Mechanical effects of rock cement alteration quantified using digital rock physics

2020 ◽  
Author(s):  
Maria Wetzel ◽  
Thomas Kempka ◽  
Michael Kühn
Keyword(s):  
Three Dimensional ◽  
Rock Physics ◽  
Mineral Dissolution ◽  
Rock Properties ◽  
Pore Filling ◽  
Porous Network ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Macro Scale ◽  
Cement Distribution

<p>Mineral dissolution is a micro-scale process, which may significantly alter the microstructure of rocks, and consequently affect their effective mechanical behavior at the macro scale. Predicting changes in rock stiffness is of paramount importance within the context of risk assessment for most applications related to geological subsurface utilization, where reduction of mechanical parameters is of particular relevance to assess reservoir, caprock and fault integrity [1].</p><p>In the present study, the effective elastic properties of typical reservoir rocks are determined based on micro-computer tomography (micro-CT) scans. The resulting three-dimensional rock geometry comprises a more realistic microstructure regarding the shapes of grains, cements and the overall porous network compared to available empirical approaches. Effective rock stiffness is calculated by a static finite element method, which imposes an uniform strain on the digital rock sample and calculates the resulting stresses. The effect of spatial cement distribution within the pore network is taken into account, considering passive pore filling as well as framework supporting cements. <span xml:lang="DE-DE" data-contrast="auto"><span>Rock </span><span>stiffness</span> <span>increases</span><span> due </span><span>to</span> <span>the</span> </span><span xml:lang="DE-DE" data-contrast="auto"><span>precipitation</span> </span><span xml:lang="DE-DE" data-contrast="auto"><span>of</span> <span>pore-filling</span> <span>minerals</span></span>. This quantitative approach substantially improves the accuracy in predicting elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in mineral distribution.</p><p>[1] Wetzel M., Kempka T., Kühn M. (2018): Quantifying Rock Weakening Due to Decreasing Calcite Mineral Content by Numerical Simulations. Materials, 11, 4, 542. DOI: http://doi.org/10.3390/ma11040542</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.

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.

Digital reconstruction of reservoir sandstones to predict hydraulic and mechanical rock properties

2021 ◽  
Author(s):  
Maria Wetzel ◽  
Thomas Kempka ◽  
Michael Kühn
Keyword(s):  
Numerical Simulations ◽  
Mineral Content ◽  
Practical Importance ◽  
Rock Physics ◽  
Mineral Dissolution ◽  
Rock Properties ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Reservoir Sandstones ◽  
The Impact

<p>Quantifying trends in hydraulic and mechanical properties of reservoir sandstones has a wide practical importance for many applications related to geological subsurface utilization. In that regard, predicting macroscopic rock properties requires detailed information on their microstructure [1]. In order to fundamentally understand the pore-scale processes governing the rock behaviour, digital rock physics represents a powerful and flexible approach to investigate essential rock property relations [2]. This was shown, e.g., for hydraulic effects of anhydrite cement in the Bentheim sandstone in relation to an unsuccessful drilling campaign at the geothermal well Allermöhe, Germany [3]. Rock weakening due to decreasing calcite mineral content was also demonstrated by application of numerical simulations [4]. </p><p>In the present study, a process-based method is used for reconstructing the full 3D microstructure of three typical reservoir reference rocks: the Fontainebleau, Berea and Bentheim sandstones. For that purpose, grains are initially deposited under the influence of gravity and afterwards diagenetically consolidated. The resulting evolution in porosity, permeability and rock stiffness is examined and compared to the respective micro-CT scans of the sandstones. The presented approach enables to efficiently generate synthetic sandstone samples over a broad range of porosities, comprising the microstructural complexity of natural rocks and considering any desired size, sorting and shape of grains. In view of a virtual laboratory, these synthetic samples can be further altered to examine the impact of mineral dissolution and/or precipitation as well as fracturing on various petrophysical correlations, what is of particular relevance for a sustainable exploration and utilisation of the geological subsurface.</p><p>[1] Wetzel M., Kempka T., Kühn M. (2017): Predicting macroscopic elastic rock properties requires detailed information on microstructure. Energy Procedia, 125, 561-570. DOI: 10.1016/j.egypro.2017.08.195 <br>[2] Wetzel M., Kempka T., Kühn M. (2020): Hydraulic and mechanical impacts of pore space alterations within a sandstone quantified by a flow velocity-dependent precipitation approach. Materials, 13, 4, 3100. DOI: 10.3390/ma13143100<br>[3] Wetzel M., Kempka T., Kühn M. (2020): Digital rock physics approach to simulate hydraulic effects of anhydrite cement in Bentheim sandstone. Advances in Geosciences, 54, 33-39. DOI: 10.5194/adgeo-54-33-2020 <br>[4] Wetzel M., Kempka T., Kühn M. (2018): Quantifying rock weakening due to decreasing calcite mineral content by numerical simulations. Materials, 11, 542. DOI: 10.3390/ma11040542 </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>

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 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;

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