Effect Of Rock Properties Research Articles

Core‐flooding experiments of various concentrations of CO2/N2 mixture in different rocks: II. Effect of rock properties on residual water

AbstractDuring CO2 storage in deep saline aquifers, the presence of residual water has an important influence on the storage efficiency and safety. In this study, natural rock cores taken from deep reservoirs in the Ordos Basin and Fukang, Xinjiang are used as research objects. Nine groups of core‐flooding experiments are performed under different CO2/N2 gas mixture ratios to study the influence of rock properties (mineral composition, permeability, porosity and pore structure) on the residual water. Furthermore, the geophysical and chemical properties of rock cores are analyzed by X‐ray diffraction, electron microscopy, field emission scanning electron microscopy and piezoelectric mercury method. The results show that residual water saturation is a quantitative power function of drainage time. The residual water saturation is positively correlated with the total amount of quartz and feldspar and increases with increasing permeability. Moreover, both the average and median pore throat radius show a strong inverse correlation with irreducible residual water saturation; as these radius increase, the residual water saturation decreases. In contrast, the porosity and maximum pore throat radius display a weaker correlation with irreducible residual water saturation. This study is of great value for engineering practices such as the site selection of CO2 storage projects in saline aquifer and improvement of CO2 storage efficiency. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.

Effect of rock properties on wear and cutting performance of multi blade circular saw with iron based multi-layer diamond segments

This study is an attempt for comprehensive, combining experimental data with advanced analytical techniques and machine learning for a thorough understanding of the factors influencing the wear and cutting performance of multi-blade diamond disc cutters on granite blocks. A series of sawing experiments were performed to evaluate the wear and cutting performance of multi blade diamond disc cutters with varying diameters in the processing of large-sized granite blocks. The multi-layer diamond segments comprising the Iron (Fe) based metal matrix were brazed on the sawing blades. The segment’s wear was studied through micrographs and data obtained from the Field Emission Scanning Electron Microscopy (FESEM) and Energy Dispersive X-ray (EDS). Granite rock samples of nine varieties were tested in the laboratory to determine the quantitative rock parameters. The contribution of individual rock parameters and their combined effects on wear and cutting performance of multi blade saw were correlated using statistical machine learning methods. Moreover, predictive models were developed to estimate the wear and cutting rate based on the most significant rock properties. The point load strength index, uniaxial compressive strength, and deformability, Cerchar abrasivity index, and Cerchar hardness index were found to be the significant variables affecting the sawing performance.

Attenuation characteristics of shock waves in drilling and blasting based on viscoelastic wave theory

This study investigates the propagation and attenuation characteristics of shock waves produced by drilling and blasting. The focus is on a novel method for calculating the attenuation of the shock wave pressure. Based on the propagation of shock waves in a rod with a variable section and a Maxwell model for rock, theoretical solutions for the attenuation of the blast-induced shock wave pressure were derived and the main factors influencing the attenuation speed were analyzed. The attenuation law of shock waves for siltstone, limestone, and granite, with common borehole diameters of 76–150 mm and initial shock pressures of 1–6 GPa, was analyzed through numerical simulations. The results show that the shock wave falls off as the square root of the relative distance. The attenuation speed of the shock wave is mainly related to the borehole size, rock properties, and shock wave intensity. The attenuation speed increases with increasing initial shock pressure on the borehole wall, but decreases with increasing borehole radius. Compared with soft rock, the shock wave pressure attenuates faster in hard rock. Combining theoretical analysis and numerical simulations, an exponential attenuation coefficient was introduced to the attenuation formula. Statistical analysis shows that the exponential attenuation coefficient is linearly proportional to the initial shock pressure. Furthermore, a new method for calculating the attenuation of shock wave pressure was proposed, reflecting the comprehensive influence of rock characteristics and shock wave intensity. The new method is an improvement over existing methods, which only consider the effect of rock properties on shock wave attenuation. The reliability of the new method was verified against the results of field tests. The findings provide a theoretical basis for the optimization of blasting parameters and assessments of blast-resistance for structures.

An Investigation into the Effect of Rock Properties on Drill Bit Life

An Investigation into the Effect of Rock Properties on Drill Bit Life

Hierarchical Homogenization With Deep‐Learning‐Based Surrogate Model for Rapid Estimation of Effective Permeability From Digital Rocks

AbstractEffective permeability is a key physical property of porous media that defines its ability to transport fluid. Digital rock physics (DRP) combines modern tomographic imaging techniques with advanced numerical simulations to estimate effective rock properties. DRP is used to complement or replace expensive and time‐consuming or impractical laboratory measurements. However, with increase in sample size to capture multimodal and multiscale microstructures, conventional approaches based on direct numerical simulation (DNS) are becoming very computationally intensive or even infeasible. To address this computational challenge, we propose a hierarchical homogenization method (HHM) with a data‐driven surrogate model based on 3‐D convolutional neural network (CNN) and transfer learning to estimate effective permeability of digital rocks with large sample sizes up to billions of voxels. This HHM‐CNN workflow divides a large digital rock into small sub‐volumes and predicts their permeabilities through a CNN surrogate model of Stokes flow at the pore scale. The effective permeability of the full digital rock is then predicted by solving the Darcy equations efficiently on the upscaled model in which the permeability of each cell is assigned by the surrogate model. The proposed method has been verified on micro‐CT scans of both sandstones and carbonates, and applied to the Bentheimer sandstone and a reconstructed high‐resolution carbonate rock obtained by multiscale data fusion. The computed permeabilities of the HHM‐CNN are consistent with the results of DNS on the full digital rock. Compared with conventional DNS algorithms, the proposed hierarchical approach can largely reduce the computational time and memory demand.

Digital transformation in rock physics: Deep learning and data fusion

Rock physics plays an essential role in geophysical reservoir characterization. It aims to build a bridge between geophysical measurements and in-situ rock and fluid properties. With the advancement of microscopic imaging and computer science, rock physics is transitioning to the digital age. This is referred to as digital rock physics (DRP). DRP provides a nondestructive and efficient way to determine physical rock properties directly from digital images. Over the last decades, it has become a routine tool in reservoir characterization by complementing or replacing expensive and time-consuming laboratory measurements. With the emergence of deep learning, DRP has advanced significantly from image processing to physical simulation. This paper presents an application of deep learning in multiscale fusion of digital rock images. It aims to overcome the trade-off between image resolution and field of view (FoV) by integrating imaging data from multiple sources including (1) 3D microcomputed tomography images at micronscale with a large FoV and (2) 2D scanning electron microscopy images at nanoscale with a small FoV. The reconstructed image integrates information of microstructures at different scales and helps characterize heterogeneous porous rocks more accurately. It is helpful to improve the prediction accuracy of effective rock properties and to have deeper insight into physical processes at pore scale. Data fusion based on deep learning would unlock new pathways for geophysical characterization of porous rocks, with broad implications for various subsurface applications such as groundwater transport, enhanced oil recovery, and geologic carbon sequestration.

Effects of Rock Properties on the Wear of TBM Disc Cutter: A Case Study of the Yellow River Diversion Project, China

Effects of Rock Properties on the Wear of TBM Disc Cutter: A Case Study of the Yellow River Diversion Project, China

An adaptive prediction method for mechanical properties deterioration of sandstone under freeze\u2013thaw cycles: a case study of Yungang Grottoes

Due to the location of the Yungang Grottoes, freeze–thaw cycles contribute significantly to the degradation of the mechanical properties of the sandstone. The factors influencing the freeze–thaw cycle are classified into two categories: external environmental conditions and the inherent properties of the rock itself. Since the parameters of rock properties are inherent to each rock, the effect of rock properties on freeze–thaw degradation cannot be investigated by the control variates method. An adaptive multi-output gradient boosting decision trees (AMGBDT) algorithm is proposed to fit nonlinear relationships between mechanical properties and physical factors. The hyperparameters in the GBDT algorithm are set as variables, and the Sequential quadratic programming (SQP) algorithm is applied to solve the hyperparameter optimization, which means finding the maximum Score. The case study illustrates that the AMGBDT algorithm can precisely determine the effect of each independent factor on the output. The patterns of mechanical properties are similar when the number of freeze–thaw cycles and porosity are used as variables separately and when both are used simultaneously. The uniaxial compressive strength decay rate is positively correlated with the number of freeze–thaw cycles and porosity. The modulus of elasticity is negatively correlated with the number of freeze–thaw cycles and porosity. The results show that the number of freeze–thaw cycles is the main factor influencing the freeze–thaw cycling action, and the porosity is minor. In addition, the fitting accuracy of the AMGBDT algorithm is generally higher than neural networks (NN) and random forests (RF). Studying the influence of porosity and other rock properties on the freeze–thaw cycle will help to understand the failure mechanism of rock freeze–thaw cycles.

Experimental study of enhanced oil recovery by CO2 huff-n-puff in shales and tight sandstones with fractures

The fractures and kerogen, which generally exist in the shale, are significant to the CO2 huff-n-puff in the shale reservoir. It is important to study the effects of fractures and kerogen on oil recovery during CO2 huff-n-puff operations in the fracture–matrix system. In this study, a modified CO2 huff-n-puff experiment method is developed to estimate the recovery factors and the CO2 injectivity in the fractured organic-rich shales and tight sandstones. The effects of rock properties, injection pressure, and injection time on the recovery factors and CO2 usage efficiency in shales and sandstones are discussed, respectively. The results show that although the CO2 injectivity in the shale is higher than that in the sandstone with the same porosity; besides, the recovery factors of two shale samples are much lower than that of two sandstone samples. This demonstrates that compared with the tight sandstone, more cycles are needed for the shale to reach a higher recovery factor. Furthermore, there are optimal injection pressures (close to the minimum miscible pressure) and CO2 injection volumes for CO2 huff-n-puff in the shale. Since the optimal CO2 injection volume in the shale is higher than that in the sandstone, more injection time is needed to enhance the oil recovery in the shale. There is a reference sense for CO2 huff-n-puff in the fractured shale oil reservoir for enhanced oil recovery (EOR) purposes.

Effect of Rock Properties on Electromagnetic Radiation Characteristics Generated by Rock Fracture During Uniaxial Compression

The phenomenon of electromagnetic radiation (EMR) generated by rock fracture is relatively common. Due to different properties of rock, the variation laws and distribution characteristics of signals in time and frequency domain are significantly different. In this paper, the uniaxial compression experiments of four different kinds of rocks were carried out under the same loading conditions. EMR response characteristics during loading were studied, and the relationship between EMR signal statistics and mechanical parameters or quartz contents of rocks were analyzed. However, quartz content is not a decisive factor since quartz-free rock can also produce significant EMR signals when it fractures. Quartz content does not stimulate the activity and intensity of EMR signals generated by rock fracture. For the same kind of rock, specimen with larger elastic modulus tend to exhibit higher EMR signal intensity. Activity of EMR signals is not strictly proportional to the compressive strength of rocks but affected by complex stress-induced crack events during the loading process. With the continuous evolution of cracks, the dominant frequency of EMR signal shifts from a higher band to a lower frequency. As the quartz content decreases, the dominant frequency of EMR signal appears in a higher frequency band.

Impact of rock properties and wettability on Tertiary-CO2 flooding in a fractured composite chalk reservoir

This study presents the experimental and numerical evaluation of tertiary-CO2 flooding (CF) using reservoir and outcrop composite chalk at reservoir conditions. We were able to reproduce the results of composite core flooding experiment and our findings show the considerable effect of rock properties and wettability on the tertiary-CO2 flooding.In our experiments, we place the composite reservoir chalk core vertically in the core-holder with the total length of 45 cm and average diameter of 3.74 cm. The composite core consists of six core plugs of 7.5 cm each and include a centralized axial hole that represents the single fracture with the diameter of 0.6 cm. The whole core plugs are sampled from the reservoir formation in North-Sea-Chalk-Field (NSCF) and are saturated with NSCF stock tank oil (STO) and synthetic connate water. Once reservoir conditions are established, the sea water is injected from the bottom of the core holder and the STO is produced from the top. After no additional produced oil is observed, water flooding (WF) is stopped and CO2 is then injected from the top and the hydrocarbon streams are produced from the bottom of the fracture. The whole core flooding is operated at constant reservoir conditions of 258 bara and 110 °C, representative of NSCF reservoir conditions. Two different chalks, one from the reservoir formation (Exp-3C) and the other from outcrop (Exp-2C) are used in this study to investigate the effect of wettability during tertiary CO2 flooding. A comprehensive compositional numerical simulation with a tuned equation of state (EOS) was developed to model the experiments. Best match for the WF experiments was achieved mainly through tuning the oil-water capillary pressure and reducing the oil relative permeability data. Although the final tuned capillary pressure and relative permeability data were different, we observe similar water saturation at the end WF experiments for Exp-3C and Exp-2C.The tertiary CF lab results were reproduced by numerical model mainly by tuning the multi-component diffusion coefficients. The produced water during CF was successfully modeled by taking the hysteresis effect into account in water-oil capillary pressure data. We also observe that although the final water saturation at the end of WF is comparable, performance of tertiary CO2 flooding for each experiment is different. The reservoir chalk experiment shows higher oil recovery during the tertiary CO2 injection.

THE EFFECT OF GEOLOGICAL PROPERTIES OF DIMENSION STONES ON THE PREDICTION OF SPECIFIC ENERGY (SE) DURING DIAMOND WIRE CUTTING OPERATIONS

Given the increasing demand for dimension stones, mining operations in quarries have always been an important branch of mining engineering. Among different techniques, diamond wire cutting is one of the most common methods of dimension stone mining. A reliable assessment and accurate prediction of diamond wire cutting performance are essential for feasibility analysis and operational planning in this area. This performance depends on factors such as physical, mechanical, and textural properties of the rock and the characteristics of cutting operations which can be evaluated by criteria such as specific energy, production rate, efficiency, and diamond bead wear rate. This study aims to develop a method for predicting the specific energy of diamond wire cutting in dimension stones based on rock properties. For this purpose, the specific energy of diamond wire cutting in 11 different igneous rock samples was measured. Given the high strength and abrasivity of igneous rocks, cutting operations in these rocks generally requires a great amount of energy. In a series of tests performed on the samples, rock properties such as uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), Young’s modulus, density, textural properties, abrasivity and operating factors such as pullback amperage were measured. The measured parameters were divided into four groups of physical, mechanical, textural, and operating parameters. After determining the specific cutting energy of each sample, the relationship of the energy with each individual property was investigated. This investigation showed that density, abrasivity, and p-wave velocity respectively had the highest correlation with specific energy. Using the correlation results, four input parameters (one from each of the four considered parameter groups) were selected for inclusion in the prediction model. These parameters were density, abrasivity, wave velocity, and amperage. Multivariate linear regression was then used to analyse the effect of rock properties and operating parameters on specific energy. The developed regression model showed that once the rock properties are known, the specific energy can be predicted with an accuracy of 85.8%. The proposed model can be used to estimate the specific energy of diamond wire cutting operations in dimension stone quarries in advance, and predict the amount of energy consumption, the required energy source, and the optimal cutting machine accordingly.

Computation of effective elastic properties of clay from X-ray texture goniometry data

We have developed a new method for estimating the contribution of a pure clay fraction (i.e., devoid of organic matter) to the total effective rock stiffness. The method is based on published clay mineral stiffness data and on an original preferred clay mineral orientation data set obtained by X-ray texture goniometry on 56 samples of Kimmeridgian and Devonian age from two North American shale plays. We find that (1) large variability in preferred orientation of clay results in moderate variability in effective clay elastic anisotropy and (2) the effect of variations in the preferred orientation on effective rock properties is small compared with the effects of variations in clay abundance. As a result, a single clay elastic tensor is computed to be used in effective medium models. In addition, to account for various degrees of hydration, water is incorporated into the dry clay tensor through inclusion models. In situations in which isotropic approximations are necessary, we also provide apparent bulk and shear moduli for a hydrated clay fraction as a function of porosity and propagation angle.

Effect of rock properties on rippability of laterite in Iron Ore mines of Goa

Effect of rock properties on rippability of laterite in Iron Ore mines of Goa

Performance Evaluation of Adaptive Neuro-Fuzzy Inference System and Group Method of Data Handling-Type Neural Network for Estimating Wear Rate of Diamond Wire Saw

The wear rate of diamond wire saw plays a vital role in the performance of sawing process. Predicting the sawing performance is very important in the production’s cost estimation and planning of the dimension stone quarries. In this research, an adaptive neuro-fuzzy inference system (ANFIS) is applied to estimate the wear rate of diamond wire saw under uncertain processes; hence, indirect prediction in ANFIS is carried out using subtractive clustering method (SCM) and fuzzy c-means clustering method based on four effective rock properties, such as Shore hardness, Schimazek’s F-abrasivity, uniaxial compressive strength and Young modulus. For this purpose, 38 rock samples were selected to test the proposed model from Turkey quarries. The results of indirect prediction indicated that the best performed model was related to ANFIS-SCM with highly acceptable degrees of accuracy 0.998 and 0.59 for R2 of the train and test data sets, respectively. In addition, group method of data handling type of neural network is used to assess the factors influencing the wear rate of the diamond wire saw. A sensitivity analysis was performed on the laboratory test results of studied rocks using three methods. In comparison to the existing models, the estimated results showed that a satisfactory performance could be obtained using the proposed ANFIS-subtractive clustering method.

Quantitative characterization of shales within tidally influenced fluvial valley fill deposits of the Ferron Sandstone, eastern Utah: Implications for hydrocarbon exploration

This study evaluates the proportion, length, and effective properties of thin (0.003 - 0.7 m [0.01 – 2.3 ft.]) shale beds and drapes in tidally-influenced channels within a compound valley fill with a focus on estimating geologically-based effective rock properties. The Cretaceous Ferron Sandstone is an outcrop analog for fluvial-tidal systems with primary reservoirs being deposited as tidally-influenced valley filling point bars. The study outcrops expose three valley systems in Neilson Wash of Utah. Light detection and ranging derived digital outcrop models have been used to characterize shale length, width, thickness and frequency of each valley fill succession. Long, uncommon, and anisotropic shales in Valley-1 (V1) were deposited in a braided setting with little tidal influence. In contrast, shales in Valley-2 (V2) were abundant, short, common, and equidimensional suggesting deposition by more tidally-influenced meandering rivers. Short, frequent, and equidimensional shales in Valley-3 (V3) were deposited in single-thread meandering rivers with less tidal influence. A sandstone-shale model was utilized to estimate the effects of shales on vertical to horizontal permeability ratio (kv/kh). The unique character of each depositional unit was reflected in resultant kv/kh distributions. The valley fill deposits, V1, V2, and V3 had an average kv/kh ratio of 0.11, 0.09 and 0.17, respectively. More tidally-influenced reservoirs such as the studied V2 had short, but frequent shales which resulted in low kv/kh estimates. Estimates of kv/kh for valleys that predominantly contained fluvial point bar deposits with lesser tidal influence (V1 and V3) were higher. The results of this study highlight the link between shale heterogeneity, reservoir architecture, and inferred flow parameters.

Characterization of Basement Fracture Reservoir In Field ‘X’, South Sumatera Basin, Based On The Analysis of Core And FMI Log

Basement reservoir is a reservoir that is located in the basement rock, comprised of either igneous rock or metamorphic rock that has secondary porosity, resulting in its capability to store oil and gas. The research was conducted at field 'X' that is located at South Sumatra basin and it is a part of Jambi Sub-Basin. The study was focused on discussing hydrocarbon potential in Fields 'X', particularly at the basement metamorphic rock. The study was conducted at two wells in the field. The secondary porosity system of the basement is fracture porosity. Fracture analysis as secondary porosity system was performed on two wells, HA-1 and HA-2, by using FMI log interpretation. Based on the analysis of fracture on HA-1 well, the trend of fracture system is Northeast - Southwest (NE-SW) with a fracture porosity of 1.49%. On a different note, the trend of fracture system on HA-2 wells is East Northeast - West Southwest (ENE-WSW) with a fracture porosity of 0.888%. The effect of rock properties itself has little influence on the number of fractures as opposed to the effect of surrounding tectonic forces. The fractures are controlled by geological structures following Jambi pattern that has an orientation of Northeast - Southwest (NE-SW). Although the fracture porosity is relatively small, it is enough to storing hydrocarbons in economical quantity.

A multi-stage triaxial testing procedure for low permeable geomaterials applied to Opalinus Clay

In many engineering applications, it is important to determine both effective rock properties and the rock behavior which are representative for the problem's in situ conditions. For this purpose, rock samples are usually extracted from the ground and brought to the laboratory to perform laboratory experiments such as consolidated undrained (CU) triaxial tests. For low permeable geomaterials such as clay shales, core extraction, handling, storage, and specimen preparation can lead to a reduction in the degree of saturation and the effective stress state in the specimen prior to testing remains uncertain. Related changes in structure and the effect of capillary pressure can alter the properties of the specimen and affect the reliability of the test results. A careful testing procedure including back-saturation, consolidation and adequate shearing of the specimen, however, can overcome these issues. Although substantial effort has been devoted during the past decades to the establishment of a testing procedure for low permeable geomaterials, no consistent protocol can be found. With a special focus on CU tests on Opalinus Clay, this study gives a review of the theoretical concepts necessary for planning and validating the results during the individual testing stages (saturation, consolidation, and shearing). The discussed tests protocol is further applied to a series of specimens of Opalinus Clay to illustrate its applicability and highlight the key aspects.

Effect of Rock Properties on ROP Modeling Using Statistical and Intelligent Methods: A Case Study of an Oil Well in Southwest of Iran

Abstract Rate of penetration (ROP) is one of the key indicators of drilling operation performance. The estimation of ROP in drilling engineering is very important in terms of more accurate assessment of drilling time which affects operation costs. Hence, estimation of a ROP model using operational and environmental parameters is crucial. For this purpose, firstly physical and mechanical properties of rock were derived from well logs. Correlation between the pair data were determined to find influential parameters on ROP. A new ROP model has been developed in one of the Azadegan oil field wells in southwest of Iran. The model has been simulated using Multiple Nonlinear Regression (MNR) and Artificial Neural Network (ANN). By adding the rock properties, the estimation of the models were precisely improved. The results of simulation using MNR and ANN methods showed correlation coefficients of 0.62 and 0.87, respectively. It was concluded that the performance of ANN model in ROP prediction is fairly better than MNR method.

Digital carbonate rock physics

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.