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Abstract

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.

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/content/papers/10.3997/2214-4609-pdb.254.GP19
2009-03-01
2021-10-21
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609-pdb.254.GP19
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