Reactive transport modeling of fluid-rock interactions associated with carbonate diagenesis and implications for reservoir quality prediction

Reactive transport modeling of fluid-rock interactions associated with carbonate diagenesis and implications for reservoir quality prediction
Author :
Publisher : Cuvillier Verlag
Total Pages : 197
Release :
ISBN-10 : 9783736966499
ISBN-13 : 3736966490
Rating : 4/5 (490 Downloads)

Book Synopsis Reactive transport modeling of fluid-rock interactions associated with carbonate diagenesis and implications for reservoir quality prediction by : Ying Xiong

Download or read book Reactive transport modeling of fluid-rock interactions associated with carbonate diagenesis and implications for reservoir quality prediction written by Ying Xiong and published by Cuvillier Verlag. This book was released on 2022-07-26 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diagenesis research is the foundation of hydrocarbon reservoir characterization and exploration. Reactive transport modeling (RTM) is an emerging approach for diagenesis research, with unique capability of quantification and forward modeling of the coupled thermo-hydro-chemical processes of diagenesis. Using TOUGHREACT simulator, this thesis investigates the two most important fluid-rock interactions in carbonate rocks, i.e., dolomitization and karstification, based on generic model analyses and a case study in the Ordos Basin, China. In particular, this study attempts to quantitatively characterize the diagenetic processes and to reconstruct the diagenesis-porosity evolution of carbonate reservoirs. Some controversies in carbonate diagenesis research, which cannot be well explained by classical geological methods, have also been discussed. The results are helpful to better understand the spatial-temporal distribution and co-evolution of diagenesis-mineral-porosity during the complicated diagenetic processes with their potential controlling factors, and to reduce the uncertainty of reservoir quality prediction.


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