Miscible Gas Injection Issues in a Thick Carbonate Volatile Oil Reservoir
Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Cited by 3 publications
References 0 publications
The Kashagan field is a huge carbonate formation located 4.5 km below the North Capian sea bottom. The reservoir is saturated by over pressured 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, matrixlike inner platform and a highly fractured/karstified rim. The reservoir geology is modelled by means of massive geological grids consisting of tens of millions of cells, with vertical spacing of one meter or even less to account for high order depositional cycles. Fine scale geological grid cannot be used to run compositional simulations and much coarser grids, where hundreds of geological layers are lumped in few tens of dynamic layers, are used by reservoir engineers. To minimize errors due to the coarse scale, an average lateral spacing of 250 m × 250 m is used for both simulation and geological grid, but 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 methodology where the outcome of the upscaling are effective transmissibility (T*) instead than k*. T* upscaling has been proposed in the past as an alternative to k* upscaling, but it is neither part of commercial work-flows 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 reference. We considered single porosity simulations with geological grid populated by only matrix (first medium) and karst+fracture (second medium) properties and dual porosity/dual permeability simulations encompassing both media. Contrary to k* upscaling, T* based coarse simulations perfectly replicate fine scale field and wells injection/production potentials. Using T* upscaling as cornerstone for Company activities on Kashagan, we can run coarse scale full field simulations in 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 computationally expensive simulation grids together with the implementation of ad-hoc multi-phase upscaling.
The Kashagan field is a huge carbonate formation located 4.5 km below the North Capian sea bottom. The reservoir is saturated by over pressured 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, matrixlike inner platform and a highly fractured/karstified rim. The reservoir geology is modelled by means of massive geological grids consisting of tens of millions of cells, with vertical spacing of one meter or even less to account for high order depositional cycles. Fine scale geological grid cannot be used to run compositional simulations and much coarser grids, where hundreds of geological layers are lumped in few tens of dynamic layers, are used by reservoir engineers. To minimize errors due to the coarse scale, an average lateral spacing of 250 m × 250 m is used for both simulation and geological grid, but 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 methodology where the outcome of the upscaling are effective transmissibility (T*) instead than k*. T* upscaling has been proposed in the past as an alternative to k* upscaling, but it is neither part of commercial work-flows 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 reference. We considered single porosity simulations with geological grid populated by only matrix (first medium) and karst+fracture (second medium) properties and dual porosity/dual permeability simulations encompassing both media. Contrary to k* upscaling, T* based coarse simulations perfectly replicate fine scale field and wells injection/production potentials. Using T* upscaling as cornerstone for Company activities on Kashagan, we can run coarse scale full field simulations in 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 computationally expensive simulation grids together with the implementation of ad-hoc multi-phase upscaling.
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.
A large proportion of world's oil reserves resides in naturally fractured reservoirs. Implementing IOR and EOR processes in these reservoirs is a high risk/high reward activity. For instance, on one side water/gas may rapidly break-through along fracture corridors and then jeopardize the IOR/EOR scheme results. On the other side, fracture networks may effectively promote gas-oil gravity drainage or spontaneous imbibition. Accurate and efficient simulation of fractured media is a recognised challenge for reservoir simulators.Various approaches, with different balance between efficiency and accuracy, have been proposed in literature. Up to now the most diffused methods to deal with fractures, have been the adoption of a Dual Porosity/Dual Permeability (DPDK) formulation in a logically structured grid, or the use of unstructured grids.In this work EOR processes in a fractured reservoir were modeled using the Embedded Discrete Fracture Model (Li and Lee, 2008). EDFM represents a practical and efficient compromise between DPDK and unstructured gridding, combining a corner point geometry grid for matrix and an unstructured network for fractures. EDFM was implemented using commercial simulators.The target of the work was sour gas reinjection in a carbonate reservoir characterised by a matrix dominated platform and a fractured rim, with some transition between these two environments. The input of the study was a discrete fracture network, developed using seismic curvature lineaments, and a geological model for the matrix. EDFM and DPDK models were first compared. Then, the new approach was used to investigate fracture impact as a risk for premature gas break-through. The results indicated that the containment of the injection inside the platform, possibly far away from the rim, is an effective way to control the EOR process.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
Contact Info
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Product
Resources
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.
