scholarly journals On the path to the digital rock physics of gas hydrate-bearing sediments – processing of in situ synchrotron-tomography data

Solid Earth ◽  
2016 ◽  
Vol 7 (4) ◽  
pp. 1243-1258 ◽  
Author(s):  
Kathleen Sell ◽  
Erik H. Saenger ◽  
Andrzej Falenty ◽  
Marwen Chaouachi ◽  
David Haberthür ◽  
...  
Keyword(s):  
Gas Hydrate ◽  
Best Practice ◽  
Rock Physics ◽  
Digital Rock Physics ◽  
Seismic Properties ◽  
Digital Rock ◽  
Synchrotron Tomography ◽  
Unique Approach ◽  
Hydrate Bearing Sediments

Abstract. To date, very little is known about the distribution of natural gas hydrates in sedimentary matrices and its influence on the seismic properties of the host rock, in particular at low hydrate concentration. Digital rock physics offers a unique approach to this issue yet requires good quality, high-resolution 3-D representations for the accurate modeling of petrophysical and transport properties. Although such models are readily available via in situ synchrotron radiation X-ray tomography, the analysis of such data asks for complex workflows and high computational power to maintain valuable results. Here, we present a best-practice procedure complementing data from Chaouachi et al. (2015) with data post-processing, including image enhancement and segmentation as well as exemplary numerical simulations of an acoustic wave propagation in 3-D using the derived results. A combination of the tomography and 3-D modeling opens a path to a more reliable deduction of properties of gas hydrate-bearing sediments without a reliance on idealized and frequently imprecise models.

scholarly journals On the path to the digital rock physics of gas hydrate bearing sediments – processing of in-situ synchrotron-tomography data

2016 ◽  
Author(s):  
Kathleen Sell ◽  
Erik-H. Saenger ◽  
Andrzej Falenty ◽  
Marwen Chaouachi ◽  
David Haberthür ◽  
...  
Keyword(s):  
Gas Hydrate ◽  
Rock Physics ◽  
Digital Rock Physics ◽  
Seismic Properties ◽  
Digital Rock ◽  
Model Free ◽  
Direct Model ◽  
In Situ Experiments ◽  
Hydrate Bearing Sediments

Abstract. To date, very little is known about the distribution of gas hydrates in sedimentary matrices and the resulting matrix-pore network affecting the seismic properties at low hydrate concentration. Digital rock physics offers a unique solution to this issue yet requires good quality, high resolution 3D representations for the accurate modelling of petrophysical and transport properties. Although such models are readily available via in-situ synchrotron radiation X-ray tomography the analysis of such data asks for complex workflows and high computational power to maintain valuable results. Here, we present a best-practise procedure complementing data from Chaouachi et al. (Geochemistry, Geophysics, Geosystems 2015, 16 (6), 1711–1722) with data post-processing, including image enhancement and segmentation as well as numerical simulations in 3D using the derived results as a direct model input. The method presented opens a path to a model-free deduction of the properties of gas hydrate bearing sediments when aiming for in-situ experiments linked to synchrotron-based tomography and 3D modelling.

scholarly journals Construction of pore structure and lithology of digital rock physics based on laboratory experiments

2021 ◽  
Vol 11 (5) ◽  
pp. 2113-2125
Author(s):  
Chenzhi Huang ◽  
Xingde Zhang ◽  
Shuang Liu ◽  
Nianyin Li ◽  
Jia Kang ◽  
...  
Keyword(s):  
Pore Structure ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Laboratory Experiments ◽  
Rock Physics ◽  
Reconstruction Method ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
The Core

AbstractThe development and stimulation of oil and gas fields are inseparable from the experimental analysis of reservoir rocks. Large number of experiments, poor reservoir properties and thin reservoir thickness will lead to insufficient number of cores, which restricts the experimental evaluation effect of cores. Digital rock physics (DRP) can solve these problems well. This paper presents a rapid, simple, and practical method to establish the pore structure and lithology of DRP based on laboratory experiments. First, a core is scanned by computed tomography (CT) scanning technology, and filtering back-projection reconstruction method is used to test the core visualization. Subsequently, three-dimensional median filtering technology is used to eliminate noise signals after scanning, and the maximum interclass variance method is used to segment the rock skeleton and pore. Based on X-ray diffraction technology, the distribution of minerals in the rock core is studied by combining the processed CT scan data. The core pore size distribution is analyzed by the mercury intrusion method, and the core pore size distribution with spatial correlation is constructed by the kriging interpolation method. Based on the analysis of the core particle-size distribution by the screening method, the shape of the rock particle is assumed to be a more practical irregular polyhedron; considering this shape and the mineral distribution, the DRP pore structure and lithology are finally established. The DRP porosity calculated by MATLAB software is 32.4%, and the core porosity measured in a nuclear magnetic resonance experiment is 29.9%; thus, the accuracy of the model is validated. Further, the method of simulating the process of physical and chemical changes by using the digital core is proposed for further study.

Strengthening the Digital Rock Physics, Using Downsampling for Sub-Resolved Pores in Tight Sandstones

2021 ◽  
pp. 103869
Author(s):  
Mohammad Ebadi ◽  
Denis Orlov ◽  
Ivan Makhotin ◽  
Vladislav Krutko ◽  
Boris Belozerov ◽  
...  
Keyword(s):  
Rock Physics ◽  
Digital Rock Physics ◽  
Digital Rock

scholarly journals Validation of Digital Rock Physics Algorithms

Minerals ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 669
Author(s):  
Rongrong Lin ◽  
Leon Thomsen
Keyword(s):  
Rock Physics ◽  
Image Resolution ◽  
Staggered Grid ◽  
Static Properties ◽  
Shear Moduli ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Saturated Rock ◽  
Theoretical Predictions ◽  
Theoretical Test

With a detailed microscopic image of a rock sample, one can determine the corresponding 3-D grain geometry, forming a basis to calculate the elastic properties numerically. The issues which arise in such a calculation include those associated with image resolution, the registration of the digital numerical grid with the digital image, and grain anisotropy. Further, there is a need to validate the numerical calculation via experiment or theory. Because of the geometrical complexity of the rock, the best theoretical test employs the Hashin–Shtrikman result that, for an aggregate of two isotropic components with equal shear moduli, the bulk modulus is uniquely determined, independent of the micro-geometry. Similarly, for an aggregate of two isotropic components with a certain combination of elastic moduli defined herein, the Hashin–Shtrikman formulae give a unique result for the shear modulus, independent of the micro-geometry. For a porous, saturated rock, the solid incompressibility may be calculated via an “unjacketed” test, independent of the micro-geometry. Any numerical algorithm proposed for digital rock physics computation should be validated by successfully confirming these theoretical predictions. Using these tests, we validate a previously published staggered-grid finite difference damped time-stepping algorithm to calculate the static properties of digital rock models.

Digital Rock Typing DRT Algorithm Formulation with Optimal Supervised Semantic Segmentation

2022 ◽  
Author(s):  
Omar Alfarisi ◽  
Djamel Ouzzane ◽  
Mohamed Sassi ◽  
TieJun Zhang
Keyword(s):  
Carbonate Rock ◽  
Chemical Properties ◽  
Rock Physics ◽  
Semantic Segmentation ◽  
Rock Properties ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Rock Types ◽  
Fluid Saturation ◽  
Rock Typing

<p><a></a>Each grid block in a 3D geological model requires a rock type that represents all physical and chemical properties of that block. The properties that classify rock types are lithology, permeability, and capillary pressure. Scientists and engineers determined these properties using conventional laboratory measurements, which embedded destructive methods to the sample or altered some of its properties (i.e., wettability, permeability, and porosity) because the measurements process includes sample crushing, fluid flow, or fluid saturation. Lately, Digital Rock Physics (DRT) has emerged to quantify these properties from micro-Computerized Tomography (uCT) and Magnetic Resonance Imaging (MRI) images. However, the literature did not attempt rock typing in a wholly digital context. We propose performing Digital Rock Typing (DRT) by: (1) integrating the latest DRP advances in a novel process that honors digital rock properties determination, while; (2) digitalizing the latest rock typing approaches in carbonate, and (3) introducing a novel carbonate rock typing process that utilizes computer vision capabilities to provide more insight about the heterogeneous carbonate rock texture.<br></p>

Predictive digital rock physics without segmentation

2021 ◽  
pp. 105008
Author(s):  
Eric J. Goldfarb ◽  
Ken Ikeda ◽  
Richard A. Ketcham ◽  
Maša Prodanović ◽  
Nicola Tisato
Keyword(s):  
Rock Physics ◽  
Digital Rock Physics ◽  
Digital Rock
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