scholarly journals Digital Carbonate Rock Physics

2016 ◽  
Author(s):  
Erik H. Saenger ◽  
Stephanie Vialle ◽  
Maxim Lebedev ◽  
David Uribe ◽  
Maria Osorno ◽  
...  
Keyword(s):  
Carbonate Rock ◽  
Image Data ◽  
Rock Physics ◽  
Rock Properties ◽  
Micro Computed Tomography ◽  
S Wave ◽  
Digital Rock Physics ◽  
Intermediate Phases ◽  
Mean Filter ◽  
Rock Characterization

Abstract. Modern estimation of rock properties combines imaging with advanced numerical simulations, an approach known as Digital Rock Physics (DRP). In this paper we suggest a specific segmentation procedure of X-Ray micro-Computed Tomography data with two different resolutions for two sets of carbonate rock samples. These carbonates were already characterized in detail in a previous laboratory study which we complement with nano-indentation experiments. In a first step a non-local mean filter is applied to the raw image data. We then apply different thresholds to identify pores and solid phases. Because of a non-neglectable amount of unresolved micro-porosity (“micritic phase”) we also define intermediate phases. Based on this segmentation we determine porosity-dependent values for P- and S-wave velocities as well as for the intrinsic permeability. The porosity measured in the laboratory is then used to predict the effective rock properties for a comparison with experimental data. Anisotropy is observed for some sub-samples, but seems to be insignificant in our case. Because of the complexity of carbonates we suggest to use DRP as a complementary tool for rock characterization in addition to classical experimental methods.

scholarly journals Digital carbonate rock physics

Solid Earth ◽  
2016 ◽  
Vol 7 (4) ◽  
pp. 1185-1197 ◽  
Author(s):  
Erik H. Saenger ◽  
Stephanie Vialle ◽  
Maxim Lebedev ◽  
David Uribe ◽  
Maria Osorno ◽  
...  
Keyword(s):  
Elastic Properties ◽  
Carbonate Rock ◽  
Rock Physics ◽  
Rock Properties ◽  
Micro Computed Tomography ◽  
Low Resolution ◽  
Two Phase ◽  
Data Set ◽  
Rock Characterization ◽  
Low Resolution Images

Abstract. Modern estimation of rock properties combines imaging with advanced numerical simulations, an approach known as digital rock physics (DRP). In this paper we suggest a specific segmentation procedure of X-ray micro-computed tomography data with two different resolutions in the µm range for two sets of carbonate rock samples. These carbonates were already characterized in detail in a previous laboratory study which we complement with nanoindentation experiments (for local elastic properties). In a first step a non-local mean filter is applied to the raw image data. We then apply different thresholds to identify pores and solid phases. Because of a non-neglectable amount of unresolved microporosity (micritic phase) we also define intermediate threshold values for distinct phases. Based on this segmentation we determine porosity-dependent values for effective P- and S-wave velocities as well as for the intrinsic permeability. For effective velocities we confirm an observed two-phase trend reported in another study using a different carbonate data set. As an upscaling approach we use this two-phase trend as an effective medium approach to estimate the porosity-dependent elastic properties of the micritic phase for the low-resolution images. The porosity measured in the laboratory is then used to predict the effective rock properties from the observed trends for a comparison with experimental data. The two-phase trend can be regarded as an upper bound for elastic properties; the use of the two-phase trend for low-resolution images led to a good estimate for a lower bound of effective elastic properties. Anisotropy is observed for some of the considered subvolumes, but seems to be insignificant for the analysed rocks at the DRP scale. Because of the complexity of carbonates we suggest using DRP as a complementary tool for rock characterization in addition to classical experimental methods.

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 Electrical Formation Factor of Clean Sand from Laboratory Measurements and Digital Rock Physics

2019 ◽  
Author(s):  
Mohammed Ali Garba ◽  
Stephanie Vialle ◽  
Mahyar Madadi ◽  
Boris Gurevich ◽  
Maxim Lebedev
Keyword(s):  
Rock Physics ◽  
Small Samples ◽  
Sand Sample ◽  
Laboratory Measurements ◽  
Micro Computed Tomography ◽  
Formation Factor ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Computed Tomography Images ◽  
Average Grain Size

Abstract. Electrical properties of rocks are important parameters for well-log and reservoir interpretation. Laboratory measurements of such properties are time-consuming, difficult, and are impossible in some cases. Being able to compute them from 3-D images of small samples will allow generating massive data in a short time, opening new avenues in applied and fundamental science. To become a reliable method, the accuracy of this technology needs to be tested. In this study, we developed a comprehensive and robust workflow with clean sand from two beaches. Electrical conductivities at 1 kHz were first carefully measured in the laboratory. A range of porosities spanning from a minimum of 0.26 to 0.33 to a maximum of 0.39 to 0.44, depending on the samples. Such range was achieved by compacting the samples in a way that reproduces natural packing of sand. Characteristic electrical formation factor versus porosity relationships were then obtain for each sand type. 3-D micro-computed tomography images of each sand sample from the experimental sand pack were acquired at different resolutions. Image processing was done using global thresholding method and up to 96 sub-samples of sizes from (200)3 to (700)3 voxels. After segmentation, the images were used to compute the effective electrical conductivity of the sub-cubes using a Finite Element electrostatic modelling. For the samples, a good agreement between laboratory measurements and computation from digital cores was found, if the sub-cube size REV is reached that is between (1300 μm)3 and (1820 μm)3, which, with an average grain size of 160 μm, is between 8 and 11 grains. Computed digital rock images of the clean sands have opened a way forward in getting the formation factor within a shortest possible time; laboratory calculations take five (5) to thirty-five (35) days as in the case of clean and shaly sands respectively, whereas, the digital tomography takes just three (3) to five (5) hours.

Recent advances in rock physics

Geophysics ◽  
1985 ◽  
Vol 50 (12) ◽  
pp. 2480-2491 ◽  
Author(s):  
David P. Yale
Keyword(s):  
Electrical Properties ◽  
Seismic Waves ◽  
Seismic Velocity ◽  
Pore Space ◽  
Rock Physics ◽  
Rock Properties ◽  
Bright Spot ◽  
Geometrical Parameters ◽  
S Wave ◽  
Velocity Models

The need to extract more information about the subsurface from geophysical and petrophysical measurements has led to a great interest in the study of the effect of rock and fluid properties on geophysical and petrophysical measurements. Rock physics research in the last few years has been concerned with studying the effect of lithology, fluids, pore geometry, and fractures on velocity; the mechanisms of attenuation of seismic waves; the effect of anisotropy; and the electrical and dielectric properties of rocks. Understanding the interrelationships between rock properties and their expression in geophysical and petrophysical data is necessary to integrate geophysical, petrophysical, and engineering data for the enhanced exploration and characterization of petroleum reservoirs. The use of amplitude offsets, S‐wave seismic data, and full‐waveform sonic data will help in the discrimination of lithology. The effect of in situ temperatures and pressures must be taken into account, especially in fractured and unconsolidated reservoirs. Fluids have a strong effect on seismic velocities, through their compressibility, density, and chemical effects on grain and clay surfaces. S‐wave measurements should help in bright spot analysis for gas reservoirs, but theoretical considerations still show that a deep, consolidated reservoir will not have any appreciable impedance contrast due to gas. The attenuation of seismic waves has received a great deal of attention recently. The idea that Q is independent of frequency has been challenged by experimental and theoretical findings of large peaks in attenuation in the low kHz and hundreds of kHz regions. The attenuation is thought to be due to fluid‐flow mechanisms and theories suggest that there may be large attenuation due to small amounts of gas in the pore space even at seismic frequencies. Models of the effect of pores, cracks, and fractures on seismic velocity have also been studied. The thin‐crack velocity models appear to be better suited for representing fractures than pores. The anisotropy of seismic waves, especially the splitting of polarized S‐waves, may be diagnostic of sets of oriented fractures in the crust. The electrical properties of rocks are strongly dependent upon the frequency of the energy and logging is presently being done at various frequencies. The effects of frequency, fluid salinity, clays, and pore‐grain geometry on electrical properties have been studied. Models of porous media have been used extensively to study the electrical and elastic properties of rocks. There has been great interest in extracting geometrical parameters about the rock and pore space directly from microscopic observation. Other models have focused on modeling several different properties to find relationships between rock properties.

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