An Integrated Workflow for the Quantitative Assessment and Prediction of 3D Pore Network Evolution in Carbonate Reservoir Rocks

2011 ◽  
Author(s):  
Eva De Boever ◽  
ClC)ment Varloteaux ◽  
Fadi Nader ◽  
Anneleen Foubert ◽  
Samir Bekri ◽  
...  
Keyword(s):  
Quantitative Assessment ◽  
Pore Network ◽  
Network Evolution ◽  
Carbonate Reservoir ◽  
Reservoir Rocks

scholarly journals Quantification and Prediction of the 3D Pore Network Evolution in Carbonate Reservoir Rocks

2012 ◽  
Vol 67 (1) ◽  
pp. 161-178 ◽  
Author(s):  
E. De Boever ◽  
C. Varloteaux ◽  
F.H. Nader ◽  
A. Foubert ◽  
S. Békri ◽  
...  
Keyword(s):  
Pore Network ◽  
Network Evolution ◽  
Carbonate Reservoir ◽  
Reservoir Rocks

Late Permian carbonate concretions in the marine siliciclastic sediments of the Ravnefjeld Formation, East Greenland

2002 ◽  
pp. 126-132
Author(s):  
Jesper Kresten Nielsen ◽  
Nils-Martin Hanken
Keyword(s):  
Mineral Resources ◽  
Sedimentary Basins ◽  
Sedimentary Facies ◽  
Carbonate Reservoir ◽  
Upper Permian ◽  
Late Permian ◽  
East Greenland ◽  
Reservoir Rocks ◽  
Carbonate Concretions ◽  
Siliciclastic Sediments

NOTE: This article was published in a former series of GEUS Bulletin. Please use the original series name when citing this article, for example: Kresten Nielsen, J., & Hanken, N.-M. (2002). Late Permian carbonate concretions in the marine siliciclastic sediments of the Ravnefjeld Formation, East Greenland. Geology of Greenland Survey Bulletin, 191, 126-132. https://doi.org/10.34194/ggub.v191.5140 _______________ This investigation of carbonate concretions from the Late Permian Ravnefjeld Formation in East Greenland forms part of the multi-disciplinary research project Resources of the sedimentary basins of North and East Greenland (TUPOLAR; Stemmerik et al. 1996, 1999). The TUPOLAR project focuses on investigations and evaluation of potential hydrocarbon and mineral resources of the Upper Permian – Mesozoic sedimentary basins. In this context, the Upper Permian Ravnefjeld Formation occupies a pivotal position because it contains local mineralisations and has source rock potential for hydrocarbons adjacent to potential carbonate reservoir rocks of the partly time-equivalent Wegener Halvø Formation (Harpøth et al. 1986; Surlyk et al. 1986; Stemmerik et al. 1998; Pedersen & Stendal 2000). A better understanding of the sedimentary facies and diagenesis of the Ravnefjeld Formation is therefore crucial for an evaluation of the economic potential of East Greenland.

Enhanced and Rock Typing-Based Reservoir Characterization of the Palaeocene Harash Carbonate Reservoir-Zelten Field-Sirte Basin-Libya

2021 ◽  
Author(s):  
Mohamed Masoud ◽  
W. Scott Meddaugh ◽  
Masoud Eljaroshi ◽  
Khaled Elghanduri
Keyword(s):  
Rock Type ◽  
Carbonate Reservoir ◽  
Classification Model ◽  
Reservoir Rocks ◽  
The Core ◽  
Core Samples ◽  
Rock Types ◽  
Rock Typing ◽  
Open Hole ◽  
Type Classification

Abstract The Harash Formation was previously known as the Ruaga A and is considered to be one of the most productive reservoirs in the Zelten field in terms of reservoir quality, areal extent, and hydrocarbon quantity. To date, nearly 70 wells were drilled targeting the Harash reservoir. A few wells initially naturally produced but most had to be stimulated which reflected the field drilling and development plan. The Harash reservoir rock typing identification was essential in understanding the reservoir geology implementation of reservoir development drilling program, the construction of representative reservoir models, hydrocarbons volumetric calculations, and historical pressure-production matching in the flow modelling processes. The objectives of this study are to predict the permeability at un-cored wells and unsampled locations, to classify the reservoir rocks into main rock typing, and to build robust reservoir properties models in which static petrophysical properties and fluid properties are assigned for identified rock type and assessed the existed vertical and lateral heterogeneity within the Palaeocene Harash carbonate reservoir. Initially, an objective-based workflow was developed by generating a training dataset from open hole logs and core samples which were conventionally and specially analyzed of six wells. The developed dataset was used to predict permeability at cored wells through a K-mod model that applies Neural Network Analysis (NNA) and Declustring (DC) algorithms to generate representative permeability and electro-facies. Equal statistical weights were given to log responses without analytical supervision taking into account the significant log response variations. The core data was grouped on petrophysical basis to compute pore throat size aiming at deriving and enlarging the interpretation process from the core to log domain using Indexation and Probabilities of Self-Organized Maps (IPSOM) classification model to develop a reliable representation of rock type classification at the well scale. Permeability and rock typing derived from the open-hole logs and core samples analysis are the main K-mod and IPSOM classification model outputs. The results were propagated to more than 70 un-cored wells. Rock typing techniques were also conducted to classify the Harash reservoir rocks in a consistent manner. Depositional rock typing using a stratigraphic modified Lorenz plot and electro-facies suggest three different rock types that are probably linked to three flow zones. The defined rock types are dominated by specifc reservoir parameters. Electro-facies enables subdivision of the formation into petrophysical groups in which properties were assigned to and were characterized by dynamic behavior and the rock-fluid interaction. Capillary pressure and relative permeability data proved the complexity in rock capillarity. Subsequently, Swc is really rock typing dependent. The use of a consistent representative petrophysical rock type classification led to a significant improvement of geological and flow models.

Nanoscale Pore Network Evolution of Xiamaling Marine Shale during Organic Matter Maturation by Hydrous Pyrolysis

2020 ◽  
Vol 34 (2) ◽  
pp. 1548-1563 ◽  
Author(s):  
Yang Wang ◽  
Luofu Liu ◽  
Qinhong Hu ◽  
Lewei Hao ◽  
Ximeng Wang ◽  
...  
Keyword(s):  
Organic Matter ◽  
Pore Network ◽  
Network Evolution ◽  
Marine Shale ◽  
Hydrous Pyrolysis ◽  
Nanoscale Pore
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