A Fractal Discrete Fracture Network Model for History Matching of Naturally Fractured Reservoirs

Zhang, Liming; Cui, Chenyu; Ma, Xiaopeng; Sun, Zheng; LIU, FAN; Zhang, Kai

doi:10.1142/s0218348x19400085

Cited by 42 publications

(10 citation statements)

References 37 publications

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“…Natural fractures [41] or hydraulic fracturing fractures [42] in the reservoir can often be obtained from history matching or seismic inversion [43]. In this work, an assumptive model sized 200 m × 200 m is used as the original fracture network and the parameters of fractures are referenced from Ref [35].…”

Section: Computational Modelmentioning

confidence: 99%

Well-Placement Optimization in an Enhanced Geothermal System Based on the Fracture Continuum Method and 0-1 Programming

Zhang¹,

Deng²,

Zhang³

et al. 2019

Energies

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The well-placement of an enhanced geothermal system (EGS) is significant to its performance and economic viability because of the fractures in the thermal reservoir and the expensive cost of well-drilling. In this work, a numerical simulation and genetic algorithm are combined to search for the optimization of the well-placement for an EGS, considering the uneven distribution of fractures. The fracture continuum method is used to simplify the seepage in the fractured reservoir to reduce the computational expense of a numerical simulation. In order to reduce the potential well-placements, the well-placement optimization problem is regarded as a 0-1 programming problem. A 2-D assumptive thermal reservoir model is used to verify the validity of the optimization method. The results indicate that the well-placement optimization proposed in this paper can improve the performance of an EGS.

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Section: Computational Modelmentioning

confidence: 99%

Well-Placement Optimization in an Enhanced Geothermal System Based on the Fracture Continuum Method and 0-1 Programming

Zhang¹,

Deng²,

Zhang³

et al. 2019

Energies

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“…where g(⋅) represents the subsurface flow simulation in fractured rock and the simulation model consists of a set of mass conservation equations and boundary conditions. In this paper, the solution of the simulation can be achieved by MATLAB Reservoir Simulation Toolbox (MRST) (Lie 2015;Zhang et al 2019).…”

Section: Bayesian Formulationmentioning

confidence: 99%

Calibrate complex fracture model for subsurface flow based on Bayesian formulation

Zhang

et al. 2019

Pet. Sci.

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In practical development of unconventional reservoirs, fracture networks are a highly conductive transport media for subsurface fluid flow. Therefore, it is crucial to clearly determine the fracture properties used in production forecast. However, it is different to calibrate the properties of fracture networks because it is an inverse problem with multi-patterns and highcomplexity of fracture distribution and inherent defect of multiplicity of solution. In this paper, in order to solve the problem, the complex fracture model is divided into two sub-systems, namely "Pattern A" and "Pattern B." In addition, the generation method is grouped into two categories. Firstly, we construct each sub-system based on the probability density function of the fracture properties. Secondly, we recombine the sub-systems into an integral complex fracture system. Based on the generation mechanism, the estimation of the complex fracture from dynamic performance and observation data can be solved as an inverse problem. In this study, the Bayesian formulation is used to quantify the uncertainty of fracture properties. To minimize observation data misfit immediately as it occurs, we optimize the updated properties by a simultaneous perturbation stochastic algorithm which requires only two measurements of the loss function. In numerical experiments, we firstly visualize that small-scale fractures significantly contribute to the flow simulation. Then, we demonstrate the suitability and effectiveness of the Bayesian formulation for calibrating the complex fracture model in the following simulation.

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“…To solve the difficulty of experiments on tight rocks, the hydraulic conductivity can be calculated based on digital rocks that are constructed from real rocks [30][31][32][33]. Using the reservoir static properties obtained from digital rocks, automated fitting methods can predict the dynamic reservoir properties [34,35]. Although flow properties have been widely evaluated, thermal properties based on digital rocks are seldom studied [36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Thermal Conduction Simulation Based on Reconstructed Digital Rocks with Respect to Fractures

et al. 2019

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Effective thermal conductivity (ETC), as a necessary parameter in the thermal properties of rock, is affected by the pore structure and the thermal conduction conditions. To evaluate the effect of fractures and saturated fluids on sandstone’s thermal conductivity, we simulated thermal conduction along three orthogonal (X, Y, and Z) directions under air- and water-saturated conditions on reconstructed digital rocks with different fractures. The results show that the temperature distribution is separated by the fracture. The significant difference between the thermal conductivities of solid and fluid is the primary factor influencing the temperature distribution, and the thermal conduction mainly depends on the solid phase. A nonlinear reduction of ETC is observed with increasing fracture length and angle. Only when the values of the fracture length and angle are large, a negative effect of fracture aperture on the ETC is apparent. Based on the partial least squares (PLS) regression method, the fluid thermal conductivity shows the greatest positive influence on the ETC value. The fracture length and angle are two other factors significantly influencing the ETC, while the impact of fracture aperture may be ignored. We obtained a predictive equation of ETC which considers the related parameters of digital rocks, including the fracture length, fracture aperture, angle between the fracture and the heat flux direction, porosity, and the thermal conductivity of saturated fluid.

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A Fractal Discrete Fracture Network Model for History Matching of Naturally Fractured Reservoirs

Cited by 42 publications

References 37 publications

Well-Placement Optimization in an Enhanced Geothermal System Based on the Fracture Continuum Method and 0-1 Programming

Well-Placement Optimization in an Enhanced Geothermal System Based on the Fracture Continuum Method and 0-1 Programming

Calibrate complex fracture model for subsurface flow based on Bayesian formulation

Thermal Conduction Simulation Based on Reconstructed Digital Rocks with Respect to Fractures

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