Nanoindentation-Based Three-Parameter Fracability Evaluation Method for Continental Shales

Shale fracturing evaluation is of great significance to the development of shale oil and gas resources, but the commonly used shale evaluation methods (e.g., the method using the brittleness index based on mineral composition or elastic parameters) have certain limitations. Fractures and beddings affecting fracturing are not considered in these methods. Therefore, it is necessary to develop a new method to evaluate fracturing more comprehensively. The samples used in this research were taken from four typical continental shale basins of China, namely the Bohai Bay Basin, the Ordos Basin, the Songliao Basin, and the Junggar Basin. From a microscopic point of view, a three-parameter evaluation method involving multi-dimensional factors has been developed based on the nanoindentation method. Then, the fracturing coefficient K2 is obtained by combining the ratio β of the fracture indentation to the total indentation and the uneven coefficient m. After that, the fracability coefficient K3 is the ratio of the elastic modulus parallel to bedding to that perpendicular to bedding. Finally, the correlation between fracability coefficients K1, K2, and K3 is used to evaluate the overall fracturing performance of shale. The results of this evaluation method are in good agreement with the actual fracturing performance. It can be concluded that this method is highly reliable and practical and well worthy of promoted applications.

Development of mobile aircraft control system model with additive technologies

The article describes the parameter evaluation of mobile spacecraft control systems and identifies their main advantages in comparison with stationary assets. The model and the mobile spacecraft control system mock-up using additive technologies were developed with existing methods for prototyping complex technical systems. This model performs experimental operations of the prototype of the mobile control system, accompanies the spacecraft in the area of its radio visibility, simulates the implementation of technological cycles of spacecraft control, evaluates the parameters of the target equipment, analyzes the characteristics of the antenna system and the layout, conducts experiments and eliminates abnormal situations. It also optimizes the spacecraft testing based on the use of artificial intelligence techniques.

Modelling and Simulation of Transformer Tests under Dynamic Testing

Large power transformers are the most important equipment for the power grid. Their reliability not only affects the availability of electricity in the supply area, but also affects the economic functioning of an energy supplier. The main objective of this work of the development of the transformer testing simulation model on the MATLAB/SIMULINK environment. The designing aspect shall comprise the generator-based and grid-based testing of the transformer and associated results on the same in the SIMULINK. And the methodology shall study the impacts on the grid-connected devices due to testing of the transformers in the grid-based method. The study concluded that there is effectively no effect on the parameter evaluation of OC and SC tests by either source. However, the practical conditions would require grid-based testing that allows a greater range of transformers of various ratings to be tested with high current capability. The impact of fault on the grid can be easily evaluated through location of fault, duration of fault, and dip if occurred. The testing should follow proper timing to avoid such disturbances on the grid. This leads to the rescheduling of the other approved outages or Short Circuit tests.

Research on Damage and Deterioration of Fiber Concrete under Acid Rain Environment Based on GM(1,1)-Markov

With steel fiber and basalt fiber volume dosing serving as variation parameters, a total of 200 d cycles of acid rain corrosion cycle tests were conducted on fiber concrete in this study. We selected three durability evaluation parameters to assess the degree of damage deterioration on fiber concrete, used scanning electron microscopy, mercury intrusion porosimetry, and a dimensional microhardness meter to analyze the concrete micromorphology, and established a GM(1,1)-Markov model for life prediction of its durability. Results reveal that the acid rain environment is the most sensitive to the influence of the relative dynamic elastic modulus evaluation parameter, and concrete has specimens that show failure damage under this parameter evaluation. Incorporation of fibers can reduce the amount of corrosion products inside the concrete, decrease the proportion of harmful pores, optimize the mean pore-size, and significantly improve the resistance to acid rain attack. Concrete with 2% steel fiber and 0.1% basalt fiber by volume has the least change in durability damage, and the predicted service life by GM(1,1)-Markov model is 322 d.

Case Report: Orchiopexy in Two Poodle Dogs and Its Effect on Their Sperm Quality Parameters

Cryptorchidism is a common congenital abnormality encountered in veterinary clinics. The treatment of choice for this condition is a surgical procedure named orchiectomy or orchidectomy, where the retained testicle is removed. Surgical placement and fixation of the cryptorchid testicle into the scrotum, referred to as orchiopexy, is used in humans. However, due to the hereditary nature of cryptorchidism in dogs, this treatment option has not been proposed in veterinary clinics. Two adult Poodle dogs were referred to our research facility for a sperm parameter evaluation check. The two dogs were unilateral cryptorchid dogs treated with orchiopexy before the age of 6 months. Their sperm kinematics and morphology were within normal ranges, and their libido and testicles sizes were normal. Treatment of unilateral cryptorchidism by orchiopexy in dogs before the age of 6 months successfully restored spermatogenic function and sperm quality-related parameters. However, due to the nature of this condition, orchiectomy remains the treatment of choice.

Parameter Evaluations for Vertical Wells with Hydraulic Fracture Using Well-Testing and Deep Learning Method

The reliability of well-testing interpretation largely depends on the experience of reservoir engineers, which make the issue of non-unique solution serious and increase its application threshold. Virtually, deep learning assistive techniques are good strategies in well-testing interpretation. Although some work has been done based on automatic interpretation techniques, there is still a lack of an automatic interpretation model with wide applicability and fast interpretation on parameter evaluation of vertically fractured well. To improve this situation and make the well-testing interpretation easier to apply, this paper uses deep learning methods to build an automatic interpretation model of well-testing data for vertically fractured well. The model can automatically identify the corresponding parameters. The results in the validation set show that the median relative error of the curve parameter inversion is less than 10%. In addition, the accuracy of parameter prediction can be improved by increasing the weight of some important parameters in deep learning model training, such as permeability and fracture half-length. Finally, the automatic interpretation model is tested on a field case. The test results prove that the model has high accuracy and interpretation speed.