Application of neural networks in petroleum reservoir lithology and saturation prediction
Summary: The Kloštar oil field is situated in the northern part of the Sava Depression within the Croatian part of the Pannonian Basin. The major petroleum reserves are confi ned to Miocene sandstones that comprise two production units: the Lower Pontian I sandstone series and the Upper Pannonian II...
| Permalink: | http://skupni.nsk.hr/Record/nsk.NSK01000739878/Details |
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| Matična publikacija: |
Geologia Croatica 62 (2009), 2 ; str. 115-121 |
| Glavni autor: | Cvetković, Marko (-) |
| Ostali autori: | Velić, Josipa (-), Malvić, Tomislav |
| Vrsta građe: | Članak |
| Jezik: | eng |
| Predmet: | |
| Online pristup: |
Geologia Croatica |
| LEADER | 02161caa a2200301 i 4500 | ||
|---|---|---|---|
| 001 | NSK01000739878 | ||
| 003 | HR-ZaNSK | ||
| 005 | 20121112102347.0 | ||
| 007 | ta | ||
| 008 | 100527s2009 ci ||| ||eng | ||
| 035 | |a (HR-ZaNSK)000739878 | ||
| 040 | |a HR-ZaNSK |b hrv |c HR-ZaNSK |e ppiak | ||
| 042 | |a croatica | ||
| 044 | |a ci |c hr | ||
| 080 | |a 55 |2 MRF 1998. | ||
| 100 | 1 | |a Cvetković, Marko | |
| 245 | 1 | 0 | |a Application of neural networks in petroleum reservoir lithology and saturation prediction / |c Marko Cvetković, Josipa Velić, Tomislav Malvić. |
| 300 | |b Ilustr. | ||
| 504 | |a Bibliografija: 22 jed | ||
| 520 | 8 | |a Summary: The Kloštar oil field is situated in the northern part of the Sava Depression within the Croatian part of the Pannonian Basin. The major petroleum reserves are confi ned to Miocene sandstones that comprise two production units: the Lower Pontian I sandstone series and the Upper Pannonian II sandstone series. We used well logs from two wells through these sandstones as input data in the neural network analysis, and used spontaneous potential and resistivity logs (R16 and R64) as the input in network training. The fi rst analysis included prediction of lithology, which was defined as either sandstone or marl. These two rock types were assigned categorical values of 1 or 0 which were then used in numerical analysis. The neural network was also used to predict hydrocarbon saturation in selected wells. The input dataset was extended to depth and categorical lithology. The prediction results were excellent, because the training and prediction dataset showed little disagreement between the true and predicted values. At present, this study represents the best and most useful application of neural networks in the Croatian part of the Pannonian Basin | |
| 653 | 0 | |a Neuralna mreža |a Zasićenje ugljikovodicima |a Pješčenjak | |
| 653 | 5 | |a Kloštar (polje) | |
| 700 | 1 | |a Velić, Josipa | |
| 700 | 1 | |a Malvić, Tomislav | |
| 773 | 0 | |t Geologia Croatica |x 1330-030X |g 62 (2009), 2 ; str. 115-121 | |
| 981 | |b B06/09 |p CRO | ||
| 998 | |a dalo100708 |c vol2o121112 | ||
| 856 | 4 | 2 | |u http://hrcak.srce.hr/geologia-croatica |y Geologia Croatica |