A self-suspending ultra-low density proppant (UDP) was developed based on the polymerization of the unsaturated carbon double bond.
Hydraulic fracturing and acid fracturing are very effective stimulation technologies and are widely used in unconventional reservoir development. Fracture height, as an essential parameter to describe the geometric size of a fracture, is not only the input parameter of two-dimensional fracturing models but also the output parameter of three-dimensional fracturing models. Accurate prediction of fracture height growth can effectively avoid some risks. For example, petroleum reservoirs produce a large amount of formation water because wrong fracture height prediction leads to the connection between the oil or gas reservoir and the water layer. Although some fracture height prediction models were developed, few models considered the effects of the plastic zone, induced stress, and heterogeneous multilayer formation and its interaction. Therefore, considering the influence of many factors, an improved fracture-equilibrium-height model was developed in this study. The successive over-relaxation iteration method and the displacement discontinuity method were used to solve the model. We investigated the effects of the geological and engineering factors on fracture height growth by using the model, and some important conclusions were obtained. The higher the fracture height, the larger the plastic zone size, and the more obvious its influence on fracture height propagation. High overlying or underlying in situ stress and fracture toughness and low fluid density played a positive role in limiting the growth of the fracture height. Induced stress caused by fracture 1 could not only inhibit the height growth of fracture 2 but also promote its growth. The model established in this paper could be coupled to a fracturing simulator to provide a more reliable fracture height prediction.
Hydraulic fracturing is an important method to improve the oil and gas production in low and ultra-low permeability reservoirs. A remarkable progress has been made in the technology and materials. However, the existing conventional hydraulic fracturing technology faces problems, such as reservoir damage, equipment abrasion, low effective propped area, and early screen-out. Therefore, a novel self-propped fracturing fluid (SPFF) was proposed, which remains in the liquid-phase before entering the fracture, and forms solid proppant particles when stimulated by the reservoir temperature after entering the fracture (Chemical proppant, CP). In this paper, the micro-morphology of CP was studied by SEM, and the temperature of the CP-formed was measured by the CP formation experiments at room temperature and field conditions. Furthermore, the compressive strength, thermal stability, stability in formation fluid, acid and alkali, leak-off, core damage, and fracture conductivity of the developed SPFF were tested. The test results show that the leak-off volume and core damage level of SPFF were less than that of conventional fracturing fluid, thereby effectively reducing the damage to the reservoir permeability. The CP exhibited good performance in terms of compressive strength, thermal stability, stability in reservoir fluid and treatment fluid. Besides, the conductivity of the propped fracture was high. These advantages determine that CP can meet the field treatment requirements. The CP could enter any narrow fractures, and effectively solved the existing problems in the conventional fracturing technology by significantly improving the fracturing effect, especially the network fracturing effect in tight reservoir systems.
To a certain extent, automated fruit sorting systems reflect the degree of automated production in modern food industry, and boast a certain theoretical and application value. The previous studies mostly concentrate on the design of robot structure, and the control of robot motions. There is little report on the feature extraction of fruits in specific applications of fruit sorting. For this reason, this paper explores the target positioning and sorting strategy of fruit sorting robot based on image processing. Firstly, the authors constructed a visual sorting system for fruit sorting robot, and explained the way to recognize objects in three-dimensional (3D) scene and to reconstruct the spatial model based on sorting robot. Next, the maturity of the identified fruits was considered the prerequisite of dynamic sorting of fruit sorting robot. Finally, the program flow of the fruit sorting robot was given. The effectiveness of our strategy was verified through experiments.
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