Numerical simulation and optimization study of the complex fracture network in naturally fractured reservoirs

\n Unconventional hydrocarbon resources mostly found in highly stressed, overpressured, and deep formations, where the rock strength and integrity are very high. When fracturing these kinds of rocks, the hydraulic fracturing operation becomes much more challenging and difficult and in some cases reaches to the maximum pumping capacity limits without generating any fracture. This reduces the operational gap to optimally place the hydraulic fractures. Current stimulation methods to reduce the fracture pressures involvement with adverse environmental effects and high costs due to the entailment of water mixed with huge volumes of chemicals. In this study, a new environment friendly approach to reduce the breakdown pressure of the unconventional rock is presented. The new method incorporates the injection of chemical-free fracturing fluid in a series of cycles with a progressive increase of the pressurization rate in each cycle. This study is carried out on different cement blocks with varying petrophysical and mechanical properties to simulate real rock types. The results showed that the new method of cyclic fracturing can reduce the breakdown pressure to 24.6% in ultra-tight rocks, 19% in tight rocks, and 14.8% in medium- to low-permeability rocks. This reduction in breakdown pressure helped to overcome the operational challenges in the field and makes the fracturing operation much greener.

An Environment Friendly Approach to Reduce the Breakdown Pressure of High Strength Unconventional Rocks by Cyclic Hydraulic Fracturing


 Conventional hydrocarbon reservoirs, from an engineering and economic standpoint, are the easiest and most cost-efficient deposits to develop and produce. However, as economic deposits of conventional oil/gas become scarce, hydrocarbon recovered from tight sands and shale deposits will likely fill the void created by diminished conventional oil and gas sources. The purpose of this paper is to review the numerical methods available for simulating multiphase flow in highly fractured reservoirs and present a concise method to implement a fully implicit, two-phase numerical model for simulating multiphase flow, and predicting fluid recovery in highly fractured tight gas and shale gas reservoirs. The paper covers the five primary numerical modeling categories. It addresses the physical and theoretical concepts that support the development of numerical reservoir models and sequentially presents the stages of model development starting with mass balance fundamentals, Darcy’s law and the continuity equations. The paper shows how to develop and reduce the fluid transport equations. It also addresses equation discretization and linearization, model validation and typical model outputs. More advanced topics such as compositional models, reactive transport models, and artificial neural network models are also briefly discussed. The paper concludes with a discussion of field-scale model implementation challenges and constraints. The paper focuses on concisely and clearly presenting fundamental methods available to the novice petroleum engineer with the goal of improving their understanding of the inner workings of commercially available black box reservoir simulators. The paper assumes the reader has a working understanding of flow a porous media, Darcy’s law, and reservoir rock and fluid properties such as porosity, permeability, saturation, formation volume factor, viscosity, and capillary pressure. The paper does not explain these physical concepts neither are the laboratory tests needed to quantify these physical phenomena addressed. However, the paper briefly addresses these concepts in the context of sampling, uncertainty, upscaling, field-scale distribution, and the impact they have on field-scale numerical models.

Multiphase Flow in Highly Fractured Shale Gas Reservoirs: Review of Fundamental Concepts for Numerical Simulation

Projection-based embedded discrete fracture model (pEDFM) is an effective numerical model to handle the flow in fractured reservoirs, with high efficiency and strong generalization of flow models. However, this paper points out that pEDFM fails to handle flow barriers in most cases, and identifies the physical projection configuration of fractures is a key step in pEDFM. This paper presents and proves the equivalence theorem, which explains the geometric nature of physical projection configurations of fractures, that is, the projection configuration of a fracture being physical is equivalent to it being topologically homeomorphic to the fracture, by analyzing the essence of pEDFM. Physical projection configurations of fractures may be rigorously established based on this theorem, allowing pEDFM to obtain physical numerical results for many flow models, particularly those with flow barriers. Furthermore, a natural idea emerges of employing flow barriers to flexibly ‘cut’ the formation to quickly handle the flow problems in the formation with complex geological conditions, and several numerical examples are implemented to test this idea and application of the improved pEDFM. 

A Numerical Modelling Method of Fractured Reservoirs with Embedded Meshes and Topological Fracture Projection Configurations

\n Understanding the role of geological uncertainties on reservoir management decisions requires an ensemble of reservoir models that cover the uncertain space of parameters. However, in most cases, high computation time is needed for the flow simulation step, which can have a negative impact on a suitable assessment of flow behavior. Therefore, one important point is to choose a few scenarios from the ensemble of models while preserving the geological uncertainty range. In this study, we present a statistical solution to select the representative models (RMs) based on a novel scheme of measuring the similarity between 3D flow-unit models. The proposed method includes the integration of multidimensional scaling and cluster analysis (IMC). IMC can be applied to the models before the simulation process to save time and costs. To check the validity of the methodology, numerical simulation and then uncertainty analysis are carried out on the RMs and full set. We create an ensemble of 200 3D flow-unit models through the Latin Hypercube sampling method. The models indicate the geological uncertainty range for properties such as permeability, porosity, and net-to-gross. This method is applied to a synthetic benchmark model named UNISIM-II-D and proves to offer good performance in reducing the number of models so that only 9% of the models in the ensemble (18 selected models from 200 models) can be sufficient for the uncertainty quantification if appropriate similarity measures and clustering methods are used.

Using an Integrated Multidimensional Scaling and Clustering Method to Reduce the Number of Scenarios Based on Flow-Unit Models Under Geological Uncertainties

\n Accurately characterizing hydraulic fracture network and tight oil reservoir properties can lay the foundation for the production forecast and development design. In this work, we proposed a history matching framework for tight oil. We first use the Hough transform method to characterize complex fracture network from microseismic data. Then, we put the fracture network into an embedded discrete fracture model (EDFM) to build a tight oil reservoir simulation model. After that, we further couple whale optimization algorithm (WOA) and EDFM to match the field production data. In this way, we can accurately estimate reservoir properties, including matrix permeability and porosity, as well as fracture permeability. We apply the framework to two-field applications in China. One is fractured vertical well in the Songliao Basin of Daqing oilfield. The other one is multi-stage fractured horizontal well in the Jimsar Sag of the Xinjiang oilfield. Results show that if we do not consider tight oil characteristics, the estimated fracture permeability, matrix permeability, and matrix porosity will underestimate 73%, 20%, and 47%, respectively. Because we apply WOA to history matching for the first time, we compare the performance of WOA with ensemble–smoother with multiple data–assimilation (ES-MDA). When we fit six parameters, ES-MDA performs better than WOA. However, when we fit three parameters, WOA performs better than ES-MDA. In addition, for engineering problem, WOA performs well on both convergence speed and stability. Therefore, WOA is recommended in the future application of history matching.

A History Matching Framework to Characterize Fracture Network and Reservoir Properties in Tight Oil

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A History Matching Framework to Characterize Fracture Network and Reservoir Properties in Tight Oil