Naturally Fractured Reservoirs (NFR) are very heterogeneous media containing highly permeable fractures in a poorly permeable rock matrix. Explicit simulations of such reservoirs are complex and computationally time consuming. Alternatively for full-field simulation, dual-medium models are commonly used (dual-porosity, dual-permeability) where fractures are represented as a continuous medium in communication with the rock matrix. Required effective dynamic properties at the coarse continuous scale should produce the same flow simulation results than Discrete Fracture Network (DFN) models with their small-scale properties, using explicit simulation (as reference). Many calculation methods with different accuracy and computational efficiency have been proposed for the estimation of the anisotropic effective permeability tensor of fracture networks. These methods rely on different conceptual models, which are simplified representations of actual complex and partially unknown fracture systems. They are using either a global deterministic DFN, or local representations of DFNs defined by their statistical properties. Analytical methods rely on connectivity assumptions, seldom met in practice. Numerical methods rely on flow simulations, and are supposed to be more accurate but computationally demanding. The development of new simulators using Discrete Fracture and Matrix (DFM) models, where all fractures are represented explicitly as well as the matrix, offers the opportunity to benchmark the accuracy of the different effective permeability calculation methods. Simulations based on effective properties are compared with DFM model simulations, considered as a reference solution.In a first part, 2D Cartesian fracture networks are simulated explicitly with Eclipse. These reference simulations are compared with simulations based on effective properties. In this paper we consider the following effective permeability calculation techniques: an analytical method (the Oda's technique); two flow-based numerical methods with different boundary conditions (impermeable boundaries and linearly varying pressure); and a numerical method using a periodic DFN defined locally, that does not depend on boundary conditions (Image Based Periodic Object Simulation -IBPOSimplemented in GoFraK, a plugin of Gocad). In a second part, a simulation was performed on a much more realistic fracture network with CSMP++, simulation software using DFM models. This simulation is compared with simulations using effective properties calculated with the Oda's method and the two flow-based numerical methods.The first observation concerns the large variability of results, which stresses the large uncertainty produced by the various methods. When compared to the reference, the most accurate effective permeability calculation methods tested in this paper are the numerical methods, using no-flow boundary condition and the IBPOS technique. These results show the importance of the fracture network connectivity for the calculation of the effective permeability, and ...

This paper discusses the design and implementation of a Single Well Chemical Tracer Test (SWCTT) to evaluate the efficacy of a lab-optimized surfactant-polymer formulation for the Raudhatain Lower Burgan (RALB) reservoir in North Kuwait. A SWCTT was designed upon completing extensive lab and simulation work as discussed in a previous publication (Al-Murayri et al. 2017 and Al-Murayri et al. 2018). SWCTT design work was aimed at confirming the optimal injection/production sequence determined at core flood scale in terms of minimal volumes, rates and duration. The main uncertainties were assessed using numerous sensitivity scenarios. Afterwards, the SWCTT was implemented in the field and the results were carefully analyzed and compared to previously obtained lab andsimulation results. The main objective of this SWCTT was to validate the efficacy of polymer and surfactant solutions in terms of residual oil saturation reduction and injectivity. This invovles comparing residual oil saturation estimates before and after chemical flooding while monitoring injection rates and corresponding wellhead pressures. The SWCTT injection sequence included the following steps:Initial water-flooding, followed by tracer injection, soaking and production to measure oil saturation post water flooding.Pre-flush followed by a main-slug (with 5,000 ppm of surfactant and 500 ppm of polymer) and a post-flush (with only polymer).Sea-water push, followed by tracer injection, soaking and production to measure oil saturation post chemical flooding. Simulation work prior to the execution of the SWCTT test showed encouraging oil desaturation results post chemical flooding within a distance of 10 ft from the well. However, upon analyzing the pilot results, it was realized that there is a gap between the actual SWCTT results and previously obtained lab andsimulation results. This paper sheds light on the design and implementation of the above-mentioned SWCTTwith emphasis on the potential reasons for the realized gap between actual field data and lab/simulation results. The insights from this study are expected to assist in further optimization of surfactant-polymer flooding to economically increase oil recovery from relatively mature reservoirs.

EOR surfactants are usually formulated at the initial reservoir temperature. Is this a correct approach? Field data from three Single-Well Chemical Tracer pilots in North Africa are used to answer this question. The objectives are, first, to provide a realistic image of the temperature variations inside the water-flooded reservoir; second, to demonstrate the impact of such temperature variations on the surfactant performances; and last, to introduce a new methodology for estimating the target temperature window for surfactant formulations. During pre-SWCTT pilot tests, water injection, shut-in and back-production were performed. The bottom-hole temperature was monitored to evaluate the reservoir temperature changes (initially at 120°C) and to calibrate a thermal model. The thermal parameters were applied to the reservoir model to simulate 30 years of water injection (with its surface temperature varying between 20°C and 60°C) and to obtain a full picture of the temperature variations inside the reservoir. Multi-well surfactant injection was modelled assuming that the surfactant is only efficient within ±10°C around the design temperature. The impact of this assumption on the additional oil recovery was analyzed for several scenarios. The rock thermal transmissivity was found to be the key parameter for properly reproducing the observed data gathered in the North African pre-SWCTT tests. The measured temperature during the back-production phase demonstrated the accuracy of the thermal model parametrization. It proved that the heat exchange between the reservoir and the injected fluid is considerably less than what industry expects: the injected water temperature inside the reservoir remains far below the initial reservoir temperature even after 11 days of shut-in. When simulating various historical bottom-hole injection temperatures and pre-flush durations, the thermal model showed an average cooling radius of 275m, larger than the industry recommended well-spacing for the EOR 5-spot patterns. This was mainly due to the significant temperature difference between the historical injected water and the initial reservoir temperature. Several simulations were performed for 3 representative bottom-hole injection temperatures of 20°C, 40°C and 60°C, varying the surfactant design temperature range between the injection temperature and the initial reservoir temperature. The results showed that regardless of the injection temperature, the simulated additional oil recovery is highest when the design temperature range is close to the injection bottom-hole temperature. This is an important subject since in the EOR industry, the surfactants are usually formulated at the initial reservoir temperature and thus, the impact of the reservoir cooling on the surfactant efficiency is seldom considered. In a water flooded reservoir, the injected chemicals are unlikely to encounter the initial reservoir temperature. This results in a dramatic loss of surfactant performance especially when there is a considerable difference between the initial reservoir and the injected fluid temperatures.

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