Multiscale Reconstructions, Effective Elastic Properties, and Ultrasonic Responses of Kerogen Matter Based on Digital Organic Shales

Abstract

Organic shales usually present significant heterogeneities in rock textures and reservoir properties due to differing kerogen contents and morphologies, subsequently impacting shale elastic properties and acoustic responses. Numerical upscaling of digital organic shales to evaluate effective elastic properties and acoustic responses has important implications for source rocks and unconventional reservoir characterization. We propose a modeling framework that includes the multiscale reconstruction of kerogen distributions, the numerical modeling of effective elastic properties, and the acoustic response to evaluate the contribution of organic matter. Based on digitized images of the microstructure of Longmaxi black shale samples obtained by X-ray CT, the kerogen components are identified and decomposed into different-level slices in terms of organic matter sizes and morphologies. Multiscale random media reconstruction is applied to these kerogen slices, with synthetic kerogen distributions validated by original counterparts. A finiteelement method is used to model the effective elastic properties of digital organic shales, by which we investigate the effect of different kerogen contents and organic matter morphologies. We use a rotated staggered-grid finite-difference method to simulate ultrasonic wave propagation in digital organic shales to evaluate the response of different kerogen contents and organic matter morphologies. Numerical examples show that the multiscale random media method can be applicable to natural organic shales for the reconstruction of kerogen distributions. The elastic properties mainly depend on kerogen contents, with less influence by organic matter morphologies. The ultrasonic scattering effects become stronger for higher kerogen contents with smaller rounding coefficients. Our results confirm the applicability of the proposed modeling framework to support unconventional reservoir characterization. The purpose of this study is to provide the possibility of indicating the sweet point of shale. INDEX TERMS Digital organic shales, effective elastic properties, kerogen contents, multiscale reconstructions, organic matter morphologies, ultrasonic responses.

Factors that influence fluid flow in a single fracture

“…(2019), the height z distribution in the location ( x , y ) can be calculated by the random function that satisfies the Gaussian distribution as follows: where RAND G ( x,y ) represents the random function that satisfies Gaussian distribution with PSDF as p . By using equation (), we can generate the rough fracture surface with the use of MATLAB software (Rao et al ., 2021), with the height standard deviation as σ .…”

“…where RAND G (x,y) represents the random function that satisfies Gaussian distribution with PSDF as p. By using equation (2), we can generate the rough fracture surface with the use of MATLAB software (Rao et al, 2021), with the height standard deviation as σ . Kang et al (2016) and Ma et al (2019) point out that, because the autocorrelation of the lower surface length λ represents the distribution of the mismatching in the real fractures, the fracture with a rough elastic lower surface and a flat rigid upper surface can reflect the fracture properties.…”