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Shale gas is an extremely important unconventional oil and gas resource, and its efficient development can effectively alleviate the current tense energy situation. However, shale gas reservoirs often have extremely poor permeability, and reservoir transformation has become a key technology for achieving their efficient development. However, the commonly used hydraulic fracturing technology is difficult to achieve its target production capacity, and other engineering technologies related to reservoir transformation urgently need to be proposed and attempted. The synergistic operation of oxidation dissolution and acid fracturing may provide new ideas for the effective transformation of shale reservoirs. To this end, a comparative analysis was conducted on the synergistic effects of oxidation dissolution and acid fracturing operations in improving shale gas production capacity. The research results indicate that the dissolution effect of oxidants is more effective than acid solution in the transformation process of shale reservoirs. The use of acid only widens the crack width from the initial 4.4 mm to the final 5.1 mm. However, the use of oxidants will result in the final width of hydraulic fractures reaching 8.3 mm. Meanwhile, the effects of acid concentration and oxidant concentration on hydraulic fracture conductivity and shale gas production capacity were investigated. The results indicate that increasing the acid concentration below the low concentration range can significantly enhance the fracture conductivity, thereby promoting the production capacity of shale gas. However, within a higher concentration range, its effect on shale gas production is significantly limited. It is recommended to set the acid concentration design value at 0.5 wt% during the acidizing and fracturing reservoir transformation process of the shale gas reservoir in Changning block. In addition, an increase in the concentration of oxidants can widen the width of fractures and increase permeability, thereby promoting the migration and extraction of shale gas. To avoid the increase in development costs caused by high oxidant concentration in the working fluid, it is recommended to design the oxidant concentration at 3 wt%. [ABSTRACT FROM AUTHOR]

With the development of data collection and storage capabilities in recent decades, abundant data have been accumulated in geotechnical engineering fields, providing opportunities for the usage of machine learning approaches. Thus, a rising number of scholars are adopting machine learning techniques to settle geotechnical issues. In this paper, the application of three popular machine learning algorithms, support vector machine (SVM), artificial neural network (ANN), and decision tree (DT), as well as other representative algorithms in geotechnical engineering, is reviewed. Meanwhile, the applicability of diverse machine learning algorithms in settling specific geotechnical engineering issues is compared. The main findings are as follows: ANN, SVM, and DT have been widely adopted to solve a variety of geotechnical engineering issues, such as the classification of soil and rock types, predicting the properties of geotechnical materials, etc. Based on the collected relevant research, the performance of random forest (RF) in sorting soil types and assessing landslide susceptibility is satisfying; SVM has high precision in classifying rock types and forecasting rock deformation; and backpropagation ANNs and Hopfield ANNs are recommended to forecast rock compressive strength and soil settlement, respectively. [ABSTRACT FROM AUTHOR]

The peak shear strength of clayey soil-geomembrane interfaces is a vital parameter for the design of relevant engineering infrastructure. However, due to the large number of influence factors and the complex action mechanism, accurate prediction of the peak shear strength for clayey soil-geomembrane interfaces is always a challenge. In this paper, a machine learning model was established by combining Mind Evolutionary Algorithm (MEA) and the ensemble algorithm of Adaptive Boosting Algorithm (ADA)-Back Propagation Artificial Neural Network (BPANN) to predict the peak shear strength of clayey soil-geomembrane interfaces based on the results of 623 laboratory interface direct shear experiments. By comparing with the conventional machine learning algorithms, including Particle Swarm Optimisation Algorithm (PSO) and Genetic Algorithm (GA) tuned ADA-BPANN, MEA tuned Support Vector Machine (SVM) and Random Forest (RF), the superior performance of MEA tuned ADA-BPANN has been validated, with higher predicting precision, shorter training time, and the avoidance of local optimum and overfitting. By adopting the proposed novel model, sensitivity analysis was carried out, which indicates that normal pressure has the largest influence on the peak shear strength, followed by geomembrane roughness. Furthermore, an analytical equation was proposed to assess the peak shear strength that allows the usage of machine learning skills for the practitioners with limited machine learning knowledge. The present research highlights the potential of the MEA tuned ADA-BPANN model as a useful tool to assist in preciously estimating the peak shear strength of clayey soil-geomembrane interfaces, which can provide benefits for the design of relevant engineering applications. • The ensemble artificial intelligence algorithms in predicting the peak shear strength of interfaces is compared. • An analytical equation for estimating the peak shear strength is proposed. • Physical experiments are conducted to validate the effectiveness of the proposed analytical equation. [ABSTRACT FROM AUTHOR]

• A method for preparing cement mortar with diverse numbers of internal cracks was proposed. • Permeability and porosity for the samples under diverse stress states were measured. • The stress-dependent permeability and porosity for the prepared samples was analysed. In this paper, gas permeability and porosity for the prepared cement mortar samples with diverse numbers of internal cracks under diverse pore pressure during confining pressure loading and unloading was measured. According to the outcomes of experiments, the following findings were obtained: Klinkenberg correction is appliable to the modification on gas permeability of cement mortar samples containing different number of internal cracks to obtain the intrinsic permeability, with the quadratic equation (Coefficient of Determination R2 is above than 0.92) having a better performance than that of Klinkenberg equation; Owing to the increase in the equivalent pore radius of seepage passages, Klinkenberg Effect of the cement mortar samples reduces when the number of internal cracks rises. When the number of internal cracks rises from 0 to 12, the slippage factor decreases over 90 %; When the number of internal cracks is high, the same changing extent in the number of internal cracks can lead to higher influence on the intrinsic permeability than that when the number of internal cracks is low. The variation magnitude of intrinsic permeability when the number of internal cracks increases from 6 to 12 is around 3–10 times higher than that when the number goes up from 0 to 6; When confining pressure increases, the sensitivity of intrinsic permeability to the changes in confining pressure reduces. The variation magnitude of intrinsic permeability when confining pressure is loaded from 0 MPa to 25 MPa is 5–10 times higher than that when confining pressure is loaded from 25 MPa to 45 MPa; Owing to the permanent deformation of pores and cracks, under the same confining pressure, the intrinsic permeability and porosity during the unloading stage are less than those during the loading stage, respectively; The sub-cubic law (R2 is above than0.90) is able to describe gas seepage in cement mortar specimens with different number of internal cracks more precisely compared to the cubic law. [ABSTRACT FROM AUTHOR]

Viscoelasticity is a key mechanical feature of shale that can influence a variety of oil and gas engineering issues. To describe the time-dependent creep behavior of shale at nano-scale, the nanoindentation technique was used. Moreover, Maxwell and Zener fractional derivative models were applied for the fitting data and the applicability and the accuracy of these fractional viscoelastic models are discussed. Moreover, the creep difference on samples with different mineral compositions may be compared using Energy Dispersive Spectra (EDS) mapping techniques. The experimental results indicate that there is a better match between fitting values and measured values versus time by fractional models compared to traditional viscoelastic models. Furthermore, fitting parameter changes with different holding times were investigated. The results demonstrate that the fractional Zener model yield the highest RMSE and R 2, indicating the optimal fitting results. The fractional Maxwell model likewise provides an excellent fit to the data and takes the least amount of time to compute, however, the creep response is infinite. In addition, both elastic parameters and fractional derivatives decrease while viscous parameters increase along with a reduction of Young's modulus and hardness, indicating microdamage accumulation induced by the viscoelastic behavior of shale. Comparing the results of clay-rich and quartz-rich samples showed reduced stiff shale creep, but creep-induced deformation led to more obvious deformation and mechanical strength reduction. This study not only investigates the use of nanoindentation in the creep analysis of composite shale but also shows that fractional models can be used to characterize shale viscoelasticity. • Fractional Maxwell model and Zener model are used to creep behavior of shale. • Fractional models yield the highest accuracy. • The fractional Zener model is more recommended for time-dependent behavior description of shale. • Stiff shale creep less but creep induce deformation and mechanical strength reduction. [ABSTRACT FROM AUTHOR]

This study investigates the effect of chlorine corrosion and flow scour on the lateral bearing capacity of piles. A chloride diffusion model was established to obtain the initial corrosion time of reinforcement based on Fick's second law. The degradation of stiffness after corrosion is represented by a reduction coefficient. The finite difference method is used to solve the deflection differential equation of laterally loaded piles. The maximum scouring depth of piles in cohesive soil and the variation of scouring depth with time are calculated by empirical model. The calculated results from the analytical solution revealed that the pile stiffness decreases with the exposure time. As the time increase, the lateral displacement and shear force decrease on the other hand the bending moment increases. The increase of flow velocity and pile diameter results in the increase of the maximum scour depth around the pile. The bending moment, shear force, and lateral displacement of piles after scour increase significantly compared to the lateral bearing performance of piles before scour. • Chloride diffusion model is established to obtain the initial corrosion time. • Degradation of pile stiffness is established by introducing the stiffness reduction coefficient. • Maximum scouring depth is calculated by empirical model. • Lateral bearing capacity of piles combined with corrosion and scour is investigated. [ABSTRACT FROM AUTHOR]

• The corrosion initiation time and reinforcement corrosion depth of CFRP composite piles are predicted. • The degradation model of bending stiffness of CFRP composite piles is established. • The flexural stiffness reduction factor of CFRP composite piles is obtained by conducting the model pile bending tests. • The horizontal bearing characteristics of CFRP composite piles in marine environments is analyzed. In this paper, the durability life and horizontal bearing characteristics of carbon fiber reinforced polymers (CFRP) composite piles in marine environments are studied. The durability life of CFRP composite piles is divided into the initial corrosion stage of reinforcement and the crack propagation stage of concrete protection layer. The chloride diffusion model and Monte Carlo simulation method are used to predict the initial corrosion time of CFRP composite piles. Based on the thick-walled cylinder theory, the critical corrosion depth of the reinforced steel corresponding to the cracking of concrete protective layer is deduced. The durability life prediction model of crack propagation stage is established. The flexural stiffness reduction factor of CFRP composite piles with different replacement ratios is obtained by conducting the model pile bending tests. The attenuation law of bending stiffness and horizontal bearing characteristics of CFRP composite piles in marine environments are analyzed. The results show that the higher the replacement ratio of CFRP bar, the slower the reduction rate of flexural stiffness of CFRP composite pile is. Under the same buried depth, the pile bending moment and shear force of CFRP composite piles decrease with the increase of CFRP reinforcement replacement ratio. The horizontal displacement of CFRP composite piles increases with the increase of CFRP reinforcement replacement ratio. [ABSTRACT FROM AUTHOR]