Geophysical 3D Inversion Modelling is a powerful technique used to analyze and interpret geophysical data (such as magnetic, gravity, seismic, resistivity, or electromagnetic data) in order to create a detailed three-dimensional model of the subsurface structure.

The inversion process aims to convert the observed geophysical measurements into a representation of subsurface properties, such as geological formations, material distributions, or the location of resources like minerals, hydrocarbons, or groundwater.

Here’s a more detailed breakdown of Geophysical 3D Inversion Modelling:

1. Basic Concept of Inversion in Geophysics

  • Inversion is the process of deducing the subsurface distribution of physical properties (such as density, magnetization, resistivity, or velocity) from geophysical measurements made at or near the surface. This is the reverse process of forward modelling, where a subsurface model is used to predict geophysical data.
  • Geophysical inversion is typically ill-posed, meaning there is no unique solution, and multiple subsurface models may explain the same observed data. Therefore, inversion algorithms aim to find the best fit between the model and the observed data, often with constraints to make the solution more realistic.

2. Types of Geophysical Data Used

Geophysical surveys collect a wide range of data, including:

  • Magnetic data (measuring variations in the Earth’s magnetic field)
  • Gravity data (measuring variations in the Earth’s gravitational field)
  • Seismic data (measuring wave velocities in the Earth)
  • Electromagnetic (EM) data (measuring resistivity or conductivity of subsurface materials)
  • Electrical Resistivity (measuring how easily electrical current can pass through subsurface materials)
  • Ground Penetrating Radar (GPR) (high-resolution subsurface imaging, often used for shallow depths)

3. 3D Inversion Process

In 3D inversion modelling, the goal is to construct a model of the subsurface in three dimensions (x, y, and z) that best explains the geophysical data. Here are the general steps involved:

a. Data Collection

  • Field measurements: Geophysical data is collected from surveys (e.g., magnetic, seismic, or electrical measurements) that are conducted at the Earth’s surface or through boreholes.
  • Survey Design: The design of the survey grid or the positioning of the sensors (e.g., for airborne or ground surveys) is important for resolving the subsurface features accurately.

b. Initial Model (Starting Point)

  • In the inversion process, an initial or “starting” model of the subsurface is constructed. This can be based on geological knowledge or simple assumptions (like a uniform background).

c. Forward Modelling

  • The initial model is used to generate synthetic geophysical data using forward modelling techniques. Forward modelling calculates the expected geophysical measurements based on the properties (e.g., magnetization, density, resistivity) assigned to different regions of the model.
  • Forward modelling is done using physical equations that describe how the geophysical field (e.g., magnetic, gravity, etc.) behaves in the presence of different materials or structures in the subsurface.

d. Comparison to Observed Data

  • The synthetic data from the forward model is compared to the observed field data. The difference between the modeled and observed data is called the misfit or residual.

e. Optimization / Inversion Algorithm

  • The inversion algorithm adjusts the model parameters (e.g., subsurface properties like density, resistivity, or velocity) iteratively to minimize the difference (misfit) between the predicted and observed data.
  • Common inversion algorithms used include:
    • Least-Squares Inversion: Minimizes the squared difference between observed and predicted data.
    • Gauss-Newton and Levenberg-Marquardt methods: Used for non-linear problems, which are common in geophysics.
    • Simulated Annealing and Genetic Algorithms: These methods can be used to avoid local minima in the inversion process.
    • Conjugate Gradient Methods: Often used in large-scale inversions.

f. Regularization and Constraints

  • Regularization techniques are employed to stabilize the inversion process and ensure a realistic, physically plausible model. This may involve:
    • Smoothness constraints: Preventing abrupt changes between adjacent cells or model parameters to avoid overfitting to noise.
    • Geological constraints: Incorporating prior knowledge (e.g., boundaries, geological layers) into the inversion process to improve the interpretation.
    • Depth or spatial constraints: To avoid unrealistic models at extreme depths or at spatial locations where no data exists.

g. Final Model and Interpretation

  • Once the inversion converges, the result is a 3D model of the subsurface that explains the observed geophysical data as best as possible.
  • The final model typically includes parameters such as:
    • Magnetic susceptibility (for magnetic data)
    • Density (for gravity data)
    • Electrical resistivity or conductivity (for EM or resistivity data)
    • Velocity (for seismic data)
  • The model can be visualized in 3D and used for further interpretation, such as identifying geological structures, resource exploration (e.g., mineral deposits or oil/gas reserves), or environmental analysis.

4. Applications of 3D Geophysical Inversion Modelling

3D inversion modelling is widely applied in various fields, including:

  • Mineral Exploration: Mapping subsurface ore bodies and identifying geophysical anomalies that may indicate the presence of valuable minerals (e.g., gold, copper, iron ore).
  • Oil and Gas Exploration: Identifying hydrocarbon reservoirs by mapping the distribution of geological layers and their properties (such as velocity, density, and porosity).
  • Environmental and Engineering Studies: Detecting contamination plumes, buried structures (e.g., pipelines, tanks), or assessing groundwater resources.
  • Seismic Imaging: Producing high-resolution 3D images of the Earth’s subsurface to study faults, layers, and reservoirs.
  • Geothermal and Groundwater Studies: Mapping thermal properties, hydraulic conductivity, or aquifer boundaries for sustainable resource management.

Geophysical 3D Forward Model (UBC GIF Tools)

Conclusion

Geophysical 3D inversion modelling is an essential tool in modern geophysics for creating detailed and accurate representations of subsurface structures based on surface or near-surface measurements. By using advanced computational algorithms and iterative methods, geophysicists can interpret complex datasets and gain valuable insights for exploration, environmental monitoring, and scientific research. However, it comes with challenges like non-uniqueness, data noise, and computational demands, requiring careful handling and interpretation of results.