# 9.5.3. 3D Inversion¶

## 9.5.3.1. Purpose¶

In this section, we will invert the simulated data in 3D with three strategies:

Note

Example

## 9.5.3.3. Step by step¶

Tip

If you have already completed either the Survey Design and Simulation or the 2D Inversion demo, you may advance directly to the Unconstrained Inversion Section

• Step 1: Setup
• Step 2: Survey and Data

## 9.5.3.4. Case 1: Unconstrained Inversion¶

As a first step, we invert the simulated data with a purely unconstrained approach.

## 9.5.3.5. Case 2: Sensitivity weighted inversion¶

The result obtained with the unconstrained approach appears to be dominated by the source-receiver position, with most of the conductivity anomalies recovered near the survey lines. In order to reduce this geometric bias, we will incorporate sensitivity-based weights.

Note

This solution is an improvement over the purely unconstrained as lower conductivity anomalies are recovered at the electrodes, while the conductive kimberlites are better recovered

## 9.5.3.6. Case 3: Inversion with 2D starting model¶

In the third case, we will incorporate the stiched 2D model in the 3D inversion through a starting and a reference model.

To create a full 3D model from the merge 2D models created in the merging step, the steps are:

• Right-click on the merged model

• Select Edit -> Fill/Interpolate no-data-value (see the documentation)

• Keep the default parameters and enter 1e-8 as no-data-value and choose the Log interpolation

Then you can use that model as starting and reference model:

Note

We have once again improved the solution, and the iteration process is a lot quicker since we are starting with a model closer to the final solution.