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Carbonate Petrophysical Rock Typing - Integrating Geological Attributes and Petrophysical Properties While Linking With Dynamic Behavior

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TLDR
In this paper, the authors propose a workflow for determining petrophysical rock types (PRTs), which control static properties and dynamic behaviour of the reservoir, while optimally linking to geological attributes (depositional and diagenetic) and their spatial interrelationships and trends.
Abstract
Abstract Carbonate rock typing provides a vehicle to propagate petrophysical properties through association with geological attributes and, therefore, is critical for distributing reservoir properties, such as permeability and water saturation, in the reservoir model. The conventional approaches to rock typing have significant gaps in incorporating diagenetic processes, transferring rock types from core to log domain, accounting for fractures and using appropriate methodology to realistically distribute rock types in the static reservoir model. The workflow proposed in this paper addresses these issues in a comprehensive way by determination of petrophysical rock types (PRTs), which control static properties and dynamic behaviour of the reservoir, while optimally linking to geological attributes (depositional and diagenetic) and their spatial interrelationships and trends. This approach is novel for the fact that it: (1) integrates geological processes, petrophysics and Earth modelling aspects of rock typing; (2) integrates core and log scales; and (3) provides a flexible ‘road map’ from core to 3D model for variable data scenarios that can be updated with progressive changes in data quality and quantity during the life cycle of an asset. This paper introduces the rationale behind this workflow, and demonstrates its workings and agility through deployment in two large carbonate fields.

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Citations
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References
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Classification of Carbonate Rocks According to Depositional Textures

TL;DR: In this paper, three textural features seem especially useful in classifying those carbonate rocks that retain their depositional texture: presence or absence of carbonate mud, which differentiates muddy carbonate from grainstone; abundance of grains, which allows muddy carbonates to be subdivided into mudstone, wackstone, and packstone; and presence of signs of binding during deposition, which characterizes boundstone.
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TL;DR: This report is a self-contained guide to application of Tough2 to subsurface flow problems, and gives a technical description of the TOUGH2 code, including a discussion of the physical processes modeled, and the mathematical and numerical methods used.
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Geologic Nomenclature and Classification of Porosity in Sedimentary Carbonates

TL;DR: In this paper, the authors present a taxonomic classification of porosity in sedimentary carbonates, based on the time and place in which porosity is created or modified, which is important elements of a genetically oriented classification.
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Conditional Simulation of Complex Geological Structures Using Multiple-Point Statistics

TL;DR: The approach proposed in this paper consists of borrowing the required multiple-point statistics from training images depicting the expected patterns of geological heterogeneities from the geostatistical numerical model where they are anchored to the actual data in a sequential simulation mode.
Journal ArticleDOI

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