Generating geologically realistic 3D reservoir facies models using deep learning of sedimentary architecture with generative adversarial networks

Abstract This paper proposes a novel approach for generating 3-dimensional complex geological facies models based on deep generative models. It can reproduce a wide range of conceptual geological models while possessing the flexibility necessary to honor constraints such as well data. Compared with...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:Petroleum Science
المؤلفون الرئيسيون: Tuan-Feng Zhang, Peter Tilke, Emilien Dupont, Ling-Chen Zhu, Lin Liang, William Bailey
التنسيق: مقال
اللغة:الإنجليزية
منشور في: KeAi Communications Co., Ltd. 2019-06-01
الموضوعات:
Geological facies
Geomodeling
Data conditioning
Generative adversarial networks
الوصول للمادة أونلاين:http://link.springer.com/article/10.1007/s12182-019-0328-4

الانترنت

http://link.springer.com/article/10.1007/s12182-019-0328-4

مواد مشابهة