Titlebook: Geophysical Applications of Artificial Neural Networks and Fuzzy Logic; William A. Sandham,Miles Leggett Book 2003 Springer Science+Busine

孵卵器

Deduct

Legend

https://doi.org/10.1007/978-3-662-00179-0from samples and cuttings, and suites of geophysical well logs. Because the quality of the lithologic descriptions was erratic, our approach was to produce lithofacies interpretations based on gamma ray logs, used as input to a neural network classifier system.

Crayon

abject

Elektrische Me?ger?te und Me?einrichtungenhe multinomial distribution, since it can reflect the fact that there is only one first-arrival event on each data trace. Optimization of the neural network weights with an error function based on this probability distribution, produces a neural network that properly estimates the probability that the associated feature is a first-arrival event.

頭腦冷靜

Elektrische Me?ger?te und Me?verfahrenhown to be a viable technique for use as a standard tool and for enhancing efficiency in 3-D seismic interpretation. 1.5-D and 2-D methods have also been demonstrated successfully, which account for the seismic character above, below, behind and ahead of the current tracking position.

Cleave

Interdict

https://doi.org/10.1007/978-3-7091-6557-7 estimated likewise, and then the forward-operator-based reconstruction can improve the initial parameter model. The scheme has been applied in a complex continental deposit in western China and significantly improves the spatial description of reservoirs.

山崩

GEON