A Neural Networks Based Seismic Object Detection Technique

Seismic technology has historically focused on resolving the structures. To a lesser degree, presence or absence of reservoir has also been a focus. This paper shows the use of seismic data to detect several other “seismic objects”. The technique to be referred to as “meta attribute”, uses the combination of “artificial intelligence” of neural networks and the “natural intelligence” of an interpreter. Examples of many geologic features and reservoir properties detected using this technique will be provided. They include hydrocarbon probability, lithofacies, chimney, faults and salt.