The Kashagan field is a huge carbonate formation located 4.5 km below the bottom of the North Caspian sea. The reservoir is saturated by overpressured light oil, and the development is based on first-contact-miscible gas injection.The reservoir is highly stratified, with a fine sequence of depositional cycles and long-range lateral correlations. Three porosity systems (matrix, karst, and fractures) can be organized in two main environments: a massive, low-permeability, matrix-like inner platform and a highly fractured/karstified rim.The reservoir geology is modeled by means of detailed geological grids consisting of tens of millions of cells, with vertical spacing of 1 m or even less to account for high-order depositional cycles. Geological grid cannot be used to run compositional simulations, and much-coarser grids, in which hundreds of geological layers are lumped in few tens of dynamic layers, are used by reservoir engineers. To minimize coarse-scale errors, an average lateral spacing of 250×250 m is used for both simulation and geological grid; nonetheless, upscaling remains a challenge. Traditional permeability (k*) upscaling methods, including flow-based methods, overestimate Kashagan field/wells production and injection potentials.We implemented a method in which the outcome of the upscaling is effective transmissibility (T*) instead of k*. T* upscaling has been proposed in the past as an alternative to k* upscaling, but it is neither part of commercial workflows nor widely accepted in the reservoir-modeling community. In our T* upscaling, the solution of local flow problems around coarse-cell interfaces is used to compute coarse transmissibility. T* and k* upscaling were compared by simulating both single-phase and gas-injection problems, including platform and rim, using the results of fine-scale simulation as a reference. We considered (1) single-porosity simulations with geological grid populated by only matrix (first medium) and karst+fracture (second medium) properties and (2) dual-porosity/ dual-permeability simulations encompassing both media. Contrary to k* upscaling, T*-based coarse simulations perfectly replicate fine-scale field and well injection/production potentials.Using T* upscaling as a cornerstone for company activities on Kashagan, we can run coarse-scale full-field simulations in a few hours without loss of consistency with the results provided by weeks-long, often unpractical, fine-scale simulations. On the contrary, the inaccuracy of k* upscaling would have required much finer and more computationally-expensive simulation grids together with the implementation of ad hoc multiphase upscaling.
In this work, we address the challenge of modelling a complex, carbonate reservoir, where the fractures network, connected throughout a complex fault framework, represents large part of both the storage and the flow capacity of the system. The asset is a giant, onshore field, developed since the 90's by primary depletion through several horizontal wells, targeting anomalous fluid columns. Different culminations are characterized by specific production drive mechanisms. The objective is to integrate an impressive amount of data into a digital model, suitable to understand fluid flow behavior and support decision. The field is challenging in every geological and dynamic feature. The reservoir complexity ranges from the intricate structural framework (several hundreds of reverse faults), to the puzzling fractures network at different scales, to the unclear role of the low-porosity rock matrix, to the heterogeneous distribution - both laterally and vertically - of fluid properties, related to different combinations of hydrocarbon and acid components. The workflow is based on the adoption of Volume Based Modelling (VBM) to account for seismic faults. Then, large-scale fractures are modelled using a blend of stochastic and deterministic Discrete Fracture Networks (DFNs), while background fractures (BGF) are characterized using a Continuous Fracture Modeling (CFM) formulation. A Dual Porosity - Dual Permeability (DPDK) approach is then implemented for reservoir simulation. The model is finally reconciled with the production data by iterating between geology and simulated dynamic response. The whole modeling and simulation workflow, from static to dynamic model definition, is developed relying on company's top-class computational resources. The DPDK formulation, where DFN is the second medium while the first medium consists of BGF and rock matrix, allows us to simulate the main production mechanism: large-scale discontinuities – DFN – are withdrawal first, and then fluid is recharged by smaller scale features. Besides, the history matching phase, together with accurate production and Pressure-Volume-Temperature (PVT) data analysis, sheds light on the extreme heterogeneity of the field. Petrophysical properties, storage and effective apertures of discontinuities are calibrated according to the production history, and integrated into a comprehensive understanding of the reservoir. Eventually, we reveal how a robust history matched model may be used as a powerful tool to understand the impact of all the involved criticalities on the subsurface fluid behavior and movement in a complex fractured carbonate setting. The challenges addressed in this work provide relevant best practices for carbonate reservoir modelling, in particular highlighting the role of the integration between geology and reservoir engineering to minimize subsurface uncertainties. Furthermore, the PVT model developed in this study proposes new migration scenarios to explain the sour gas distribution. Finally, optimized procedures to tackle numerical criticalities using advanced reservoir simulators are disclosed.
Since field discovery, several studies have been performed in order to estimate the reservoir characteristics. In fact data collection has allowed a better understanding of this complex carbonate reservoir, although uncertainties still remain. The first step of production ramp-up will achieve 180,000 stb/d, actually constrained by the gas handling capacity. The production will be delivered by wells located in the D and A islands, whose potential exceeds this production target. Platform Interior wells performance has been defined through a Reservoir-Rock-Type petro-physical characterization matching well test data while Rim wells, characterized by outstanding performances, have been modeled trying to represent the very complex framework constituted by rock-matrix, karst features and fractures. The second ramp-up at 370,000 stb/d will be achieved by the expansion of the gas handling capacity through the start of gas injection applied to the Platform Interior. This phase will rely on the conversion of four D island producers into injectors: their injectivity will be affected by the maximum gas injection pressure, constrained by the cap-rock integrity and the reservoir pressure draw-down achieved during the initial pre-depletion. The gas injection effectiveness will be affected by Platform Interior heterogeneity and by the possible presence of a fracture network. Next development steps will be influenced by the Rim connectivity, actually not well understood.
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