Naslov
Successfulness of different neural network algorithms for missing well log data prediction – Example from the Sava Depression

Autori
Cvetković, Marko ; Bošnjak, Marija

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
XIII. Congres of Hiungarian geomathematics and the II. Congress of Croatian and Hhungarian geomathematics "Applications of geostatistics, GIS and remote sensing in the fields of geosciences and environmental protection : abstract book / - Mórahalom, 2009, 11-11

Skup
Congres of Hiungarian geomathematics (13 ; 209) ; Congress of Croatian and Hhungarian geomathematics (2 ; 2009)

Mjesto i datum
Mórahalom, Mađarska, 21.05.2009. - 23.05.2009

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
neural networks; well logs; Pannonian Basin

Sažetak
Intervals with missing well log data can be successfully amended with neural network predicted data (Sagaff and Nebrija, 2003). Process for completing well log data consists of training the neural network on the well with the complete set of curves and applying the neural network to predict the missing data. For this procedure well log curves, least dependent on mud properties, were chosen for better well to well to well prediction. Three wells with gamma ray, neutron porosity and acoustic well log curves were selected form Kloštar oil field. Three different neural network types were used: multi layer perceptron, radial basis function and generalized regression neural network. Program used for the neural network analysis was StatSoft STATISTICA 7. Well to well prediction was successfully achieved. Best results came from multi layer perceptron and generalized regression neural networks.

Izvorni jezik
Engleski

Znanstvena područja
Geologija

POVEZANOST RADA