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LSM-DFN Modeling for Seismic Responses in Complex Fractured Media: Comparison of Static and Dynamic Elastic Moduli

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 Added by Ning Liu
 Publication date 2021
  fields Physics
and research's language is English




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Crack microgeometries pose a paramount influence on effective elastic characteristics and sonic responses. Geophysical exploration based on seismic methods are widely used to assess and understand the presence of fractures. Numerical simulation as a promising way for this issue, still faces some challenges. With the rapid development of computers and computational techniques, discrete-based numerical approaches with desirable properties have been increasingly developed, but have not yet extensively applied to seismic response simulation for complex fractured media. For this purpose, we apply the coupled LSM-DFN model (Liu and Fu, 2020b) to examining the validity in emulating elastic wave propagation and scattering in naturally-fractured media. By comparing to the theoretical values, the implement of the schema is validated with input parameters optimization. Moreover, dynamic elastic moduli from seismic responses are calculated and compared with static ones from quasi-static loading of uniaxial compression tests. Numerical results are consistent with the tendency of theoretical predictions and available experimental data. It shows the potential for reproducing the seismic responses in complex fractured media and quantitatively investigating the correlations and differences between static and dynamic elastic moduli.



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59 - Ning Liu 2020
Crack micro-geometries and tribological properties pose an important impact on the elastic characteristics of fractured rocks. Numerical simulation as a promising way for this issue still faces some challenges. With the rapid development of computers and computational techniques, discrete-based numerical approaches with desirable properties have been increasingly developed, but few attempts to consider the particle surface roughness in a lattice type model. For this purpose, an integrated numerical scheme accounting rough contact deformation is developed by coupling modified LSM and DFN modeling for predicting the effective mechanical properties of a realistic outcrop. Smooth joint logic is introduced to consider contact and slip behaviors at fracture surfaces and a modified contact relation to estimating the normal force-displacement from rough contact deformation. Improved constitutive laws are developed and employed for rock matrix and rough fracture surface and implemented in the modified LSM. Complex fracture networks presented by DFNs are automatically extracted based on the gradient Hough transform algorithm. This developed framework is validated by classic equivalent medium theories. It shows the model could be used to emulate naturally-fractured media and to quantitatively investigate the effects of fracture attributes and micro-scale surface roughness on the compression mechanism.
We study two-dimensional tensorial elastic wave transport in densely fractured media and document transitions from propagation to diffusion and to localization/delocalization. For large fracture stiffness, waves are propagative at the scale of the system. For small stiffness, multiple scattering prevails, such that waves are diffusive in disconnected fracture networks, and localized in connected ones with a strong multifractality of the intensity field. A reentrant delocalization is found in well-connected networks due to energy leakage via evanescent waves and cascades of mode conversion.
Field-scale properties of fractured rocks play crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion technique to infer two such parameters, fracture density and fractal dimension, from cross-borehole thermal experiments data. It is based on a particle-based heat-transfer model, whose evaluation is accelerated with a deep neural network (DNN) surrogate that is integrated into a grid search. The DNN is trained on a small number of heat-transfer model runs, and predicts the cumulative density function of the thermal field. The latter is used to compute fine posterior distributions of the (to-be-estimated) parameters. Our synthetic experiments reveal that fracture density is well constrained by data, while fractal dimension is harder to determine. Adding non-uniform prior information related to the DFN connectivity improves the inference of this parameter.
Seismic attributes calculated by conventional methods are susceptible to noise. Conventional filtering reduces the noise in the cost of losing the spectral bandwidth. The challenge of having a high-resolution and robust signal processing tool motivated us to propose a sparse time-frequency decomposition while is stabilized for random noise. The procedure initiates by using Sparsity-based adaptive S-transform to regularize abrupt variations in frequency content of the nonstationary signals. Then, considering the fact that a higher amplitude of a frequency component results in a higher signal to noise ratio, an adaptive filter is applied to the time-frequency spectrum which is sparcified previously. The proposed zero adaptive filter enhances the high amplitude frequency components while suppresses the lower ones. The performance of the proposed method is compared to the sparse S-transform and the robust window Hilbert transform in estimation of instantaneous attributes by applying on synthetic and real data sets. Seismic attributes estimated by the proposed method is superior to the conventional ones in terms of its robustness and high resolution image. The proposed approach has a vast application in interpretation and identification of geological structures.
This paper presents two approaches to mathematical modelling of a synthetic seismic pulse, and a comparison between them. First, a new analytical model is developed in two-dimensional Cartesian coordinates. Combined with an initial condition of sufficient symmetry, this provides a valuable check for the validity of the numerical method that follows. A particular initial condition is found which allows for a new closed-form solution. A numerical scheme is then presented which combines a spectral (Fourier) representation for displacement components and wave-speed parameters, a fourth order Runge-Kutta integration method, and an absorbing boundary layer. The resulting large system of differential equations is solved in parallel on suitable enhanced performance desktop hardware in a new software implementation. This provides an alternative approach to forward modelling of waves within isotropic media which is efficient, and tailored to rapid and flexible developments in modelling seismic structure, for example, shallow depth environmental applications. Visual comparisons of the analytic solution and the numerical scheme are presented.
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