Using Digital Rock Physics to Investigate the Impacts of Diagenesis Events and Pathways on Rock Properties

2020 ◽  
pp. 108025
Author(s):  
Yuqi Wu ◽  
Pejman Tahmasebi ◽  
Chengyan Lin ◽  
Chunmei Dong
Keyword(s):  
Rock Physics ◽  
Rock Properties ◽  
Digital Rock Physics ◽  
Digital Rock

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>

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>

scholarly journals Digital rock physics approach to simulate hydraulic effects of anhydrite cement in Bentheim sandstone

2020 ◽  
Vol 54 ◽  
pp. 33-39
Author(s):  
Maria Wetzel ◽  
Thomas Kempka ◽  
Michael Kühn
Keyword(s):  
Large Scale ◽  
Pore Space ◽  
Rock Physics ◽  
Rock Properties ◽  
Permeability Evolution ◽  
Three Dimensional Model ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Precipitation Regimes ◽  
Macro Scale

Abstract. Cementation of potential reservoir rocks is a geological risk, which may strongly reduce the productivity and injectivity of a reservoir, and hence prevent utilisation of the geologic subsurface, as it was the case for the geothermal well of Allermöhe, Germany. Several field, laboratory and numerical studies examined the observed anhydrite cementation to understand the underlying processes and permeability evolution of the sandstone. In the present study, a digital rock physics approach is used to calculate the permeability variation of a highly resolved three-dimensional model of a Bentheim sandstone. Porosity-permeability relations are determined for reaction- and transport-controlled precipitation regimes, whereby the experimentally observed strong decrease in permeability can be approximated by the transport-limited precipitation assuming mineral growth in regions of high flow velocities. It is characterised by a predominant clogging of pore throats, resulting in a drastic reduction in connectivity of the pore network and can be quantified by a power law with an exponent above ten. Since the location of precipitation within the pore space is crucial for the hydraulic rock properties at the macro scale, the determined porosity-permeability relations should be accounted for in large-scale numerical simulation models to improve their predictive capabilities.

Digital rock physics: A geological driven segmentation workflow for Ruhr sandstone

2021 ◽  
Author(s):  
Martin Balcewicz ◽  
Mirko Siegert ◽  
Marcel Gurris ◽  
David Krach ◽  
Matthias Ruf ◽  
...  
Keyword(s):  
High Resolution ◽  
Rock Physics ◽  
Rock Properties ◽  
Homogeneity Test ◽  
Grayscale Image ◽  
Sample Sizes ◽  
Digital Rock Physics ◽  
Digital Twin ◽  
Digital Rock

&lt;p&gt;Over the last two decades, Digital Rock Physics (DRP) has become a complementary part of the characterization of reservoir rocks due to, among other things, the non-destructive testing character of this technique. The use of high-resolution X-ray Computed Tomography (XRCT) has become widely accepted to create a digital twin of the material under investigation. Compared to other imaging techniques, XRCT technology allows a location-dependent resolution of the individual material particles in volume. However, there are still challenges in assigning physical properties to a particular voxel within the digital twin, due to standard histogram analysis or sub-resolution features in the rock. For this reason, high-resolution image-based data from XRCT, transmitted-light microscope, Scanning Electron Microscope (SEM) as well as inherent material properties like porosity are combined to obtain an optimal spatial image of the studied Ruhr sandstone by a geologically driven segmentation workflow. On the basis of a homogeneity test, which corresponds to the evaluation of the grayscale image histogram, the preferred scan sample sizes in terms of transport, thermal, and effective elastic rock properties are determined. In addition, the advanced numerical simulation results are compared with laboratory tests to provide possible upper limits for sample size, segmentation accuracy, and a calibrated digital twin of the Ruhr sandstone. The comparison of representative grayscale image histograms as a function of sample sizes with the corresponding advanced numerical simulations, provides a unique workflow for reservoir characterization of the Ruhr sandstone.&lt;/p&gt;

Integrating grain-scale geology in digital rock physics

2018 ◽  
Vol 37 (6) ◽  
pp. 428-434
Author(s):  
Sander Hunter ◽  
Ronny Hofmann ◽  
Irene Espejo
Keyword(s):  
Pore Space ◽  
Digital Simulation ◽  
Rock Physics ◽  
Rock Properties ◽  
Micro Ct ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Full Characterization ◽  
Compositional Information

Digital rock physics (DRP) is a rapidly evolving field of study. One component of digital rock that has not received sufficient attention is how well actual rocks are represented in DRP. Instead, the digital rock community is focused on characterizing the pore space in volumes of rock imaged by microcomputed tomography (micro-CT) and simulating flow through that digitized pore network. This enables computational simulations of routine core analysis measurements, which may be completed in hours instead of days or weeks. Although this alone makes digital rock a worthwhile endeavor, it overlooks much of the detailed textural and compositional information stored within digital rock images below the resolution of micro-CT imaging. This information may be observed in high-resolution 2D transmitted light microscopy images. Textural information impacts not only the tortuosity of the flow path, impacting permeability, but also influences how the rock will respond to stress. Compositional information could also be extracted to not only better characterize the wettability of rocks for relative permeability simulations, but also to supplement petrographic information in diagenetic modeling, among other applications. Ultimately, a full characterization of a digital rock should replicate the acoustic, geomechanical, and petrophysical properties of the imaged sample. The first step toward achieving full digital simulation of rock properties is the fundamental characterization of the sample — extracting the textural and compositional information from digital rock images. Unfortunately, this is a nontrivial undertaking. It involves acquiring sample images, segmenting pores from individual rock minerals, separating these minerals into individual grains and cements, and computing multiple attributes from the segmented grains. To address this issue, we are developing a workflow to compute key textural attributes from images with a long-term vision for the incorporation of geologic characterization into DRP using machine learning.

scholarly journals Variable secondary porosity modeling of carbonate rocks based on μ-CT images

2019 ◽  
Vol 11 (1) ◽  
pp. 617-626
Author(s):  
Xin Nie ◽  
Chi Zhang ◽  
Chenchen Wang ◽  
Shichang Nie ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Carbonate Rocks ◽  
Three Dimensional ◽  
Rock Physics ◽  
Carbonate Reservoir ◽  
Rock Properties ◽  
Secondary Porosity ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
The Matrix ◽  
Physical Simulations

Abstract As an essential carbonate reservoir parameter, porosity is closely related to rock properties. Digital rock physics (DRP) technology can help us to build forward models and find out the relationship between porosity and physical properties. In order to prepare models for the rock physical simulations of carbonate rocks, digital rock models with different porosities and fractures are needed. Based on a three-dimensional carbonate digital rock image obtained by X-ray microtomography (μ-CT), we used erosion and dilation in mathematical morphology to modify the pores, and fractional Brownian motion model (FBM) to create fractures with different width and angles. The pores become larger after the erosion operation and become smaller after the dilation operation. Therefore, a series of models with different porosities are obtained. From the analysis of the rock models, we found out that the erosion operation is similar to the corrosion process in carbonate rocks. The dilation operation can be used to restore the matrix of the late stages. In both processes, the pore numbers decrease because of the pore surface area decreases. The porosity-permeability relation of the models is a power exponential function similar to the experimental results. The structuring element B’s radius can affect the operation results. The FBM fracturing method has been proved reliable in sandstones, and because it is based on mathematics, the usage of it can also be workable in carbonate rocks. We can also use the processes and workflows introduced in this paper in carbonate digital rocks reconstructed in other ways. The models we built in this research lay the foundation of the next step physical simulations.

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