In order to improve the corrosion resistance of zinc-rich epoxy coatings and reduce the amount of zinc used, first, graphene oxide (GO) was modified by sulfonated multiwall carbon nanotubes (SMWCNTs) to obtain the modified graphene oxide (SM-GO). The samples were characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) and Raman spectroscopy. Then, four kinds of coatings were prepared, namely pure zinc-rich coating (0-ZRC), graphene oxide-based zinc-rich coating (GO-ZRC), sulfonated multiwall carbon nanotube-based zinc-rich coating (SM-ZRC) and SM-GO-based zinc-rich coating (SG-ZRC). The corrosion resistance of the above coatings was studied by open circuit potential (OCP), electrochemical impedance spectroscopy (EIS), a salt spray test, 3D confocal microscope, and electron scanning electron microscope (SEM). The results indicate that GO is successfully non-covalently modified by SMWCNTs, of which the interlayer spacing increases and dispersion is improved. The order of the corrosion resistance is GO-ZRC > SG-ZRC > SM-ZRC > 0-ZRC. The addition of GO, SMWCNTs, and SM-GO increases the shielding effect and increases the electrical connection between Zn particles and metal substrates, which improves the corrosion resistance. However, SMWCNTs and SM-GO also strengthen the galvanic corrosion, which decreases the corrosion resistance to some extent.

The study of rock damage evolution is of great significance in the field of underground engineering. In this paper, the damage development of deep formation rock was quantitatively evaluated by acoustic emission (AE) test. The Young’s modulus of the test rock specimens under ideal intact state was obtained by assuming a linear relationship between the AE rate parameter and the damage variation based on the rate process theory. Through the multi-stage cyclic loading test, the damage parameters corresponding to the peak stress of the previous stage were calculated by using the tangent modulus at the initial moment. The results showed that there was abrupt transition stage of damage development with the linear increase of stress. The damage parameter curves of rock specimens during loading process were obtained by using the method of cumulative AE energy, and the development trend of the curves was analyzed simply by combining the concepts of crack initiation stress and crack damage stress. Comparing the two methods of obtaining damage parameters by using cyclic loading test and cumulative AE energy, the results of them were highly consistent except for some deviation in the initial and final stages.

The Kaiser effect in rock acoustic emission (AE) test is the most direct manifestation of rock memory function. This article focuses on the influence of different deformation stages and different historical stress conditions on stress memory function, and conducts AE testing of rock-like specimens. It explained the stress memory function in AE testing from the perspectives of crack propagation and damage accumulation. The crack initiation stress σ_ci and crack damage stress σ_cd of specimens were obtained based on the stress-strain curve method, and the different deformation stages were divided. The damage evolution coefficient [ ] was proposed to measure the size of the stable development range of damage based on the normalized crack initiation and crack damage stress. The historical stress in the elastic stage could be easily identified from the Kaiser effect during the reloading process, even if the time interval reached 120 hours. The Felicity effect appeared during the reloading process when the historical stress was in the stage of stable crack propagation, and the FR value showed a decreasing trend with the extension of the time interval between loading tests. The loading history in the elastic stage was a training for the AE stress memory function under complex historical stress conditions, which restored the Kaiser effect in the stage of stable crack propagation. The distribution of AE events and CT scanning results were also analyzed in the article, and the damage accumulation information characterized by both are basically consistent. The double Kaiser effect phenomenon appeared in the AE test under complex historical stress conditions, although the criterion for discriminating the AE signal at the Kaiser effect point corresponding to the lower stress remained to be further studied and verified.

Heavy oil thermal recovery wells and ultra-deep wells cementing have high requirements for high temperature compressive strength and density of oil well cement. In this paper, the experimental stud...

With hydraulic fracturing technology, manmade fractures can be generated around the shale-gas wells. After hydraulic fracturing at each stage, many wells in shale reservoirs have the "shut-in" process, which providing many precious data for parameter estimation. But, owing to intricate geological and engineering factors, the fractures in reservoirs are asymmetric and heterogeneous, which brings a great challenge for fracture estimation. To improve this situation, coupling the deep learning (DL) approach and field practices, we established a surrogate model for non-uniform fractures at one stage based on deep Bi-directional LSTM model. First, a well testing model containing three distinct flow regions is developed, namely (1) heterogeneous hydraulic fractures, (2) the inner region affected by hydraulic fracturing, and (3) the outer region without stimulation. Laplace transformation method are used for model solutions. Then, with the model solutions, a surrogate model based on deep bidirectional LSTM is built for improve computational efficiency. The results show that the model can effectively reduce the early prediction error of pressure derivative, and the average relative prediction error is 1.67%. Finally, model verification was shown by comparing with the results from traditional well testing model. The results show that the calculation speed of the surrogate model is three orders of magnitude higher than that of the well test model, which helps to efficiently evaluate the fracture parameter in complex fracture system generated by large-scale fracturing treatments in shale reservoirs.