ResSimpy is a Python API for automating reservoir simulation workflows, allowing the user to read, manipulate and write reservoir simulation input decks. Whilst it was created by staff at BP, we welcome contributions from anybody interested, whether it is by raising pull requests, or simply suggesting features / raising bugs in the GitHub issues.
See the complete package documentation on readthedocs.
ResSimpy can be installed with pip:
pip install ressimpy
Please see Contributing Guide for instructions on how to set up a dev environment and contribute code to the project.
The following Python code examples demonstrate how to perform some simple operations on a model using ResSimpy:
from ResSimpy import NexusSimulator as Simulator
nexus_fcs_file = '/path/to/fcsfile.fcs'
model = Simulator(origin=nexus_fcs_file) # Create the 'Simulator' model object
Once these steps are completed, you are able to perform any supported operations on the model. The following code snippets are examples of a few such operations:
# Update the files in the model that have been modified.
# IMPORTANT: no changes made to the model, such as adding completions or removing constraints will be applied to the model files until this function is called.
model.update_simulator_files()
# Create a copy of the entire model
model.write_out_new_simulator(new_file_path='/new/path/to/fcsfile.fcs', new_include_file_location='/new/path/to/includes_directory/')
wells_info = model.wells.get_wells_overview() # Returns a list of wells with their information. Can be print()ed
print(wells_info)
well = model.wells.get(well_name='well_1') # Retrieves the named well as a NexusWell object
# You can then access the various properties for that well (such as perforations, shutins, completion events etc) using (for example)
perforations = well.perforations
# You can pretty print the information about a well using
print(well.printable_well_info)
# Get the wells information in dataframe format
wells_df = model.wells.get_df()
print(wells_df)
# Adding a completion
new_completion = {'date': '01/02/2025', 'i': 4, 'j': 5, 'k': 6, 'well_radius': 7.50} # Create a dictionary containing the properties of the completion you wish to add
model.wells.add_completion(well_name='well_1', completion_properties=new_completion) # Add the new completion
# Removing a completion
completion_to_modify = {'date': '01/02/2025', 'i': 4, 'j': 5, 'k': 6, 'well_radius': 7.5} # Create a dictionary containing the properties of the existing completion
model.wells.remove_completion(well_name='well_1', completion_properties=completion_to_modify) # Remove the completion
# Modifying a completion
modified_properties = {'date': '10/03/2025'} # Create a dict with the properties you want to change and their new values
model.wells.modify_completion(well_name='well_1', properties_to_modify=modified_properties, completion_to_change=completion_to_modify) # Modify the completion
func_list = model.grid.get_array_functions_list()
func_summary_df = model.grid.get_array_functions_df() # get a dataframe instead
[print(x) for x in func_list[0:9]] # Example showing how to print out the first 10 functions
constraints = model.network.constraints.get_all()
constraints_for_well = constraints['well_1'] # Get the constraints for the well well_1
# You can then access various properties related to the constraints, such as oil, water and gas rates using
oil_rate = constraints_for_well[0].max_surface_oil_rate
print(f"\nmax surface oil rate: {oil_rate}")
# Get a dataframe with all constraints in it.
constraint_df = model.network.constraints.get_df()
print(constraint_df)
df_well_cons = model.network.connections.get_df()
df_well_bores = model.network.wellbores.get_df()
df_connections = model.network.connections.get_df()
df_nodes = model.network.nodes.get_df()
For most bugs or feature requests, we recommend using GitHub issues. If, however, you have a query related to something else, or if your query relates to something confidential, please feel free to email the team at [email protected].