In this study, three shale samples from the Wolfcamp Formation in Permian basin were selected and studied for creep behavior using two different methods at macro- and micro-scale: triaxial and ...nanoindentation creep tests. The triaxial creep test showed the effects of axial differential stress on the creep behavior of shale rocks including the strain and contact creep modulus. As the axial differential stress increased, the creep strain value presented an increasing trend. Additionally, based on the grid nanoindentation creep experiments, three different mechanical phases were recognized in these samples; Phase 1: soft mechanical phase, Phase 2: intermediate, and Phase 3: hard mechanical phase. Based on the micro-scale results, at the same creep time periods, phase 1 (clay + organic matter) was found to have a smaller contact creep modulus and larger creep strain value than Phase 3 (quartz). Comparing the results from these two scales of measurements, the contact creep modulus from the triaxial test and the homogenized contact creep modulus from nanoindentation experiments showed some discrepancies. Based on the samples in this study, the contact creep modulus from the triaxial test varied from 0.5 to 4 times the value of the nanoindentation test. The differences between the contact creep modulus from the nanoindentation and triaxial test could be due to the creep strain amplitude. Considering Sample 1 as an example, the creep strain amplitude under the nanoindentation is inferred to be 0.069 which is not equal to the creep strain amplitude from the triaxial test (0.0052 under differential stress of 30 MPa). Ultimately, the contact creep modulus from the nanoindentation can fluctuate based on the samples’ content, while the reason for this is still a question that needs further study. Overall, this study is a preliminary investigation to help us understand how nanomechanical data in complex geomaterials can relate to traditional triaxial data.
To evaluate pore structures of the Bakken Shale, which is one of the most important factors that affect petrophysical properties, high-pressure mercury intrusion was employed in this study. Pore ...structures such as pore-throat size, pore-throat ratio, and fractal attributes are investigated in this major shale play. Pore-throat size from 3.6 to 200 um is widely distributed in these shale samples. Accordingly, pore-throat size distributions demonstrate the multimodal behavior within the samples. The whole pore-throat network can be divided into four clusters: one set of large pores, two transitional/intermediate pore groups, and one set of smaller pores. The fractal analysis revealed that fractal dimensions decrease as the pore-throat size decreases. The multifractal analysis demonstrated that as the maturity of the shale samples increases, pore-throat size distributions would become more uniform and pore structures tend to become more homogeneous. The results are compared to our previous results obtained from nitrogen gas adsorption for further verifications of fractal behavior. Finally, although fractal analysis of mercury intrusion and nitrogen gas adsorption were comparable, the results of multifractal analysis from these two methods were not identical.
Fracture toughness is an important parameter in the hydraulic fracturing design, which is the major tool in the development of unconventional resources. Laboratory techniques for fracture toughness ...measurements usually require intact core samples and time-consuming sample preparation. The objective of this study is to compare fracture toughness values obtained by two less conventional methods: nanoindentation test and scratch test, which could facilitate the evaluation of this important parameter on smaller samples and at different scales. A set of 5 Antrim shale samples characterized by different mineral compositions is used to test this approach. For the scratch test, the fracture toughness and hardness are linearly correlated and show the same changing trend along the scratch length on all tested samples. For the nanoindentation test, the fracture toughness also increases with the increasing hardness. Most importantly, the results show that the fracture toughness values derived from these two methods are very similar, despite the difference in the scale of the measurements. This study is the first to compare fracture toughness between scratch and nanoindentation tests. Our results suggest that these two methods can be used to quickly evaluate fracture toughness from the shale core intervals containing both intact and nonintact parts.
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3D printing technology offers an innovative approach to manufacture rock samples with controlled properties. However, in this process, pore structure is one of the major concerns when printing ...similar specimens to natural rocks. The purpose of this study was to lay out an optimal post-processing of 3D-printed samples that can facilitate replicating natural rocks with similar microstructure characteristics. In this study, four cylindrical rocks were manufactured without designed porosity by 3D printing using gypsum powder as the main component. Various types of infiltrants (Colorbond
®
and Surehold
®
) and coating conditions (SmoothOn
®
and WBAE
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) were used after completing the printing process of binder jetting. Mercury injection porosimetry was then used to investigate their petrophysical properties including porosity and pore throat size distribution. Multifractal theory was applied to understand the heterogeneity of pore throat distribution within the 3D-printed samples on different pore size intervals. The results showed that 3D-printed rocks have a clustered and negative skewness of pore throat size distributions. The majority of pore sizes are micropores, while a small portion can be categorized under nanopore size category. Multifractal analysis results found a homogeneous distribution of micropores but a heterogeneous distribution of nanopores. Comparing four different samples, it was found that infiltrants could mainly affect the heterogeneous distribution of nanopores more than the micropores, whereas coating does not impact pore structure significantly. In comparison with pore multifractal characteristics of common types of natural rocks, 3D-printed rocks exhibited a higher heterogeneity of pore size distribution.
Evaluating pore structure of unconventional shale reservoirs enables us to determine their productivity, allowing for better operational decisions. Despite extensive studies in this field, ...considering the complexity of shale plays, pore structure analysis of such formations still requires novelties and further research. In this study, 10 samples from the Qingshankou Formation (from 5 wells) were analyzed with X-ray diffraction (XRD), programmed pyrolysis, N2 adsorption, and mercury intrusion capillary pressure (MICP). In the next step, several modern intelligent smart models including multilayer perceptron (MLP), radial basis function (RBF), generalized regression neural network (GRNN), cascaded forward neural network (CFNN), and least squares support vector machine (LSSVM), that were optimized by levenberg-marquardt (LM), Bayesian regularization (BR), genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), and differential evolution (DE) algorithms were employed, to estimate the volumes of N2 adsorbed and desorbed based on the mineralogy and geochemical properties of the samples. Results show that samples are mainly composed of clay (up to 42.3 wt%) and quartz (up to 34.6 wt%), low in total organic carbon (TOC) (up to 2.89%) and in the oil generation window. Complexity of smaller pores was found higher compared to medium and larger ones. In addition, deconvolution of N2 adsorption pore size distribution (PSD) curve revealed that samples are composed of up to three families in the range of macropore size and different families in mesopore size. We found that LSSVM with applicability to the entire input dataset, outperformed all other models in predicting the amount of nitrogen adsorption and desorption with an average absolute percent relative error (AAPRE) value of 1.94%. Ultimately, clay minerals and potash feldspar had the greatest effect on increasing and decreasing the amount of nitrogen adsorbed and desorbed, respectively. The Leverage technique's findings demonstrate that more than 97% of total data points in the LSSVM model are in the valid domain. This study proves that smart methods if used properly, would enable us to study a large group of samples independent from exhaustive, time consuming and expensive experimental methods.
In order to understand the pore structures of the Middle Jurassic Xishanyao Formation in the Junggar Basin, 11 shale samples from a single well were picked and were subjected to several analyses ...including mineralogy, (programmed) Rock-Eval pyrolysis for geochemical and N2 adsorption for pore structure analysis. The results showed that the mean value of total organic carbon (TOC) content of these samples is around 1.54% while Tmax varies between 429 to 443°C, indicating they are in the oil window. Mineral assemblages of the samples is mainly quartz and clay (illite, chlorite and kaolinite). Moreover, negative correlations between the K-feldspar/plagioclase and micro-mesopore volume was found, depicting that few of such pore sizes exist in these two abundant minerals. In contrast, micro, meso and macro pores all were detected in clay minerals. Particularly, the pores with radii of around 5.35 nm were abundant in clay minerals and there was not a robust relationship between the organic matter, surface area and pore volume. Finally, fractal analysis was performed to better delineate heterogenous characteristics of pore structures which showed that D2 (representing the larger pores) is greater than D1 (smaller pores). In addition, the differences between the fractal dimensions of the adsorption and desorption (D2d–D2a) branches to better interpret the hysteresis, was defined. The positive correlation between the (D2d–D2a) and the meso-macro pore volume, pointed out that the meso-macro condensation is the main reason for hysteresis that was observed in N2 adsorption experiments in the Xishanyao Shale samples.
Unconventional lacustrine shale formations are characterized by strong heterogeneity and intensive lithological variations in the vertical direction. Nevertheless, most studies focused merely on the ...organic-rich intervals due to the successful exploration and development of marine shale gas resources. This study systematically analyzed the overall pore system of the Triassic Chang 7 lacustrine shale formation in the Ordos Basin, China, using geochemical, petrological, mineralogical and petrophysical methods. In addition, the statistical analysis method of spearman rank correlation was employed for the intensive data analysis. The results showed that rock components and diagenetic processes have significantly different effects on the development of multi-lithologic pore systems in lacustrine shale formations. Organic-rich laminated shale (ORLS) and argillaceous siltstone (AS) show a bimodal, while the medium organic matter massive shale (MOMMS), fine sandstone A (FSA), and coarse sandstone B (CSB) exhibit unimodal pore size distribution. Organic matter negatively affects the pore volume and positively influences the pore throat, while clay minerals generally play a negative role except for ORLS. Quartz is conducive to the pore development of the reservoir except that it blocks some pore space in ORLS. Meanwhile, feldspar boosts the pore volume of all reservoirs and inhibits the pore throat of ORLS and MOMMS. Calcite and dolomite have negative effects on the entire pore system. Pyrite and siderite could facilitate pore throat preservation but inhibit pore space development. The diagenetic analysis shows that thermal maturation of organic matter and mineral dissolution play important roles in promoting pore development, while cementation and mechanical compaction have counteracting effects. The assemblage of ORLS and CSB acts as the most favorable reservoirs for lacustrine shale oil exploration under ideal conditions. The pore size distribution of the lacustrine shale oil reservoir with random multi-lithologies shows that macropores and mesopores are the main reservoir space. This study contributes to a better understanding of sweet spot prediction in the notoriously complicated lacustrine shale formation.
Rock permeability, defined as the ability of fluid to flow through the rocks, is one of the most important properties of rock. Many researchers have developed models to predict the permeability of ...rock from the porosity and pore size based on the mercury intrusion. However, these existing models still have some limitations. In this study, based on data regarding the fractal nature of the mercury intrusion of the rocks, we built a new model to predict the permeability of the rocks. In order to verify the new model, we extracted data regarding different kinds of samples from the literature and estimated the permeability using the new model. The results showed that the model could predict various types of rocks, such as tight sandstone, carbonates, and shale. The comparison of the calculated permeability using the new model is closer to the measured value than the value estimated from the existing models, indicating that the new model is better in predicting the permeability of rock samples.
In order to analyze and compare the differences in pore structures between shale gas and shale oil formations, a few samples from the Longmaxi and Bakken Formations were collected and studied using ...X-ray diffraction, LECO TOC measurement, gas adsorption and field-emission scanning electron microscope. The results show that samples from the Bakken Formation have a higher TOC than those from the Longmaxi Formation. The Longmaxi Formation has higher micropore volume and larger micropore surface area and exhibited a smaller average distribution of microsize pores compared to the Bakken Formation. Both formations have similar meso-macropore volume. The Longmaxi Formation has a much larger meso-macropore surface area, which is corresponding to a smaller average meso-macropore size. CO
2
adsorption data processing shows that the pore size of the majority of the micropores in the samples from the Longmaxi Formation is less than 1 nm, while the pore size of the most of the micropores in the samples from the Bakken Formation is larger than 1 nm. Both formations have the same number of pore clusters in the 2–20 nm range, but the Bakken Formation has two additional pore size groups with mean pore size diameters larger than 20 nm. Multifractal analysis of pore size distribution curves that was derived from gas adsorption indicates that the samples from the Longmaxi Formation have more significant micropore heterogeneity and less meso-macropore heterogeneity. Abundant micropores as well as meso-macropores exist in the organic matter in the Longmaxi Formation, while the organic matter of the Bakken Formation hosts mainly micropores.
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