sets of values may comprise generating different sets of values within boundaries defined by a user for each parameter. In some cases, the step of generating different sets of values may be based on a Latin Hypercube sampling method.

[0011] In some aspects, the initial input files maybe from an ECLIPSE reservoir simulator and / or an INTERSECT reservoir simulator.

[0012] In some aspects, the parameters may comprise reservoir property related parameters, fluid property related parameters, field operating parameters, and / orwell-level parameters. In some cases, the reservoir property related parameters may comprise porosity, permeability, net-to-gross, and / or rock compressibility. In some cases, the fluid property related parameters may comprise viscosity, density, and / or composition. In some cases, the field operating parameters may comprise maximum production rate, water injection rate, and / or well spacing. In some cases, the well -level parameters may comprise geometry, completion details, and / or well trajectories.

[0013] In some aspects, the computer-implemented method may further comprise the steps of extracting simulation results associated with the different reservoir simulation cases.

[0014] In some aspects, the computer-implemented method may further comprise the steps of analyzing, based on the simulation results, an impact of a respective parameter on reservoir performance.

[0015] In some aspects, the computer-implemented method may further comprise the steps of determining optimal parameters for operating a reservoir underlying the reservoir simulation model.

[0016] An example computer program may comprise computer readable instructions which, when implemented on a computer, cause the computer to carry out the following steps: parsing initial input files for a reservoir simulation model; identifying parameters to be modified from the initial input files; determining one or more additional parameters that are not included in the initial input files and are also to be modified; generating, for each of the one or more additional parameters, a respective new component; and updating the reservoir simulation model with the one or more new components. Moreover, the example computer program may comprise computer readable instructions which, when implemented on a computer, cause the computer to carry out any method in accordance with the present invention.

[0017] In some aspects, the computer program maybe written in Python.

[0018] In some aspects, the computer program may comprise an interface adapted to read and parse files from ECLIPSE and / or INTERSECT reservoir simulators.

[0019] In some aspects, the computer program may comprise an interface adapted to connect with ECLIPSE and / or INTERSECT reservoir simulators to run simulation files and / or to extract simulation results.

[0020] An example storage medium may comprise any computer program in accordance with the present invention.

[0021] An example apparatus may comprise a processor; a memory coupled with the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform the following steps: parsing initial input files for a reservoir simulation model; identifying parameters to be modified from the initial input files; determining one or more additional parameters that are not included in the initial input files and are also to be modified; generating, for each of the one or more additional parameters, a respective new component; and updating the reservoir simulation model with the one or more new components. Moreover, the example apparatus may comprise instructions stored in the memory and executable by the processor to cause the apparatus to perform any method in accordance with the present invention.

[0022] Another example apparatus may comprise means for parsing initial input files for a reservoir simulation model; means for identifying parameters to be modified from the initial input files; means for determining one or more additional parameters that are not included in the initial input files and are also to be modified; means for generating, for each of the one or more additional parameters, a respective new component; and means for updating the reservoir simulation model with the one or more new components. Moreover, the apparatus may comprise means for performing any method in accordance with the present invention.Brief description of the drawings

[0023] The accompanying drawings are included to provide a further understanding of the invention. The drawings illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0024] In the drawings:

[0025] FIG. 1 illustrates an example method according to aspects of the disclosure.

[0026] FIG. 2 shows an example computer program according to aspects of the disclosure.

[0027] FIG. 3 shows an example computer program according to aspects of the disclosure.

[0028] FIG. 4 shows an example computer program according to aspects of the disclosure.Detailed description

[0029] In the following, a few terms are defined to better understand the context of the invention.

[0030] “Reservoir simulation” is a computational tool used in the oil and gas industry to model and predict the behavior of oil and gas reservoirs over time. The process involves creating a mathematical model of the reservoir based on geological and engineering data, such as the size and shape of the reservoir, the properties of the rock and fluids, and the production history. Once the model is created, it is used to simulate the behavior of the reservoir under different conditions, such as changes in production rates, injection of fluids, or the introduction of new wells. This allows engineers to optimize production and recovery while minimizing costs and risks.

[0031] A “reservoir simulation model” is a computer-based mathematical model that is used to simulate the behavior of an oil or gas reservoir over time. Reservoir simulation models typically use data on the reservoir's geometry, geological properties, fluid properties, and production history to create a detailed and accurate representation of the reservoir. The model is built by dividing the reservoir into a grid of cells and assigning properties to each cell, such as porosity, permeability, and fluid saturation. The model then simulates the flow of fluids through the reservoir, taking into account factors such as pressure, temperature, fluid properties, and the effects of production and injection wells. By running the model under different scenarios, engineers can optimize production rates, assess the impact of new wells or production strategies, and predict the long-term behavior of the reservoir.

[0032] A “reservoir simulation scenario” typically includes a range of input parameters, such as rock properties, fluid properties, and well configurations, which are based on available data and assumptions about the reservoir. Theboundary conditions for the scenario may include the initial reservoir conditions, the injection and production rates, and any other external factors that may affect the behavior of the reservoir, such as water flooding or gas injection. By running multiple reservoir simulation scenarios with different input parameters and boundary conditions, engineers can evaluate the performance of the reservoir under different operating conditions and identify the optimal strategies for maximizing oil or gas recovery, minimizing costs, and reducing risks.

[0033] There are a number of commercial and open-source software programs available for reservoir simulation. Example commercial software programs include Eclipse, CMG (Computer Modelling Group), Petrel, INTERSECT, Reservoir Toolbox, Nexus, etc. Example open-source software programs include OpenFOAM, MRST (Matlab Reservoir Simulation Toolbox), DuMuX (DUNE for Multi-phase, extended), Open Porous Media (0PM), Resinsight, etc.

[0034] The following detailed description describes techniques for improving the process of parameterization for reservoir simulation, so that time and resources can be saved. In particular, the techniques are provided to be compatible with existing reservoir simulation programs, so that seamless integration and automation of the simulation process can be realized. The present disclosure is not intended to be limited to the described or illustrated examples, but to be accorded the widest scope consistent with the described principles and features.

[0035] FIG. 1 is a flowchart of an example method too for automated parameterization for reservoir simulation, according to aspects of the disclosure. One or more method blocks of FIG. 1 may be performed by one or more components of a computer such as a processor, a memory, and / or another component of the computer. Moreover, one or more method blocks of FIG. 1 may be implemented by a computer program 300 in accordance with Fig. 2, a computer program 400 in accordance with Fig. 3, or a computer program 500 in accordance with Fig. 4.

[0036] As shown in FIG. 1, method too may include parsing initial input files for a reservoir simulation model (block 105). This step may involve reading the input files and extracting necessary data and parameters. In some aspects, the initial input files maybe from an ECLIPSE reservoir simulator and / or an INTERSECT reservoir simulator. For example, the computer program may be adapted to read files in the format provided by a commercial software program (such as ECLIPSE reservoir simulator or the INTERSECT reservoir simulator). The initial input filesmaybe default simulation input files provided by the commercial software program. These input files typically contain default values and settings for various simulation parameters, such as reservoir geometiy, rock properties, fluid properties, and boundaiy conditions.

[0037] As further shown in FIG. 1, method 100 may include identifying parameters to be modified from the initial input files (block 110). This step may involve comparing data and parameters extracted from the initial input files against a pre-defined list of parameters of interest.

[0038] As further shown in FIG. 1, method 100 may include determining one or more additional parameters that are not included in the initial input files and are also to be modified (block 115). This step may involve determining parameters that are on the pre-defined list but not yet included in the initial input files.

[0039] As further shown in FIG. 1, method too may include generating, for each of the one or more additional parameters, a respective new component (block 120). In some cases, the new component may include a definition for a range of values for a respective additional parameter. Moreover, the new component may define how the respective additional parameter should be varied in the simulation.

[0040] AS further shown in FIG. 1, method too may include updating the reservoir simulation model with the one or more new components (block 125). For example, corresponding keywords for the respective new components maybe defined and included in a file defining the reservoir simulation model. In another example, corresponding nodes for the respective new components may be defined and included in a file defining the reservoir simulation model.

[0041] In some aspects, the parameters may comprise reservoir property related parameters, fluid property related parameters, field operating parameters, and / or well-level parameters. In some cases, the reservoir property related parameters may comprise porosity, permeability, net-to-gross, and / or rock compressibility. These parameters are critical for understanding the flow of fluids through the reservoir and predicting reservoir performance. In some cases, the fluid property related parameters may comprise viscosity, density, and / or composition. These parameters are critical for understanding fluid behaviour and predicting fluid flow through the reservoir. In some cases, wherein the field operating parameters may comprise maximum production rate, water injection rate, and / or well spacing. Theseparameters are critical for understanding how the reservoir will be produced or injected and predicting the overall impact of these operations on reservoir performance. In some cases, the well-level parameters may comprise geometry, completion details, and / or well trajectories. These parameters are critical for understanding how the fluids will flow into and out of the reservoir through the wells, and how the wells will impact the reservoir performance.

[0042] As further shown in FIG. 1, method 100 may optionally include generating different sets of values, each set of values to be applied for parameters to be modified in a reservoir simulation case (block 130). For example, a range of values for each parameter may be determined and values for each parameter may be generated within the respective range, either randomly or based on some constraints.

[0043] In some aspects, the step of generating different sets of values may comprise generating different sets of values within boundaries defined by a user for each parameter. For example, the user can define a minimum and a maximum value for some or all of the parameters.

[0044] In some cases, the step of generating different sets of values may be based on a Latin Hypercube sampling method. For example, a software module “parameters sampler” may be implemented to generate the different sets of values for the parameters.

[0045] As further shown in FIG. 1, method too may optionally include generating different simulation files, each simulation file including a respective set of values for the parameters to be modified, and each simulation file associated with a reservoir simulation case (block 135). A reservoir simulation case represents a respective reservoir simulation scenario. In some cases, the number of reservoir simulation cases to be generated may be specified by the user.

[0046] As further shown in FIG. 1, method too may optionally include launching a reservoir simulator to simulate different reservoir simulation cases by using the different simulation files (block 140). The reservoir simulator maybe provided by an existing commercial software program such as ECLIPSE or INTERSECT.

[0047] In some aspects, method too may optionally include extracting simulation results associated with the different reservoir simulation cases. In some cases, eachset of results corresponding to a respective combination of parameters maybe output in a separate file or a separate file folder.

[0048] In some aspects, method 100 may optionally include analyzing, based on the simulation results, an impact of a respective parameter on reservoir performance.

[0049] In some aspects, method 100 may optionally include determining optimal parameters for operating a reservoir underlying the reservoir simulation model.

[0050] As can be seen, method 100 can be used to automate and streamline the process of generating new scenarios. Thus, the techniques implemented by method 100 provide efficient and accurate predictions of reservoir performance, which can lead to improved decision-making and effective management of oil and gas reservoirs. Furthermore, these techniques can save time and resources for the industry by automating the process of parameterizing reservoir simulation models. It can also lead to improved decision-making and effective management of oil and gas reservoirs, which can result in increased production and profitability.

[0051] FIG. 2 shows an example computer program 300 in communication with an existing reservoir simulator 200.

[0052] The computer program 300 may comprise instructions which are adapted to implement some or all aspects of the method too as described above.

[0053] In some aspects, the computer program 300 may be provided in form of Python scripts.

[0054] In some aspects, the computer program 300 may comprise an interface adapted to read and parse files from the existing reservoir simulator 200. For example, the existing reservoir simulator 200 may be an ECLIPSE or an INTERSECT reservoir simulator.

[0055] In some aspects, the computer program 300 may comprise an interface adapted to connect with the existing reservoir simulator 200 to run simulation files and / or to extract simulation results.

[0056] As can be seen, the computer program 300 allows for seamless integration with existing reservoir simulator and automation of the simulation process.

[0057] Fig- 3 shows an example computer program 400. As shown in FIG. 3, computer program 400 may include software modules 300a, 300b and 350.

[0058] Software modules 300a and 300b may include similar instructions as in the computer program 300 except the instructions to generate different sets of values for the parameters. The instructions to generate different sets of values for the parameters may be included in software module 350 (e.g., a “parameters sampler”) and thus can be shared by software modules 300a and 300b. In some cases, the software module 350 may implement a Latin Hypercube Sampling method.

[0059] In some aspects, software module 300a may be adapted to read input files from a first existing reservoir simulator (e.g., ECLIPSE) and generate simulation files compatible with the first existing reservoir simulator, and software module 300b maybe adapted to read input files from a second existing reservoir simulator (e.g., INTERSECT) and generate simulation files compatible with the second existing reservoir simulator.

[0060] In a further aspect, even more software modules similar to software modules 300a and 300b can be implemented in the computer program 400. Each software module may be adapted to read input files from a specific existing reservoir simulator and generate compatible simulation files accordingly. Each software module may be adapted to share the software module 350 for generate different sets of values for the parameters.

[0061] Fig. 4 shows an example computer program 500. As shown in FIG. 4, computer program 500 may include software modules 510, 520, 530 and 540. Software module 540 may have similar functions like software module 350 (e.g., a “parameters sampler”), and the functions are shared by software modules 510 and 520. Software modules 510 and 520 may have similar functions like software modules 300a and 300b except that software modules 510 and 520 further share software module 530, which maybe adapted to launch different simulators.

[0062] As further shown in FIG. 4, software module 510 may include software modules 511, 512, 513, 514 and 515, and software module 520 may include software modules 521, 522, 523, 524 and 525. Software module 510 maybe adapted to process data related to a first reservoir simulator (such as an ECLIPSE reservoir simulator). Similarly, software module 520 maybe adapted to process data related to a second reservoir simulator (such as an INTERSECT reservoir simulator).

[0063] Software module 511 may be adapted to read simulation files 610 associated with the first reservoir simulator. Similarly, software module 521 may be adapted to read simulation files 620 associated with the second reservoir simulator. Software module 511 / 521 may implement techniques similar to those implemented in block 105 of Fig. 1. Software module 511 may thus provide an interface for the software 500 to connect with the first reservoir simulator to read and parse the corresponding simulation files. Similarly, software module 521 may thus provide an interface for the software 500 to connect with the second reservoir simulator to read and parse the corresponding simulation files.

[0064] Alternatively, software module 511 and 521 maybe implemented as one software module (i.e., to provide a combined interface to read different simulation files from different reservoir simulators).

[0065] Software module 512 may be adapted to identify parameters to be modified from the simulation files 610. Similarly, software module 522 may be adapted to identify parameters to be modified from the simulation files 620. Software module 512 / 522 may implement techniques similar to those implemented in block 110 of Fig. 1.

[0066] Software module 513 maybe adapted to determine one or more additional parameters that are not included in the simulation files 610. Similarly, software module 523 may be adapted to determine one or more additional parameters that are not included in the simulation files 620. Software module 513 / 523 may implement techniques similar to those implemented in block 115 of Fig. 1.

[0067] Software module 514 may be adapted to generate, for each of the one or more additional parameters, a respective new component for the reservoir simulation model associated with the first reservoir simulator. Similarly, software module 524 maybe adapted to generate, for each of the one or more additional parameters, a respective new component for the reservoir simulation model associated with the second reservoir simulator.

[0068] Further, software module 514 maybe adapted to update the reservoir simulation model associated with the first reservoir simulator the with the respective one or more new components. Similarly, software module 524 may be adapted to update the reservoir simulation model associated with the second reservoir simulator the with the respective one or more new components. Softwaremodule 514 / 524 may implement techniques similar to those implemented in block 120 and block 125 of Fig. 1.

[0069] In some aspects, the first reservoir simulator may be an ECLIPSE reservoir simulator, and the software module 514 maybe adapted to write corresponding keywords for the one or more new components in order to update the reservoir simulation model associated with the ECLIPSE reservoir simulator.

[0070] In some aspects, the second reservoir simulator may be an INTERSECT reservoir simulator, and the software module 524 may be adapted to write corresponding nodes for the one or more new components in order to update the reservoir simulation model associated with the INTERSECT reservoir simulator.

[0071] Software module 540 may be adapted to generate different sets of values, and each set of values are to be applied for parameters to be modified in a reservoir simulation case. Software module 540 may implement techniques similar to those implemented in block 130 of Fig. 1.

[0072] Software module 515 maybe adapted to generate different simulation files for the first reservoir simulator. Similarly, software module 525 maybe adapted generate different simulation files for the second reservoir simulator. Software module 515 / 525 may implement techniques similar to those implemented in block 135 of Fig. 1. Furthermore, generating different simulation files maybe based on the different sets of values generated by software module 540.

[0073] Software module 530 maybe adapted to launch the first and / or second reservoir simulators to simulate different reservoir simulation cases by using the different simulation files. Software module 530 may implement techniques similar to those implemented in block 140 of Fig. 1. Software module 530 may thus provide an interface for the software 500 to connect with the first and / or second reservoir simulators. Moreover, the interface may be used to extract simulation results from the first and / or second reservoir simulators.

[0074] Alternatively, software module 530 may be implemented as two separate software modules, each adapted to launch a respective reservoir simulator.

[0075] File 700 may include a pre-defined list of parameters of interest, which are to be modified (i.e., varied) in different reservoir simulation cases. Software module 513 (or 523) may be adapted to determine one or more additional parameters that arenot included in the simulation files 6io (or 620, respectively) based on the parameters included in file 700.

[0076] While specific examples have been described herein, it will be obvious to those skilled in the art that various changes and modifications may be aimed to in the specification. It will, therefore, be understood by those skilled in the art that the particular embodiments of the invention presented here are byway of illustration only and are not meant to be in anyway restrictive; therefore, numerous changes and modifications may be made, and the full use of equivalents resorted to, without departing from the scope of the invention.

[0077] Further examples according to the disclosure are described in the following:Aspect 1 Computer-implemented method for automated parameterization for reservoir simulation, the method comprising: parsing initial input files for a reservoir simulation model; identifying parameters to be modified from the initial input files; determining one or more additional parameters that are not included in the initial input files and are also to be modified; generating, for each of the one or more additional parameters, a respective new component; and updating the reservoir simulation model with the one or more new components.Aspect 2 The computer-implemented method of the proceeding aspect, further comprising: generating different sets of values, each set of values to be applied for parameters to be modified in a reservoir simulation case; generating different simulation files, each simulation file including a respective set of values for the parameters to be modified, and each simulation file associated with a reservoir simulation case; andlaunching a reservoir simulator to simulate different reservoir simulation cases by using the different simulation files.Aspect 3 The computer-implemented method of the proceeding aspect, wherein the step of generating different sets of values comprises generating different sets of values within boundaries defined by a user for each parameter.Aspect 4 The computer-implemented method of aspect 2 or 3, wherein the step of generating different sets of values is based on a Latin Hypercube sampling method.Aspect 5 The computer-implemented method of any preceding aspect, wherein the initial input files are from an ECLIPSE reservoir simulator and / or an INTERSECT reservoir simulator.Aspect 6 The computer-implemented method of any preceding aspect, wherein the parameters comprise reservoir property related parameters, fluid property related parameters, field operating parameters, and / or well -level parameters.Aspect 7 The computer-implemented method of the proceeding aspect, wherein the reservoir property related parameters comprise porosity, permeability, net-to- gross, and / or rock compressibility.Aspect 8 The computer-implemented method of aspect 6 or 7, wherein the fluid property related parameters comprise viscosity, density, and / or composition.Aspect 9 The computer-implemented method of any of the preceding aspects 6 -8, wherein the field operating parameters comprise maximum production rate, water injection rate, and / or well spacing.Aspect io The computer-implemented method of any of the preceding aspects 6 -9, wherein the well-level parameters comprise geometry, completion details, and / or well trajectories.Aspect n The computer-implemented method of any of the preceding aspects 2 -10, further comprising: extracting simulation results associated with the different reservoir simulation cases.Aspect 12 The computer-implemented method of the preceding aspect, further comprising: analyzing, based on the simulation results, an impact of a respective parameter on reservoir performance.Aspect 13 The computer-implemented method of the preceding aspect, further comprising: determining optimal parameters for operating a reservoir underlying the reservoir simulation model.Aspect 14 A computer program comprising computer readable instructions which, when implemented on a computer, cause the computer to carry out a method according to any preceding aspect.Aspect 15 The computer program of the preceding aspect, wherein the computer program is written in Python.Aspect 16 The computer program of the preceding aspect 14 or 15, wherein the computer program comprises an interface adapted to read and parse files from ECLIPSE and / or INTERSECT reservoir simulators.Aspect 17 The computer program of any of the preceding aspects 14 - 16, wherein the computer program comprises an interface adapted to connect with ECLIPSE and / or INTERSECT reservoir simulators to run simulation files and / or to extract simulation results.Aspect 18 A storage medium comprising the computer program according to any of aspects 14 - 17.Aspect 19 An apparatus for automated parameterization for reservoir simulation, the apparatus comprising: a processor, memory coupled with the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform the method of any one of the preceding aspects 1 to 13.Aspect 20 An apparatus for automated parameterization for reservoir simulation, the apparatus comprising means for performing the method of any one of the preceding aspects 1 to 13.

Claims

CLAIMS1. Computer-implemented method for automated parameterization for reservoir simulation, the method comprising: parsing initial input files for a reservoir simulation model; identifying parameters to be modified from the initial input files; determining one or more additional parameters that are not included in the initial input files and are also to be modified; generating, for each of the one or more additional parameters, a respective new component; and updating the reservoir simulation model with the one or more new components.

2. The computer-implemented method of the proceeding claim, further comprising: generating different sets of values, each set of values to be applied for parameters to be modified in a reservoir simulation case; generating different simulation files, each simulation file including a respective set of values for the parameters to be modified, and each simulation file associated with a reservoir simulation case; and launching a reservoir simulator to simulate different reservoir simulation cases by using the different simulation files.

3. The computer-implemented method of the proceeding claim, wherein the step of generating different sets of values comprises generating different sets of values within boundaries defined by a user for each parameter.

4. The computer-implemented method of claim 2 or 3, wherein the step of generating different sets of values is based on a Latin Hypercube sampling method.

5. The computer-implemented method of any preceding claim, wherein the initial input files are from an ECLIPSE reservoir simulator and / or an INTERSECT reservoir simulator.

6. The computer-implemented method of any preceding claim, wherein the parameters comprise reservoir property related parameters, fluid property related parameters, field operating parameters, and / or well -level parameters.

7. The computer-implemented method of the proceeding claim, wherein the reservoir property related parameters comprise porosity, permeability, net-to-gross, and / or rock compressibility.

8. The computer-implemented method of claim 6 or 7, wherein the fluid property related parameters comprise viscosity, density, and / or composition.

9. The computer-implemented method of any of the preceding claims 6 - 8, wherein the field operating parameters comprise maximum production rate, water injection rate, and / or well spacing.

10. The computer-implemented method of any of the preceding claims 6 - 9, wherein the well -level parameters comprise geometry, completion details, and / or well trajectories.

11. The computer-implemented method of any of the preceding claims 2 - 10, further comprising: extracting simulation results associated with the different reservoir simulation cases.

12. The computer-implemented method of the preceding claim, further comprising: analyzing, based on the simulation results, an impact of a respective parameter on reservoir performance.

13. The computer-implemented method of the preceding claim, further comprising: determining optimal parameters for operating a reservoir underlying the reservoir simulation model.14- A computer program comprising computer readable instructions which, when implemented on a computer, cause the computer to carry out a method according to any preceding claim.

15. The computer program of the preceding claim, wherein the computer program is written in Python.

16. The computer program of the preceding claim 14 or 15, wherein the computer program comprises an interface adapted to read and parse files from ECLIPSE and / or INTERSECT reservoir simulators.

17. The computer program of any of the preceding claims 14 - 16, wherein the computer program comprises an interface adapted to connect with ECLIPSE and / or INTERSECT reservoir simulators to run simulation files and / or to extract simulation results.

18. A storage medium comprising the computer program according to any of claims 14 - 17-19. An apparatus for automated parameterization for reservoir simulation, the apparatus comprising: a processor, memory coupled with the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform the method of any one of the preceding claims 1 to 13.

20. An apparatus for automated parameterization for reservoir simulation, the apparatus comprising means for performing the method of any one of the preceding claims 1 to 13.

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