A new approach to derive an Acoustic Impedance Inversion volume is proposed in Petrel. Multi layer<br>neural networks as well as genetic algorithm are combined together in order to provide a robust and straight<br>forward seismic inversion.<br>Estimation of rock properties using seismic data and derived attributes has always been a very<br>important but challenging task. There are several "schools" using different methods in order to achieve this<br>goal. All of them are based on strong and constraining a-priori information. The required knowledge of an<br>initial model (cf. for the stochastic inversions), or source wavelet (cf. Colored-, Sparse Spike Inversion), is in<br>several cases hard to acquire, if not even impossible. Moreover, the result of this kind of inversion is often<br>biased by the input initial model itself.


Article metrics loading...

Loading full text...

Full text loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error