History matching and uncertainty quantification of discrete fracture network models in fractured reservoirs

Nejadi, Siavash; Trivedi, Japan; Leung, Juliana Y.

doi:10.1016/j.petrol.2017.01.048

Cited by 36 publications

(9 citation statements)

References 26 publications

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“…The DFM approach is often preferred in detailed geological studies due to its accuracy (Berre et al., 2019; Flemisch et al., 2018; Moinfar et al., 2011; Wong et al., 2020). DFM models typically require a high meshing accuracy to resolve the fracture networks' complex geometry, thereby drastically increasing the computational complexity and rendering them unusable for uncertainty quantification purposes (Jung et al., 2013; Nejadi et al., 2017; Spooner et al., 2021). More recently, the DFM approach in reservoir simulation has been enhanced for practical applications by fully coupling geomechanics (Garipov et al., 2016) and fracture propagation (Gallyamov et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

An Advanced Discrete Fracture Methodology for Fast, Robust, and Accurate Simulation of Energy Production From Complex Fracture Networks

Hoop

Voskov

Bertotti

et al. 2022

Water Resources Research

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Fracture networks are abundant in subsurface applications (e.g., geothermal energy production, CO2 sequestration). Fractured reservoirs often have a very complex structure, making modeling flow and transport in such networks slow and unstable. Consequently, this limits our ability to perform uncertainty quantification and increases development costs and environmental risks. This study provides an advanced methodology for simulation based on Discrete Fracture Model approach. The preprocessing framework results in a fully conformal, uniformly distributed grid for realistic 2D fracture networks at a required level of precision. The simplified geometry and topology of the resulting network are compared with input (i.e., unchanged) data to evaluate the preprocessing influence. The resulting mesh‐related parameters, such as volume distributions and orthogonality of control volume connections, are analyzed. Furthermore, changes in fluid‐flow response related to preprocessing are evaluated using a high‐enthalpy two‐phase flow geothermal simulator. The simplified topology directly improves meshing results and, consequently, the accuracy and efficiency of numerical simulation. The main novelty of this work is the introduction of an automatic preprocessing framework allowing us to simplify the fracture network down to required level of complexity and addition of a fracture aperture correction capable of handling heterogeneous aperture distributions, low connectivity fracture networks, and sealing fractures. The graph‐based framework is fully open‐source and explicitly resolves small‐angle intersections within the fracture network. A rigorous analysis of changes in the static and dynamic impact of the preprocessing algorithm demonstrates that explicit fracture representation can be computationally efficient, enabling their use in large‐scale uncertainty quantification studies.

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Section: Introductionmentioning

confidence: 99%

An Advanced Discrete Fracture Methodology for Fast, Robust, and Accurate Simulation of Energy Production From Complex Fracture Networks

Hoop

Voskov

Bertotti

et al. 2022

Water Resources Research

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“…Based on fractal analysis method, seepage characteristics of full-scale fracture networks can be calculated by Eqs. (11)- (14). The model parameter of the fracture network is denoted as…”

Section: Mixture Of Multi-scale Parameterizationmentioning

confidence: 99%

“…many works implement history matching based on the continuous fracture modeling method. [8][9][10] Zhang et al [11][12][13] took the geometric parameters of major fractures as the inversion parameters, and A Fractal Discrete Fracture Network Model for History Matching Siavash Nejadi et al 14 took the parameters of different fracture sets as the uncertain parameters. Furthermore, the method of Zhang et al is suitable for solving the reservoir with large fault distribution, while Siavash Nejadi et al' method is more suitable for solving the reservoir of small fracture accumulation development.…”

Section: Introductionmentioning

confidence: 99%

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

Zhang

Cui

et al. 2019

Fractals

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The distribution of fractures is highly uncertain in naturally fractured reservoirs (NFRs) and may be predicted by using the assisted-history-matching (AHM) that calibrates the reservoir model according to some high-quality static data combined with dynamic production data. A general AHM approach for NFRs is to construct a discrete fracture network (DFN) model and estimate model parameters given the observations. However, the large number of fractures prediction required in the AHM process could pose a high-dimensional optimization problem. This difficulty is particularly challenging when the fractures form a complex multi-scale fracture network. We present in this paper an integrated AHM approach of NFRs to tackle these challenges. Two essential ingredients of the method are (1) a 2D fractal-DFN model constructed as the geological simulation model to describe the complex fracture network, and (2) a mixture of multi-scale parameters, built according to the fractal-DNF model, as an inversion parameter model to alleviate the high-dimensional optimization burden caused by complex fracture networks. A reservoir with a multi-scale fracture network is set up to test the performance of the proposed method. Numerical results demonstrate that by use of the proposed method, the fractures well recognized by assimilating production data.

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“…Even if this is seen in a reductivist manner as only based on the motivation of avoiding litigation, to ignore it entirely would be remiss. Investment is being made into research to improve modelling techniques and to address the heterogeneity of wells and sub-surface strata, despite current methods being accepted as sufficient by regulators (Nejadi et al 2017). Whilst this is also to assess viability of the wells and ensure they are operated as efficiently as possible for economic reasons, this has the direct consequence of providing considerable data on the extent of fractures created and the materials and features into which they extend, which regulators could assess to improve environmental monitoring.…”

Section: Public Perceptions and The Public Voicementioning

confidence: 99%

Concern and counter-concern: The challenge of fragmented fears for the reguation of hydraulic fracturing

Pearson

Lynch‐Wood

2017

The Extractive Industries and Society

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History matching and uncertainty quantification of discrete fracture network models in fractured reservoirs

Cited by 36 publications

References 26 publications

An Advanced Discrete Fracture Methodology for Fast, Robust, and Accurate Simulation of Energy Production From Complex Fracture Networks

An Advanced Discrete Fracture Methodology for Fast, Robust, and Accurate Simulation of Energy Production From Complex Fracture Networks

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

Concern and counter-concern: The challenge of fragmented fears for the reguation of hydraulic fracturing

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