Summary Hydraulic fracturing is a dominant technology in unconventional resources development. Recent advances in fracture-diagnostic tools and fracture-propagation models make it necessary to model fractures with complex geometries in reservoir-simulation studies. In this paper, we present an efficient method to model fractures with complex geometries with reservoir simulators. Through nonneighboring connections (NNCs), an embedded discrete-fracture modeling (EDFM) formulation is applied to reservoir simulators to properly model fractures with complex geometries such as fracture networks and nonplanar hydraulic fractures. We demonstrate the accuracy of the approach by performing a series of case studies with two commercial reservoir simulators and comparing the results with local-grid-refinement (LGR) models and a semianalytical solution. The limitations of the model are also discussed. In addition, the results show its computational efficiency as the complexity of fractures increases. We also present two numerical case studies to demonstrate the applicability of our method in naturally fractured reservoirs. The nonintrusive application of the EDFM allows insertion of the discrete fractures into the computational domain and the use of original functionalities of the simulators without having access to the source code of the simulators. It may be easily integrated into existing frameworks for unconventional reservoirs to perform sensitivity analysis, history matching, and production forecasting.

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The Embedded Discrete Fracture Model (EDFM) is a promising new method used to explicitly model high-level inhomogeneities such as conductive faults or fractures. The EDFM formulation can be used to model naturally fractured reservoirs (NFR) and unconventional reservoirs through also in a triple porosity model composed of hydraulic fractures, natural fractures, and matrix domains for simulation of unconventional reservoirs. Using non-neighboring connections, the EDFM approach was implemented in an IMPEC compositional reservoir simulator (UTCOMP). A preprocessing code was developed to convert the discrete natural/hydraulic fractures into a data set to be used by the simulator, which allows more realistic representation of fractured reservoirs. Compared to previous studies, the developed preprocessing code introduces additional features to better represent structural properties of matrix and fractures, such as implementation of Odas permeability tensor formulation for modeling permeability anisotropy, partial penetration of fractures into the grid, partial intersection of fractures, and calculation of equivalent properties using the definition of density of fractures for conventional dual porosity/dual permeability simulation. The preprocessing code is also capable of handling the data generated by commercial geological modeling softwares. Both the updated UTCOMP and preprocessing code were validated against in-house fully implicit simulator (GPAS) and fine-grid models using commercially available reservoir simulators. Simulation run time was improved by applying a porosity cut-off in the fracture cells, upon which constant fracture conductivity was assumed. Validation case studies include multi-fractured wells producing through depletion and a 2D quarter five-spot production scheme (water and miscible gas injection) in NFR. Moreover, the updated UTCOMP was further used for application case studies including 3D models and considering miscible gas injection for different, geological scenarios: horizontal, dipping, and anticline fractured reservoirs. Both continuous gas and water alternating gas (WAG) injection were evaluated. The validation studies show good agreement between EDFM and fine-grid models. Results show that the effect of fractures on hydrocarbon production depends on fracture network connectivity, which can be properly modeled using the preprocessing code integrates with a numerical simulator capable of handling non-neighboring connections.

Summary Foam has been successfully used in the oil industry for conformance and mobility control in gas-injection processes. The efficiency of a foam-injection project must be assessed by means of numerical models. Although there are several foam-flow models in the literature, the prediction of foam behavior is an important issue that needs further investigation. In this paper, we estimate foam parameters and investigate foam behavior for a given range of water saturation by use of two local equilibrium foam models: the population balance assuming local equilibrium (LE) model and the University of Texas (UT) model. Our method uses an optimization algorithm to estimate foam-model parameters by matching the measured pressure gradient from steady-state foam-coreflood experiments. We calculate the effective foam viscosity and the water fractional flow by use of experimental data, and we then compare laboratory data against results obtained with the matched foam models to verify the foam parameters. Other variables, such as the foam texture and foam relative permeability, are used to further investigate the behavior of the foam during each experiment. We propose an improvement to the UT model that provides a better match in the high-quality regime by assuming resistance factor and critical water saturation as a linear function of the pressure gradient. Results show that the parameter-estimation method coupled with an optimization algorithm successfully matches the experimental data by use of both foam models. In the LE model, we observe different values of the foam effective viscosity for each pressure gradient caused by variations of foam texture and the shear-thinning viscosity effect. The UT model presents a constant effective viscosity for each pressure gradient; we propose the use of resistance factor and critical water saturation as a linear function of the pressure gradient to improve the match in the high-quality regime, when applicable.

This paper was presented as part of the student paper contest associatedwith the Annual Technical Conference and Exhibition. Abstract The definition and optimization of production strategies involve manyvariables and a great number of possible scenarios and the problem complexity.Quality maps are important decision making tools capable of representingvarious reservoir properties, which influence field production and, therefore, are important for the process of defining and optimizing production strategies.These maps integrate geological and fluid variables, allowing for theidentification of regions of greater or lower production potential, whether oneis analyzing reservoirs in the development phase or mature fields. These mapswere used by several authors yielding improvements in the reservoirproductivity. The most commonly used method to generate a quality map usesreservoir numerical simulations considering a unique production well, operatingfor enough time to represent the oil potential of each position. The wellposition is changed in each simulation run in order to cover all the reservoirgrid area. This could require long running times and high computational effortdepending on the problem features, thus rendering the process unfeasible. Theobjective of this work is to speedup the process and to develop a reliablemethodology. Therefore, several generation methods were developed in thepresent work and the best technique was selected after a thorough analysis. Thekriging interpolation method was used for the skipped points in all cases.Three reservoir models are shown, two theoretical models, with homogeneous andheterogeneous properties, and one model derived from a real oil field. Theresults have shown that the method proposed in the present work, with fixedproducers and injectors, is a reliable technique and yield good results, beingalso much faster than the methods presented in the literature.