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Pregled bibliografske jedinice broj: 509919

Neural networks in petroleum geology as interpretation tools


Malvić, Tomislav; Velić, Josipa; Horvath, Janina; Cvetković, Marko
Neural networks in petroleum geology as interpretation tools // Central European geology, 53 (2011), 1; 97-115 doi:10.1556/CEuGeol.53.2010.1.6 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 509919 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Neural networks in petroleum geology as interpretation tools

Autori
Malvić, Tomislav ; Velić, Josipa ; Horvath, Janina ; Cvetković, Marko

Izvornik
Central European geology (1788-2281) 53 (2011), 1; 97-115

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
neural network; log data; seismic; Croatia; Pannonian Basin
(neural network; log data; seismic; Croatia; Pannonian Basinneural network; log data; seismic; Croatia; Pannonian Basin)

Sažetak
Three examples of the use of neural networks in analyses of geologic data from hydrocarbon reservoirs are presented. All networks are trained with data originating from clastic reservoirs of Neogene age located in the Croatian part of the Pannonian Basin. Training always included similar reservoir variables, i.e. electric logs (resistivity, spontaneous potential) and lithology determined from cores or logs and described as sandstone or marl, with categorical values in intervals. Selected variables also include hydrocarbon saturation, also represented by a categorical variable, average reservoir porosity calculated from interpreted well logs, and seismic attributes. In all three neural models some of the mentioned inputs were used for analyzing data collected from three different oil fields in the Croatian part of the Pannonian Basin. It is shown that selection of geologically and physically linked variables play a key role in the process of network training, validating and processing. The aim of this study was to establish relationships between log-derived data, core data, and seismic attributes. Three case studies are described in this paper to illustrate the use of neural network prediction of sandstone-marl facies (Case Study # 1, Okoli Field), prediction of carbonate breccia porosity (Case Study # 2, Beničanci Field), and prediction of lithology and saturation (Case Study # 3, Kloštar Field). The results of these studies indicate that this method is capable of providing better understanding of some clastic Neogene reservoirs in the Croatian part of the Pannonian Basin.

Izvorni jezik
Engleski

Znanstvena područja
Geologija

Napomena
Science Citation Index Expanded (SciSearch), Journal Citation Reports/Science Edition, SCOPUS, Astrophysics Data System (ADS), Google Scholar, Current Contents/Physical, Chemical and Earth Sciences, EI-Compendex, GeoArchive, Geobase, GeoRef, OCLC, Petroleum Abstracts, SCImago, Summon by Serial Solutions On-line ISSN 1896-1517



POVEZANOST RADA


Projekti:
195-1951293-0237 - Stratigrafska i geomatematička istraživanja naftnogeoloških sustava u Hrvatskoj (Velić, Josipa, MZOS ) ( CroRIS)

Ustanove:
Rudarsko-geološko-naftni fakultet, Zagreb

Profili:

Avatar Url Marko Cvetković (autor)

Avatar Url Josipa Velić (autor)

Avatar Url Tomislav Malvić (autor)

Poveznice na cjeloviti tekst rada:

doi www.akademiai.com

Citiraj ovu publikaciju:

Malvić, Tomislav; Velić, Josipa; Horvath, Janina; Cvetković, Marko
Neural networks in petroleum geology as interpretation tools // Central European geology, 53 (2011), 1; 97-115 doi:10.1556/CEuGeol.53.2010.1.6 (međunarodna recenzija, članak, znanstveni)
Malvić, T., Velić, J., Horvath, J. & Cvetković, M. (2011) Neural networks in petroleum geology as interpretation tools. Central European geology, 53 (1), 97-115 doi:10.1556/CEuGeol.53.2010.1.6.
@article{article, author = {Malvi\'{c}, Tomislav and Veli\'{c}, Josipa and Horvath, Janina and Cvetkovi\'{c}, Marko}, year = {2011}, pages = {97-115}, DOI = {10.1556/CEuGeol.53.2010.1.6}, keywords = {neural network, log data, seismic, Croatia, Pannonian Basin}, journal = {Central European geology}, doi = {10.1556/CEuGeol.53.2010.1.6}, volume = {53}, number = {1}, issn = {1788-2281}, title = {Neural networks in petroleum geology as interpretation tools}, keyword = {neural network, log data, seismic, Croatia, Pannonian Basin} }
@article{article, author = {Malvi\'{c}, Tomislav and Veli\'{c}, Josipa and Horvath, Janina and Cvetkovi\'{c}, Marko}, year = {2011}, pages = {97-115}, DOI = {10.1556/CEuGeol.53.2010.1.6}, keywords = {neural network, log data, seismic, Croatia, Pannonian Basinneural network, log data, seismic, Croatia, Pannonian Basin}, journal = {Central European geology}, doi = {10.1556/CEuGeol.53.2010.1.6}, volume = {53}, number = {1}, issn = {1788-2281}, title = {Neural networks in petroleum geology as interpretation tools}, keyword = {neural network, log data, seismic, Croatia, Pannonian Basinneural network, log data, seismic, Croatia, Pannonian Basin} }

Časopis indeksira:


  • Scopus


Uključenost u ostale bibliografske baze podataka::


  • Geobase
  • Chemical Abstracts, Elsevier Geo Abstracts, Scopus, Referativnyi Zhurnal, Zoological Abstracts


Citati:





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