The Arab C reservoir interval of Qatar Petroleum's Dukhan Field is a prolific oil producer. After sixty years of development activity and with hundreds of logged and cored wells, there is an extensive database of rock, geophysical and production surveillance information available for interrogation. The reservoir hosts an accumulation of carbonate lithologies and textures representing a depositional organization of subtidal, intertidal and sabkha environments. A Transgressive System Tract defines the Lower Arab C, migrating upwards from a complex of beach grainstones to a maximum flooding surface featuring muddy carbonates with sporadic encrustations and associated Thrombolite growths. High frequency parasequences within the overlying Highstand System Tract (HST) of the Upper Arab C form a sedimentological pattern from intertidal to sabkha facies, with increasing prevalence of thin isolated high productivity grainstones. From a practical engineering perspective, the upper parts of the HST collocate with development uncertainties associated with erratic patterns of producer support from offset water injectors. Core descriptions characterize these intervals as low permeability mud dominated tidal flats hosting sporadic conductive grainstone tidal channels, leeward of beach barrier islands. Qatar Petroleum has adopted coastal hydrodynamic principles to predict grainstone anisotropic variations. The model for the shelf area has been compartmentalized into depositional tracts based on core descriptions, supplemented by predicted facies at non-cored vertical and horizontal wells using inter-dependent 3D-spatial and 1D log-based fuzzy probability. Vector representations of interpreted tidal flux directions have been used to assign analogy-realistic geometries for beach and tidal channel deposits within an environment of deposition framework. The output distributions reflect a close coupling of control data at wells within the context of sedimentary depositional dynamics, linked to production surveillance. An objective for high resolution 3D static modeling of rock textural and petrophysical anisotropy is the optimization of future infill horizontal wells to maximize IOR sweep efficiency.
A challenge for carbonate rock classification in reservoir models is the seemingly chaotic variability in the total pore system which ultimately controls petrophysical and dynamic behaviour. The aim of this study is to describe and spatially model a unified rock-typing scheme aligning the dual requirement for: 1) hydraulically consistent rock classes suited to numerical flow simulation, and 2) heterogeneity shaped according to field-scale geological anisotropy. Description of a suite of samples derived from the Jurassic Arab Formation reservoirs in the Dukhan Field, Qatar, facilitated the following:• Definition of petrophysical rock classes based on consistent pore and capillary pressure characteristics. • Evaluation of the rock-type 3D spatial distributions to ensure conformance with inferred geological patterns. • Computation of absolute permeability ranges based on measured responses to the fractional proportions of pore systems. • Creation of an initial saturation model accounting for the compound saturation fractions related to the pore system components. • Implementation of the concepts in a novel geomodeling workflow.Statistical analyses of almost a thousand pore throat radius distributions and capillary pressure responses reveal a remarkably consistent set of micro-textural associations. Hierarchical clustering analyses define an ordered system of building blocks comprising five dominant pore systems. The macro-porous samples (Ͼ2m pore throat radius -PTR) are distinctly bimodal in two classes (Macro1 and Macro2), while the micro-porous samples have typically unimodal PTR and form three clusters: Micro1 (2 -0.2m), Micro2 (0.2 -0.02m) and Micro3 (Ͻ0.02m).Each rock element is a variable mixture of the five textural building blocks and the relative proportions are utilized to define the rock classification. Spatial continuity and anisotropy are shaped by geological trend vectors interpreted from collocated lithological and depositional texture distributions. This approach meets a dual objective of accounting for the myriad of geological processes implicit in the rock fabric while also providing a rock classification applicable for reservoir engineering and flow simulation purposes.
Paleozoic clastic sediments, comprising continental to transitional marine depositional environments, form excellent hydrocarbon reservoirs in Saudi Arabia. In order to develop a realistic dynamic model that can be used in reservoir performance prediction, a robust geological model is required. Detailed modeling of sand accumulations, their lateral continuity and vertical stacking patterns is needed to capture reservoir heterogeneity at all wavelengths. To build an understanding of the sandstone 'plumbing' within the reservoirs, the Depositional Related Environment Architecture Modelling (DREAM) workflow is invoked. Initially, the fabric of the medium-to-long dimension gross depositional environments is described in 3D. The distribution resides within the envelope of a sequence stratigraphic structural framework that links the main time-correlative boundaries. This model captures the progradational and retrogradational depositional behaviour and employs a stochastic distribution process to address population uncertainties. With the broad-scale environments defined, a subsequent step involves the distribution of short-to-medium scale sedimentary facies conditioned to the environment model. Lateral probability distribution maps and vertical proportion curves, combined with geological templates, are invoked within each environment to ensure that the facies distributions conform to as many observable and analogue trend constraints as possible. In this paper, the DREAM workflow was applied for two case studies and the results are presented. The output models combine the structural framework based on seismic and sequence stratigraphic interpretation principles with linked environment and facies distributions. Introduction The numerical characterisation of the petrophysical anatomy of a reservoir is a synthesis of many information types and can often be approached in a two-pronged fashion:Compartmentalisation of the reservoir into discrete rock quanta with consistent petrophysical and hydraulic signaturesDevelopment of a predictive model to spatially propagate the quanta within the framework of the depositional architectural configuration consistent with the described quantities at well locations. In terms of rock quanta, classification of the reservoir matrix into discrete components based on correlated petrophysical and hydraulic criteria is a crucial initial step. These quanta are described here as petrophysical rock-types (PRTs). Where secondary alteration processes are not significant, then sedimentary facies (or grouped facies associations) are directly translated to PRTs. Alteration processes may mask the original depositional fabric, and a purely petrophysical-based reservoir rock-type approach may then become the optimum discriminator of rock class.
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