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Stochastic – advantages and uncertainties for subsurface geological mapping and volumetric or probability calculation


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[1] Dubrule, O. (1998): Geostatistics in Petroleum Geology. American Association of Petroleum Geologists, Volume 38, Tulsa, 210 p.10.1306/CE3823Search in Google Scholar

[2] Kelkar, M., Perez, G. (2002): Applied Geostatistics for Reservoir Characterization. Society of Petroleum Engineers, Richardson, 264 p.10.2118/9781555630959Search in Google Scholar

[3] Malvić, T. (2008): Primjena geostatistike u analizi geoloških podataka (Application of geostatistics in geological data analysis). University literature, INA Plc., Zagreb, 103 p. (in Croatian).Search in Google Scholar

[4] Malvić, T. (2008): Kriging, cokriging or stochastical simulations, and the choice between deterministic or sequential approaches. Geologia Croatica, 61(1), pp. 37–47.10.4154/gc.2008.06Search in Google Scholar

[5] Novak Zelenika, K., Malvić, T. (2011): Stochastic simulations of dependent geological variables in sandstone reservoirs of Neogene age: A case study of Kloštar Field, Sava Depression. Geologia Croatica, 64(2), pp. 173–183.10.4154/gc.2011.15Search in Google Scholar

[6] Novak Zelenika, K., Malvić, T. (2014): Utvrđivanje sekvencijskim indikatorskim metodama slabopro-pusnih litofacijesa kao vrste nekonvencionalnih ležišta ugljikovodika na primjeru polja Kloštar (Determination of low permeable lithofacies, as type of unconventional hydrocarbon reservoirs, using sequential indicator methods, case study from the Kloštar Field). Rudarsko-geološko-naftni zbornik, 28(1), pp. 23–38. (in Croatian with English abstract).Search in Google Scholar

[7] Novak Zelenika, K., Velić, J., Malvić, T. (2013): Local sediment sources and palaeoflow directions in Upper Miocene turbidites of the Pannonian Basin System (Croatian part), based on mapping of reservoir properties. Geological Quarterly, 57(1), pp. 17–30.10.7306/gq.1068Search in Google Scholar

[8] Balić, D., Malvić, T. (2010): Ordinary Kriging as the most Appropriate Interpolation Method for Porosity in the Sava Depression Neogene Sandstone. Naftaplin, 30(3), pp. 81–90.Search in Google Scholar

[9] Malvić, T., Rusan, I. (2009): Investment risk assessment of potential hydrocarbon discoveries in a mature basin. Case study from the Bjelovar Sub-Basin, Croatia. Oil, gas – European Magazine, 35(2), pp. 67–72.Search in Google Scholar

[10] Režić, M. (2016): Opći model za izračun geološke vjerojatnosti novih otkrića plina na području Sjevernog Jadrana uz primjer plinskog polja Ika (General model for the calculation of geological probability associated with new gas discoveries in the Northern Adriatic with an example of the Ika gas field), Diploma Thesis. Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering; 48 p. (in Croatian with English summary).Search in Google Scholar

[11] Malvić, T., Velić, J., Režić, M. (2016): Geological probability calculation of new gas discoveries in wider area of Ivana and Ika Gas Fields, Northern Adriatic, Croatia. RMZ – Materials and Geoenvironment, 63(3), pp. 127–137.10.1515/rmzmag-2016-0012Search in Google Scholar

[12] Malvić, T., Rajić, R., Slavinić, P. & Novak Zelenika, K. (2014): Numerical integration in volume calculation of irregular anticlines. Rudarsko-geološko-naftni zbornik, 28(2), pp. 1–8.Search in Google Scholar

[13] Husanović, E. & Malvić, T. (2014): Review of deterministic geostatistical mapping of Croatian hydrocarbon reservoirs and advantages of such approach (Pregled dosadašnjih determinističkih geostatističkih kartiranja ležišta ugljikovodika u Republici Hrvatskoj te prednosti takvoga pristupa). Nafta, 65, 1, 57–68.Search in Google Scholar

[14] Malvić, T. (2009): Stochastical approach in deterministic calculation of geological risk – theory and example (Stohastički pristup u determinističkom izračunu geološkoga rizika – teorija i primjer). Nafta, 60, 12, 651662.Search in Google Scholar

[15] Malvić, T., Velić, J. (2015): Stochastically improved methodology for probability of success (‘POS’) calculation in hydrocarbon systems. RMZ – Materials and geoenvironment, 62(3), pp. 149–155.Search in Google Scholar

[16] Gaurina-Međimurec, N., Novak-Mavar, K. (2017): Depleted hydrocarbon reservoirs and CO2 injection wells – CO2 leakage assessment. Rudarsko-geološko-naftni zbornik, 36, pp. 15–27.10.17794/rgn.2017.2.3Search in Google Scholar

[17] Atkinson, K.E. (1989): An introduction to Numerical Analysis. 2nd ed., John Wiley and Sons: New York; 712 p.Search in Google Scholar

[18] Kevo, M. (1986): Numerička integracija (Numerical integration – Slovenian, issue in Serbian). Moj mikro, 2,7, pp. 25–28.Search in Google Scholar

[19] Quarteroni, A., Sacco, R., Saleri, F. (2000): Numerical Mathematics. Springer-Verlag: New York; 654 p.Search in Google Scholar

[20] Malvić, T. (2015): Upute za uporabu planimetra (Instructions to measure with planimeter). University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering (handbook), Zagreb, 20 p. (in Croatian).Search in Google Scholar

[21] Deutsch, C.V., Journel, A.G.: GSLIB – Geostatistical Software Library and User’s Guide. – 2nd edition, Oxford University Press: New York – Oxford, 369 p.Search in Google Scholar