A Dual-Grid, Implicit, and Sequentially Coupled Geomechanics-and-Composition Model for Fractured Reservoir Simulation

SPE Journal ◽  
2020 ◽  
Vol 25 (04) ◽  
pp. 2098-2118 ◽  
Author(s):  
Xin Li ◽  
Xiang Li ◽  
Dongxiao Zhang ◽  
Rongze Yu

Summary In the development of fractured reservoirs, geomechanics is crucial because of the stress sensitivity of fractures. However, the complexities of both fracture geometry and fracture mechanics make it challenging to consider geomechanical effects thoroughly and efficiently in reservoir simulations. In this work, we present a coupled geomechanics and multiphase-multicomponent flow model for fractured reservoir simulations. It models the solid deformation using a poroelastic equation, and the solid deformation effects are incorporated into the flow model rigorously. The noticeable features of the proposed model are it uses a pseudocontinuum equivalence method to model the mechanical characteristics of fractures; the coupled geomechanics and flow equations are split and sequentially solved using the fixed-stress splitting strategy, which retains implicitness and exhibits good stability; and it simulates geomechanics and compositional flow, respectively, using a dual-grid system (i.e., the geomechanics grid and the reservoir-flow grid). Because of the separation of the geomechanics part and the flow part, the model is not difficult to implement based on an existing reservoir simulator. We validated the accuracy and stability of this model through several benchmark cases and highlighted the practicability with two large-scale cases. The case studies demonstrate that this model is capable of considering the key effects of geomechanics in fractured-reservoir simulation, including matrix compaction, fracture normal deformation, and shear dilation, as well as hydrocarbon phase behavior. The flexibility, efficiency, and comprehensiveness of this model enable a more realistic geocoupled reservoir simulation.

SPE Journal ◽  
2019 ◽  
Vol 24 (04) ◽  
pp. 1508-1525
Author(s):  
Mengbi Yao ◽  
Haibin Chang ◽  
Xiang Li ◽  
Dongxiao Zhang

Summary Naturally or hydraulically fractured reservoirs usually contain fractures at various scales. Among these fractures, large-scale fractures might strongly affect fluid flow, making them essential for production behavior. Areas with densely populated small-scale fractures might also affect the flow capacity of the region and contribute to production. However, because of limited information, locating each small-scale fracture individually is impossible. The coexistence of different fracture scales also constitutes a great challenge for history matching. In this work, an integrated approach is proposed to inverse model multiscale fractures hierarchically using dynamic production data. In the proposed method, a hybrid of an embedded discrete fracture model (EDFM) and a dual-porosity/dual-permeability (DPDP) model is devised to parameterize multiscale fractures. The large-scale fractures are explicitly modeled by EDFM with Hough-transform-based parameterization to maintain their geometrical details. For the area with densely populated small-scale fractures, a truncated Gaussian field is applied to capture its spatial distribution, and then the DPDP model is used to model this fracture area. After the parameterization, an iterative history-matching method is used to inversely model the flow in a fractured reservoir. Several synthetic cases, including one case with single-scale fractures and three cases with multiscale fractures, are designed to test the performance of the proposed approach.


2009 ◽  
Vol 12 (03) ◽  
pp. 380-389 ◽  
Author(s):  
Juan Ernesto Ladron de Guevara-Torres ◽  
Fernando Rodriguez-de la Garza ◽  
Agustin Galindo-Nava

Summary The gravity-drainage and oil-reinfiltration processes that occur in the gas-cap zone of naturally fractured reservoirs (NFRs) are studied through single porosity refined grid simulations. A stack of initially oil-saturated matrix blocks in the presence of connate water surrounded by gas-saturated fractures is considered; gas is provided at the top of the stack at a constant pressure under gravity-capillary dominated flow conditions. An in-house reservoir simulator, SIMPUMA-FRAC, and two other commercial simulators were used to run the numerical experiments; the three simulators gave basically the same results. Gravity-drainage and oil-reinfiltration rates, along with average fluid saturations, were computed in the stack of matrix blocks through time. Pseudofunctions for oil reinfiltration and gravity drainage were developed and considered in a revised formulation of the dual-porosity flow equations used in the fractured reservoir simulation. The modified dual-porosity equations were implemented in SIMPUMA-FRAC (Galindo-Nava 1998; Galindo-Nava et al. 1998), and solutions were verified with good results against those obtained from the equivalent single porosity refined grid simulations. The same simulations--considering gravity drainage and oil reinfiltration processes--were attempted to run in the two other commercial simulators, in their dual-porosity mode and using available options. Results obtained were different among them and significantly different from those obtained from SIMPUMA-FRAC. Introduction One of the most important aspects in the numerical simulation of fractured reservoirs is the description of the processes that occur during the rock-matrix/fracture fluid exchange and the connection with the fractured network. This description was initially done in a simplified manner and therefore incomplete (Gilman and Kazemi 1988; Saidi and Sakthikumar 1993). Experiments and theoretical and numerical studies (Saidi and Sakthikumar 1993; Horie et al. 1998; Tan and Firoozabadi 1990; Coats 1989) have allowed to understand that there are mechanisms and processes, such as oil reinfiltritation or oil imbibition and capillary continuity between matrix blocks, that were not taken into account with sufficient detail in the original dual-porosity formulations to model them properly and that modify significantly the oil-production forecast and the ultimate recovery in an NFR. The main idea of this paper is to study in further detail the oil reinfiltration process that occurs in the gas invaded zone (gas cap zone) in an NFR and to evaluate its modeling to implement it in a dual-porosity numerical simulator.


2002 ◽  
Vol 5 (02) ◽  
pp. 154-162 ◽  
Author(s):  
S. Sarda ◽  
L. Jeannin ◽  
R. Basquet ◽  
B. Bourbiaux

Summary Advanced characterization methodology and software are now able to provide realistic pictures of fracture networks. However, these pictures must be validated against dynamic data like flowmeter, well-test, interference-test, or production data and calibrated in terms of hydraulic properties. This calibration and validation step is based on the simulation of those dynamic tests. What has to be overcome is the challenge of both accurately representing large and complex fracture networks and simulating matrix/ fracture exchanges with a minimum number of gridblocks. This paper presents an efficient, patented solution to tackle this problem. First, a method derived from the well-known dual-porosity concept is presented. The approach consists of developing an optimized, explicit representation of the fractured medium and specific treatments of matrix/fracture exchanges and matrix/matrix flows. In this approach, matrix blocks of different volumes and shapes are associated with each fracture cell depending on the local geometry of the surrounding fractures. The matrix-block geometry is determined with a rapid image-processing algorithm. The great advantage of this approach is that it can simulate local matrix/fracture exchanges on large fractured media in a much faster and more appropriate way. Indeed, the simulation can be carried out with a much smaller number of cells compared to a fully explicit discretization of both matrix and fracture media. The proposed approach presents other advantages owing to its great flexibility. Indeed, it accurately handles the cases in which flows are not controlled by fractures alone; either the fracture network may be not hydraulically connected from one well to another, or the matrix may have a high permeability in some places. Finally, well-test cases demonstrate the reliability of the method and its range of application. Introduction In recent years, numerous research programs have been focusing on the topic of fractured reservoirs. Major advances were made, and oil companies now benefit from efficient methodologies, tools, and software for fractured reservoir studies. Nowadays, a study of a fractured reservoir, from fracture detection to full-field simulation, includes the following main steps: geological fracture characterization, hydraulic characterization of fractures, upscaling of fracture properties, and fractured reservoir simulation. Research on fractured reservoir simulation has a long history. In the early 1960s, Barenblatt and Zheltov1 first introduced the dual-porosity concept, followed by Warren and Root,2 who proposed a simplified representation of fracture networks to be used in dual-porosity simulators. Based on this concept, reservoir simulators3 are now able to correctly reproduce the main driving mechanisms occurring in fractured reservoirs, such as water imbibition, gas/oil and water/oil gravity drainage, molecular diffusion, and convection in fractures. Even single-medium simulators can perform fractured reservoir simulation when adequate pseudocapillary pressure curves and pseudorelative permeability curves can be input. Indeed, except for particular cases such as thermal recovery processes, full-field simulation of fractured reservoirs is no longer a problem. Geological characterization of fractures progressed considerably in the 1990s. The challenge was to analyze and integrate all the available fracture data to provide a reliable description of the fracture network both at field scale and at local reservoir cell scale. Tools have been developed for merging seismic, borehole imaging, lithological, and outcrop data together with the help of geological and geomechanical rules.3 These tools benefited from the progress of seismic acquisition and borehole imaging. Indeed, accurate seismic data lead to reliable models of large-scale fracture networks, and borehole imaging gives the actual fracture description along the wells, which enables a reliable statistical determination of fracture attributes. Finally, these tools provide realistic pictures of fracture networks. They are applied successfully in numerous fractured-reservoir studies. The upscaling of fracture properties is the problem of translating the geological description of fracture networks into reservoir simulation parameters. Two approaches are possible. In the first one, the fractured reservoir is considered as a very heterogeneous matrix reservoir; therefore, one applies the classical techniques available for heterogeneous single-medium upscaling. The second approach is based on the dual-porosity concept and consists of upscaling the matrix and the fracture separately. Based on this second approach, methodologies and software were developed in the 1990s to calculate equivalent fracture parameters with respect to the dual-porosity concept (i.e., a fracture-permeability tensor with main flow directions and anisotropy and a shape factor that controls the matrix/fracture exchange kinetics3–5). For a given reservoir grid cell, the upscaling procedures consist of generating the corresponding 3D discrete fracture network and computing the equivalent parameters from this network. In particular, the permeability tensor is computed from the results of steady-state flow simulations in the discrete fracture network alone (without the matrix).


2020 ◽  
Vol 60 (1) ◽  
pp. 124
Author(s):  
Shahdad Ghassemzadeh ◽  
Maria Gonzalez Perdomo ◽  
Manouchehr Haghighi ◽  
Ehsan Abbasnejad

Reservoir simulation plays a vital role as a diagnostics tool to better understand and predict a reservoir’s behaviour. The primary purpose of running a reservoir simulation is to replicate reservoir performance under different production conditions; therefore, the development of a reliable and fast dynamic reservoir model is a priority for the industry. In each simulation, the reservoir is divided into millions of cells, with fluid and rock attributes assigned to each cell. Based on these attributes, flow equations are solved through numerical methods, resulting in an excessively long processing time. Given the recent progress in machine learning methods, this study aimed to further investigate the possibility of using deep learning in reservoir simulations. Throughout this paper, we used deep learning to build a data-driven simulator for both 1D oil and 2D gas reservoirs. In this approach, instead of solving fluid flow equations directly, a data-driven model instantly predicts the reservoir pressure using the same input data of a numerical simulator. Datasets were generated using a physics-based simulator. It was found that for the training and validation sets, the mean absolute percentage error (MAPE) was less than 15.1% and the correlation coefficient, R2, was more than 0.84 for the 1D oil reservoirs, while for the 2D gas reservoir MAPE < 0.84% and R2 ≈1. Furthermore, the sensitivity analysis results confirmed that the proposed approach has promising potential (MAPE < 5%, R2 > 0.9). The results agreed that the deep learning based, data-driven model is reasonably accurate and trustworthy when compared with physics-derived models.


2021 ◽  
Vol 36 (4) ◽  
pp. 151-162
Author(s):  
Yousef Shiri ◽  
Alireza Shiri

Fractured reservoirs have always been of interest to many researchers because of their complexities and importance in the oil industry. The purpose of the current study is to model the fractured reservoir based on geomechanical restoration. Our target is the Arab Formation reservoir which is composed of seven limestone and dolomite layers, separated by thin anhydrite evaporate rock. First of all, in addition to the intensity, the dip, and the azimuth of the fractures, the magnitude and the direction of the stresses are determined using wireline data e.g. photoelectric absorption factor (PEF), sonic density, neutron porosity, a dipole shear sonic imager (DSI), a formation micro imager (FMI), and a modular formation dynamics tester (MDT). Then, the seismic data are interpreted and the appropriate seismic attributes are selected. One of our extracted attributes was the ant tracking attribute which is used for identifying large-scale fractures. Using this data, fractures and faults can be identified in the areas away from wells in different scales. Subsequently, the initial model of the reservoir is reconstructed. After that, the stress field and the distribution of fractures are obtained using the relationship between the stresses, the strains, and the elastic properties of the existing rocks. The model is finely approved using the azimuth and the intensity of fractures in the test well. Our findings showed that the discrete fracture network (DFN) model using geomechanical restoration was positively correlated with real reservoir conditions. Also, the spatial distribution of fractures was improved in comparison to the deterministic-stochastic DFN.


Author(s):  
K. Zobeidi ◽  
M. Mohammad-Shafie ◽  
M. Ganjeh-Ghazvini

AbstractA comprehensive reservoir simulation study was performed on an oil field that had a wide fracture network and could be considered a typical example of highly fractured reservoirs in Iran. This field is located in southwest of Iran in Zagros sedimentary basin among several neighborhood fields with relatively considerable fractured networks. In this reservoir, the pressure drops below the saturation pressure and causes the formation of a secondary gas cap. This can help to better assess the gravity drainage phenomenon. We decided to investigate and track the effect of gravity drainage mechanism on the recovery factor of oil production in this field. In this study, after/before the implementation of gas injection scenarios with different discharges, the contribution of gravity drainage mechanism to the recovery factor was found more than 50%. Considering that a relatively large number of studies have been conducted on this field simultaneously with the growth of information from different aspects and this study is the last and most comprehensive study and also the results are extracted from real field data using existing reservoir simulators, it is of special importance and can be used by researchers.


1992 ◽  
Vol 114 (4) ◽  
pp. 847-857 ◽  
Author(s):  
J. H. Wagner ◽  
B. V. Johnson ◽  
R. A. Graziani ◽  
F. C. Yeh

Experiments were conducted to determine the effects of buoyancy and Coriolis forces on heat transfer in turbine blade internal coolant passages. The experiments were conducted with a large-scale, multipass, heat transfer model with both radially inward and outward flow. Trip strips on the leading and trailing surfaces of the radial coolant passages were used to produce the rough walls. An analysis of the governing flow equations showed that four parameters influence the heat transfer in rotating passages: coolant-to-wall temperature ratio, Rossby number, Reynolds number, and radius-to-passage hydraulic diameter ratio. The first three of these four parameters were varied over ranges that are typical of advanced gas turbine engine operating conditions. Results were correlated and compared to previous results from stationary and rotating similar models with trip strips. The heat transfer coefficients on surfaces, where the heat transfer increased with rotation and buoyancy, varied by as much as a factor of four. Maximum values of the heat transfer coefficients with high rotation were only slightly above the highest levels obtained with the smooth wall model. The heat transfer coefficients on surfaces where the heat transfer decreased with rotation, varied by as much as a factor of three due to rotation and buoyancy. It was concluded that both Coriolis and buoyancy effects must be considered in turbine blade cooling designs with trip strips and that the effects of rotation were markedly different depending upon the flow direction.


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