Skip to main content

Well Integrity Log analysis and Visualization tool [This is a Test Release]

Project description

Well Integrity Visualization Tool

pytegrity

pytegrity This application allows users to upload LAS files, visualize well integrity, and extract finger logs to analyze data related to Well integrity issues (Corrosion, Deposition, etc).

Requirements

Before running the app, make sure to install the following libraries:

pip install streamlit lasio pandas plotly pytegrity

Interactive application

Features

File Upload: Upload LAS files for analysis.

Finger Log Selection: Choose which finger/pad logs to visualize.

Depth Range Control: Adjust the depth range for the plot using a slider.

Plot Customization: Customize the plot's height and width.

Well Integrity Visualization: View a detailed plot representing the well integrity with selected logs and depth ranges.

Usage

Upload LAS File:

On the sidebar, click the "Upload LAS File" button to upload your LAS file.

The file is temporarily stored for processing. Interactive notebook

Select Finger Logs:

Choose the desired finger logs to include in the visualization.

Adjust Depth Range:

Use the depth range slider to select the depth interval to visualize.

Plot Customization:

Set the height and width of the plot for better visualization.

Visualization:

After selecting your preferences, the app will generate the well integrity plot based on the LAS file data.

Code Breakdown File Upload: The file_uploader method is used to upload LAS files, and the uploaded file is saved temporarily for further processing.

Data Loading: The LAS file is read using the lasio library and converted to a pandas DataFrame.

Finger Log Selection: Users can select columns that contain "FING" to display the desired finger logs.

Depth Range Selection: The depth range for visualization is controlled through the sidebar slider, adjusting the Y-axis range on the plot.

Visualization: The plot_well_integrity method from the pytegrity module is used to plot well integrity data. The plot is generated dynamically with customizable height and width.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pytegrity-0.1.0.tar.gz (2.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pytegrity-0.1.0-py3-none-any.whl (2.1 kB view details)

Uploaded Python 3

File details

Details for the file pytegrity-0.1.0.tar.gz.

File metadata

  • Download URL: pytegrity-0.1.0.tar.gz
  • Upload date:
  • Size: 2.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.7

File hashes

Hashes for pytegrity-0.1.0.tar.gz
Algorithm Hash digest
SHA256 2aaecbd8ece2b191845266aff5078ce37b997e5d3263a3755d6255d30b41f02e
MD5 aaa580c0180c1fcabffa0c3abe6d72b9
BLAKE2b-256 751a819fdf440995ab3431951106e5816180e30f9976aa392e6926517f1fe8f9

See more details on using hashes here.

File details

Details for the file pytegrity-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: pytegrity-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 2.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.7

File hashes

Hashes for pytegrity-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 ecfb0a5d7874828fd59c662386d58e1d4855cd03161735b18e03f1554ee174c7
MD5 8850eda0634102b388a28c4e3ae6167e
BLAKE2b-256 ae0350ef87094b72783be1e47f6e62b0eeeecb307cf3550c8f1b789191ea9b43

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page