About: Geologic modelling is a research topic. Over the lifetime, 156 publications have been published within this topic receiving 2554 citations. The topic is also known as: geological modelling & geomodelling.
TL;DR: In this article, the location of the geological interfaces and orientation data from structural field are combined to model realistic, complex geometry: scalar functions representing separate geological series are merged automatically using geological rules to enable fast computation and easy update of interpretation.
TL;DR: A methodology developed to process geological information in this context, to build a 3D geological model of the subsoil over former coalmines used to store natural gas, which integrates the geological information available and is representative of the geological context.
TL;DR: In this article, the authors present key recent advances in carbonate exploration and reservoir analysis, highlighting the need for integrated structural and diagenetic approaches in order to understand how fractures evolve as fluid-flow conduits.
Abstract: Carbonate reservoirs contain an increasingly important percentage of the world's hydrocarbon reserves. This volume presents key recent advances in carbonate exploration and reservoir analysis. As well as a comprehensive overview of the trends in carbonate over the years, the volume focuses on four key areas:
1. emerging plays and techniques – with special reference to lacustrine plays in syn-rift basins and development of super-giant heavy oil plays
2. improved reservoir characterization – with examples from the Middle East and Europe and case studies of how outcrop analogues can provide key data for input to geological models
3. impact of fractures and faults in carbonates –contributors highlight the need for integrated structural and diagenetic approaches in order to understand how fractures evolve as fluid-flow conduits
4. advances in geomodelling of carbonate reservoirs –several papers discuss the application of new and innovative geomodelling and geostatistical techniques to carbonate reservoirs.
TL;DR: The results demonstrate that this deep learning-driven modeling approach can capture more realistic facies architectures and associations than existing geostatistical modeling methods, which often fail to reproduce heterogeneous nonstationary sedimentary facies with apparent depositional trend.
TL;DR: This study shows that it is advantageous to combine several modelling methods in areas with varying geological complexity and data density, and presents a 3D geological model combined by three different techniques.