What are the advantages and challenges of using seismic inversion for petrophysical estimation?

1 What is seismic inversion?

Seismic inversion is a process that converts seismic reflection data into a model of the subsurface acoustic impedance. Acoustic impedance is the product of the density and velocity of the rock, and it reflects the contrast between different layers. By inverting the seismic data, petrophysicists can obtain a more continuous and detailed picture of the subsurface structure and properties, rather than relying on discrete well logs or sparse seismic traces.

2 Why use seismic inversion for petrophysical estimation?

Seismic inversion can provide valuable information for petrophysical estimation, such as the porosity, lithology, and fluid content of the reservoir. These parameters are important for assessing the reservoir quality and productivity, as well as for identifying potential hydrocarbon zones. For example, low acoustic impedance can indicate high porosity or gas saturation, while high acoustic impedance can indicate low porosity or oil saturation. Seismic inversion can also help to reduce the ambiguity and noise in the seismic data, and to enhance the resolution and contrast of the features of interest.

3 What are the types of seismic inversion?

Different types of seismic inversion exist, depending on the input data, the output model, and the inversion method. Band-limited inversion uses only the seismic data as input and produces an acoustic impedance model that matches the frequency range of the seismic data. This method is fast and simple, but may not capture low and high frequency components of the impedance. Model-based inversion uses both the seismic data and a low-frequency model as input to produce an acoustic impedance model that matches the full frequency range of the impedance. This type is more accurate and realistic, but requires a good initial model and more computation. Finally, sparse-spike inversion uses only the seismic data as input to produce a sparse model of the acoustic impedance consisting of only main changes or spikes. This type is useful for highlighting boundaries and interfaces, yet may not represent gradual variations or thin layers.

4 What are the challenges of seismic inversion?

Seismic inversion is not a simple or unique process, as it involves assumptions, limitations, and uncertainties that can impact the quality and reliability of the output model. Data quality, resolution, uncertainty, and interpretation are all common challenges when it comes to seismic inversion. Data quality can influence the accuracy and resolution of the inversion, while resolution can limit the ability to resolve thin layers or small features. The uncertainty of the inversion can be caused by various factors, such as non-uniqueness of the problem, noise and errors in the data, variability and complexity of the subsurface, and lack of well constraints. Lastly, interpretation of the inversion is challenging and subjective; it requires knowledge of rock physics relationships, geological context, reservoir behavior, and a careful analysis of the inverted model.

5 How to overcome the challenges of seismic inversion?

Seismic inversion is not a perfect or definitive solution, but it can be improved and optimized by applying best practices and techniques. Data processing, such as enhancing, filtering, deconvolving, and aligning the seismic data can improve the data quality and reduce noise and errors. Model building, which involves constructing a low-frequency model or a background model for the inversion, can provide a better starting point and constraint. Inversion method selection affects the speed, accuracy, and resolution of the inversion. Uncertainty analysis should be used to quantify, evaluate, and reduce uncertainty of the inversion. Rock physics involves establishing relationships between acoustic impedance and rock properties/fluid content to facilitate interpretation of the inversion.

6 Here’s what else to consider

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