--> A Multidisciplinary Approach for Rock Typing Characterization In A Highly Heterogeneous Carbonate Reservoir in Abu Dhabi UAE
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A Multidisciplinary Approach for Previous HitRockNext Hit Typing Characterization In A Highly Heterogeneous Carbonate Previous HitReservoirNext Hit in Abu Dhabi UAE

Abstract

Nowadays, there is a significant number of Previous HitreservoirNext Hit models that are purely constrained to numerical Previous HitreservoirNext Hit perception. Moreover, such models neglect the influence of geological events which are essential in characterizing and modeling carbonate reservoirs. This mentioned approach leads to conceptual errors because ideally, a Previous HitreservoirNext Hit model would enable heterogeneities predictability and mitigate Previous HitreservoirNext Hit-modeling uncertainty. The objective of this paper is to show the results obtained from an integrated Previous HitreservoirNext Hit Previous HitrockNext Hit-typing characterization process for its subsequent implementation into Previous HitreservoirNext Hit models. This multi-disciplinary study emerged as the fundamental pillar to model the Lower Cretaceous Thamama Group in a major Oil Field in the Arabian Plate. This Previous HitrockNext Hit-typing approach intends to define Previous HitrockNext Hit types (referred as Static Previous HitRockNext Hit Types (SRTs) in this paper) which result from the combination of two sub- processes, the Petrophysical Synthesis and the Geologic Synthesis. The latter aims to define Facies groups by relating depositional facies and their associated diagenetic processes. On the other hand, the Petrophysical Synthesis proposes to define petrophysical groups based on a combination of similar petrophysical characteristics. Ultimately, this Previous HitrockNext Hit-typing approach enables generating Static Previous HitRockNext Hit Types defined by the reconciliation of related geologic and petrophysical patterns. The data inventory for this study includes detailed Core Description, RCA, SCAL and of Log data. Applying consistent data quality validation, which allows implementing a robust workflow combining deterministic methods and machine learning supported algorithms for data analysis. Static Previous HitRockNext Hit Types (SRT) were classified through distinctive sets of geologic and petrophysical groups. This classification resulted in four SRTs. SRT 1 exhibiting enhanced Previous HitreservoirNext Hit properties product of early diagenesis, SRT2 is dominated by neutral diagenetic processes that preserve Previous HitreservoirNext Hit properties, SRT3 and SRT4 are both associated to late diagenetic property reducing processes that distort arrangement of minerals and pore structure. The major achievement of this Previous HitrockNext Hit-typing approach resumed in the integration of the Geology and Petrophysics. This integration enable finding significant evidence to understand Previous HitreservoirNext Hit properties at depositional stage, properties alteration product of diagenetic processes and Previous HitreservoirNext Hit dynamic behavior links to a geologic concept. This Previous HitrockNext Hit-typing approach changes the traditional practice, formerly used to model this particular Previous HitreservoirNext Hit, which was limited only to the classification of petrophysical patterns, instead, this approach allows associating a particular petrophysical pattern to a singular geologic facies, feature or event. Ultimately, via the integration of dynamic and static data, Previous HitreservoirNext Hit models become more predictive. Similarly, the basis of the Previous HitrockNext Hit-typing approach presented herein brings together a solid static understanding in order to delineate the origin of particular Previous HitreservoirNext Hit dynamic behaviors. This fit-for- purpose approach built from the premise of integration provides a complete basis for Previous HitreservoirNext Hit simulation, management, and forecasting, and at the same time contributes reducing Previous HitreservoirNext Hit uncertainties by means of enhancing heterogeneities predictability, dynamic flow understanding, which all combined yields organically into optimized field development strategies.