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Datasets:
solution-seeker-as
/
manywells

Tasks:
Tabular Regression
Tabular Classification
Modalities:
Tabular
Text
Formats:
csv
Languages:
English
Size:
1M - 10M
Tags:
simulation
multiphase
oil
gas
water
well
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files Community
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metadata
license: cc-by-nc-4.0
task_categories:
  - tabular-regression
  - tabular-classification
language:
  - en
tags:
  - simulation
  - multiphase
  - oil
  - gas
  - water
  - well
pretty_name: ManyWells simulated multiphase flow data
size_categories:
  - 1M<n<10M
configs:
  - config_name: manywells-sol-1
    data_files: data/manywells-sol-1.zip
  - config_name: manywells-sol-1-config
    data_files: data/manywells-sol-1_config.zip
  - config_name: manywells-nsol-1
    data_files: data/manywells-nsol-1.zip
  - config_name: manywells-nsol-1-config
    data_files: data/manywells-nsol-1_config.zip
  - config_name: manywells-nscl-1
    data_files: data/manywells-nscl-1.zip
  - config_name: manywells-nscl-1-config
    data_files: data/manywells-nscl-1_config.zip

ManyWells: simulation of multiphase flow in thousands of wells

The ManyWells datasets contain simulations of multiphase (gas, oil, water) flow in thousands of wells. The datasets were created and shared by Solution Seeker AS to support research on data-driven methodologies and industrial applications of machine learning and AI.

Dataset details

Dataset Structure

There are currently three datasets for three different operating conditions:

  • manywells-sol-1: simulations with stationary boundary conditions and open-loop control (no feedback)
  • manywells-nsol-1: simulations with non-stationary boundary conditions and open-loop control (no feedback)
  • manywells-nscl-1: simulations with non-stationary boundary conditions and closed-loop control (with feedback)

Each dataset has one million data points from 2000 vertical wells (500 data points per well). The datasets include a feature called "ID", which uniquely identifies a wells. Please note that ID are unique only within each dataset, meaning that well 1 in dataset A is different from well 1 in dataset B.

The parameters used in the simulation can be found in the config files, named [dataset-name]_config.zip. The configuration is stored as a dictionary with the keys being the well IDs.

Personal and Sensitive Information

The datasets do not contain any personal, sensitive, or private data.

How to use the data?

The following snippet shows how to use the HuggingFace datasets package to download the dataset in Python.

import datasets

# Download 'manywells-sol-1'
data = datasets.load_dataset("solution-seeker-as/manywells", name='manywells-sol-1')

# Cast dataset to a Pandas DataFrame
df = data['train'].to_pandas()

# Print the data
print(df)

Citation [Coming soon]

We kindly ask that you cite our paper if you use the ManyWells datasets or code in your academic work.

BibTeX:

[Coming soon]

Dataset Card Contact

Queries about the dataset can be directed to Bjarne Grimstad (e-mail: [email protected]).