# resistivityVES

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/git/https%3A%2F%2Fgit.geophysik.ruhr-uni-bochum.de%2Fkasper%2FresistivityVES.git/HEAD?urlpath=%2Fdoc%2Ftree%2FVES.ipynb)

Binder environment using [pyGIMLI](https://www.pygimli.org/) to do a VES (Vertical Electrical Sounding) inversion.

## Overview

This repository contains a Jupyter notebook (`VES.ipynb`) that demonstrates how to perform 1D DC resistivity inversion using pyGIMLI's built-in VES forward operator. The notebook uses real field data from Bausenberg to invert for a layered earth model.

## Notebook Contents

The `VES.ipynb` notebook includes the following workflow:

### 1. Setup and Imports

- Imports necessary libraries: `numpy`, `matplotlib`, `pygimli`, and the `VESManager` from `pygimli.physics`

### 2. Field Data from Bausenberg

- Uses real VES measurements with AB/2 distances ranging from 1.0 to 100.0 meters
- Apparent resistivity values (`rhoa`) showing variations from ~64 to ~672 Ωm
- Error estimates set at 2% for most measurements, increasing to 5% for deeper soundings
- MN/2 spacing fixed at 0.5 meters

### 3. Inversion Setup

- Configures a 3-layer earth model (`nlay=3`)
- Uses regularization parameter `lam=1000` with a reduction factor of 0.8
- Inverts the apparent resistivity data to determine layer thicknesses and resistivities

### 4. Visualization

The notebook provides comprehensive visualization including:

- **Model plot**: Displays the inverted resistivity model as a function of depth (up to 50m)
- **Data fit plot**: Compares measured apparent resistivity data with the model response
- Both plots are displayed side-by-side for easy comparison

### 5. Uncertainty Analysis

- Computes model covariance matrix to assess parameter uncertainties
- Displays correlation matrix showing interdependencies between layer parameters
- Generates error bars for both resistivities and layer thicknesses
- Visualizes uncertainties at layer midpoints and boundaries

## Requirements

See `environment.yml` for the complete list of dependencies. Main requirements:

- pyGIMLI>=1.5.0, which requires at least:
  - numpy
  - matplotlib
  - suitesparse=5.10.1
- jupyterlab

## Usage

Click the Binder badge above to launch an interactive session, or run locally with:

```bash
jupyter notebook VES.ipynb
```