Naturally Fractured Reservoirs (NFR) contain a significant amount of remaining petroleum reserves and are now considered for Enhanced Oil Recovery (EOR) schemes that involve three-phase flow such as water-alternating-gas (WAG) injection. Reservoir simulation of three phase flow is challenging because a proper set of flow functions, i.e. relative permeability and capillary pressure functions, that describe the underlying physics of fluid displacement is vitally important to obtain reliable production forecasts but associated with high uncertainty. For NFR, another challenge is the upscaling of recovery processes, particularly fracture-matrix transfer during three-phase flow, to the reservoir scale using dual porosity or dual permeability models.In this work we approach a solution to these challenges by analysing three-phase flow during WAG injection at various scales, starting at the pore scale and then move on to an intermediate scale which is comparable to the scale of a single reservoir simulation grid block. At this scale, we represent fractures and matrix using a fine-grid model that employs empirical and pore-network modelling derived three-phase flow functions to study the effect of capillary and gravity forces on fracture-matrix transfer. We also consider different matrix wettabilities and permeabilities, as well as matrix block size distributions. We then perform an upscaling step that is typical for field-scale recovery simulations and use the dual porosity model to represent fracture-matrix transfer processes that were observed at the grid-block scale. This enables us to analyse and improve the accuracy of dual porosity models for three-phase displacement processes inherent to WAG in NFR.We find that different three-phase saturation profiles develop inside matrix blocks, which are strongly dependent on wettability of the matrix. These profiles have a profound impact on recovery during WAG injection. The classical dual porosity model fails to capture these saturation profiles and hence miscalculates recovery during early WAG cycles. We present a double block dual porosity model, i.e. a simple multiple continua model, which better matches the fine grid simulation results.

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A multi-physics framework for compositional and non-isothermal two-phase flow in a porous medium is presented which adapts locally the model complexity depending on the physical state. It is based on a sequential (IMPET) solution scheme. As a second adaptive strategy, the simulation grid can be refined locally. This may lead to a mesh with hanging nodes, which is treated by a multi-point flux approximation (MPFA) for improved flux representation. The two adaptivity concepts are employed to simulate a combined subsurface CO₂ injection and geothermal application in an existing reservoir, the Tensleep formation.

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We integrate discrete fracture network (DFN) with discrete fracture and matrix (DFM) models to increase the efficiency and accuracy of static and dynamic calibration in naturally fractured reservoirs. The DFN method provides a framework for generation and modelling of fractured reservoir models and their conditioning to the observed data. The DFM is more accurate for the dynamic modelling in situations where there is significant flow in the matrix. We discuss a workflow where the two methods are combined jointly in a real fractured reservoir.@en

Carbonate reservoirs contain more than half of the world's remaining petroleum reserves and are increasingly becoming targets for water-alternating-gas (WAG) flooding as secondary or tertiary recovery. Heterogeneity in carbonate reservoirs spans from pore- to reservoir-scale. This is exacerbated by the presence of natural fractures and post-depositional dissolution. Furthermore, carbonate reservoirs tend to have variable wettability that impacts fluid flow which adds to reservoir uncertainty and renders managing WAG floods difficult. In this work, we examine the effect of rock and wettability heterogeneity on recovery profiles in naturally fractured carbonate reservoirs (NFCR). To simulate WAG flooding in NFCR with arbitrary wettability, we use saturation functions derived from a state-of-the-art pore network model to preserve multi-scale heterogeneities at the pore-scale. We study the interplay of capillary, gravity and viscous forces at an intermediate scale, then simulate WAG flooding in the presence of fractures in a heterogeneous carbonate ramp outcrop model. Adding the permeability and wettability heterogeneities impacts ultimate recoveries during water injection cycles by up to 6% and 14% absolute, respectively. Both heterogeneities affect the speed of recovery during gas injection cycles. Depending on its relation to permeability distribution, non-uniform wettability of matrix blocks can have a substantial impact on recovery during water injection cycles while recovery efficiency during the gas injection cycle can be reduced by a factor of 50%. Our work identifies the key factors that must be considered when modelling WAG floods in NFCR. We evaluate the reliability of conventional dual-porosity/dual- permeability numerical simulation approaches for NFCR by comparing results with multi-stage upscaled models through which we capture the fundamental controls on multi-phase flow. Hence, we can offer explanations for possible NFCR responses to WAG flooding and novel ways to improve the predictive ability of field-scale numerical simulation models.@en

Naturally Fractured Reservoirs (NFR) contain a significant amount of remaining petroleum reserves and are now being considered for water-alternating-gas (WAG) flooding as secondary or tertiary recovery. Reservoir simulation of WAG is very challenging even in non-fractured reservoirs because a proper set of saturation functions that describe the underlying physics is vitally important but associated with high uncertainty. For NFRs, another challenge is the upscaling of recovery processes, particularly the fracture-matrix transfer during three-phase flow, to the reservoir scale using dual-porosity or dual-permeability models. In this work, we approach a solution to this challenge by building models at various scales, starting from pore-scale to an intermediate scale then to the reservoir scale. We show how pore-network modelling and fine grid modelling where the fractures and matrix are represented explicitly can be used to increase the accuracy of numerical simulations at the field-scale in order to predict recoveries for NFR during WAG. We study the sensitivity to WAG design parameters as well as the impact of matrix wettability on recovery. We also compare the fine grid model with an equivalent dual-porosity model. Simulation at an intermediate scale showed at least 10% absolute change in recovery due to the choice of the empirical three-phase relative permeability model. In fine grid simulation with physically consistent pore-network derived three-phase relative permeability and capillary pressure, injected water and gas are predicted to displace each other, leaving oil behind, therefore reducing WAG efficiency. For this case, empirical models over-estimate recovery by 25%. Classical dual-porosity model over-estimates recovery during the early WAG cycles, and fails to adequately match recovery of the fine grid simulation. Our multi-scale simulation approach identifies important factors and uncertainties when considering WAG flooding in NFR. It provides a methodology through which WAG recovery can be estimated using available technology while preserving the pore-scale physics for three-phase flow, which are crucial to making reliable forecasts at the reservoir scale.

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Naturally Fractured Reservoirs (NFR) hold a significant fraction of remaining petroleum reserves. Recovery factors from NFR are usually less than in conventional reservoirs due to associated high uncertainty throughout the characterisation and modelling phases. This particularly includes the modelling and upscaling of the fracture domain using Discrete Fracture Networks (DFN). Computer assisted history matching and prediction is becoming increasingly popular as they help finding multiple history-matched models and probabilistic forecasts. Therefore, the associated uncertainty can now be quantified in a limited time frame. However, the results of a history match are known to depend on initial reservoir properties, including fracture permeability and matrix shape factors. Geological uncertainty in these two factors is exacerbated by the DFN upscaling errors. We show how DFN modelling can be used to increase geological prior knowledge and hence produce more geologically consistent models. To highlight DFN upscaling errors, we use a realistic dataset from an onshore fractured reservoir to show how the DFN upscaling error could propagate through to the history matching phase. We compare history matching of three models with different DFN upscaling processes. Results from state-of-the-art assisted history matching and prediction were found to depend on the static properties and particularly the computation of effective fracture permeability during DFN upscaling. This upscaling error alone leads to very different reservoir models, despite the best history matched models being of comparable quality. Hence, this leads to more uncertainty in reservoir production forecast. The identification of DFN upscaling errors is therefore crucial for better uncertainty quantification in reservoir simulation of NFR.@en

Nearly half of the remaining petroleum reserves are contained in naturally fractured reservoirs (NFR). An accurate estimate of the effective fracture permeability tensor is a key to the successful prediction of oil recovery from NFR. Standard workflows nowadays employ discrete fracture network (DFN) modelling and analytical or flow-based methods to upscale fracture permeabilities. However, DFN modelling imposes some important challenges, which can cause great uncertainty in the effective permeability tensor and subsequent recovery prediction: Analytical upscaling methods, which are commonly used due to computational efficiency, are inaccurate for poorly connected fracture networks. Flow-based upscaling methods depend on boundary conditions and are computationally expensive. Defining the optimum grid size for either method is also very difficult. In addition, DFN upscaling is often driven by practical issues such as time constrains and computational limitations, leaving little room to investigate the effects of upscaling methods and grid size. In this paper we compare the performance of three different DFN simulators used in standard industry workflows for computing effective permeability tensors with flow-based and analytical methods. We use a dataset from a fractured formation of an on-shore reservoir in our assessment. Not surprisingly, there is up to three orders of magnitude variation in the effective permeability based on the chosen upscaling method and perceived optimum grid cell size. Quality control with streamline calculations provides no robust assessment of the best upscaling method. We hence introduce a new simulation technique, Discrete Fracture and Matrix (DFM) modelling, which accounts accurately for flow in the fractures and rock matrix as a robust. It is an efficient alternative for computing effective permeability tensors or assessing the accuracy of classical DFN upscaling approaches, which all help reducing uncertainty in recovery prediction.

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Fractured reservoirs contain around 60% of the world's remaining oil reserves. Fracture corridors have been noticed as a major architectural element in outcrops of fractured rock and are known to affect recovery by providing high-permeability flow conduits. Simulations of fractured reservoirs using multi-porosity and multi-permeability models has proven to be challenging, with ever-changing modifications being proposed since the introduction of the dual porosity model in the 1960s. To increase the reliability of reservoir simulation of fractured reservoirs, we propose a new workflow to represent fractured reservoirs by coupling Discrete Fracture and Matrix (DFM) models for fracture corridor properties (which uses finite element and finite volume methods), and the conventional single porosity simulation(which uses finite difference methods). Relative permeabilities of fracture corridors are upscaled over a single grid block size using DFM models based on an unstructured mesh that accommodates fracture corridor patterns and characteristics. The upscaled relative permeabilities are transferred into a single porosity simulation model to reproduce the behaviour of fractured reservoirs without resorting to the transfer functions. Various fracture patterns and apertures were studied to investigate their impact on flow properties. Also, different multiphase upscaling techniques were investigated based on the dominant driving forces and the type of boundary conditions used in the upscaling process. A performance match was done between two models, a fine-mesh DFM model and a simple coarse single porosity model that uses the upscaled relative permeabilities. The models behaved similarly. Recommendations are derived as to how to use appropriate upscaling methods. The new workflow complements and may even have the potential to eliminate the need for classical dual-porosity models.@en