Wyniki wyszukiwania - Biblioteka Nauki

1

Amount and Distribution of Micro-Defects in Solidified 2219 Al Alloy Ingots: a Metallographic Investigation

100%

Liu Y. , Huang Y. , Xiao Z.

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tom Vol. 64, iss. 4

1569--1575

EN

Micro-defects detection in solidified castings of aluminum alloy has always been a hot topic, and the method employed is mainly depends upon the size and shape of the specimens. In present paper, the amount and distribution characters of micro-defects in a series of 2219 aluminum alloy ingot, with diameters of φ1380 mm, φ1250 mm, φ1000 mm, φ850 mm and φ630 mm, prepared by direct chill casting were investigated by means of metallographic, respectively. Samples were cut along the radius directionfrom slices in the steady casting stage. The result reveals that typical micro-defects are consist of inclusions, porosity and shrinkage under optical microscope, and the total amount of micro-defect per unit area in an ingot slightly decreased with the increase of its diameter. Meanwhile, defects were classified into 2 types according to its size, the results suggesting that defects greater than 40 μm account for the largest proportion among the counted two kinds of defects. Moreover, the distribution of defects greater than 40 μm along the radial direction was detected, its amount increases as its distance from the side, indicating that the micro-defects greater than 40 μm distributed the most in the center zone of ingots and the larger the ingot diameter, the more obvious the tendency was.

2

Multichannel seismic impedance inversion driven by logging–seismic data

100%

Li X. , Wang Y. , Liu Y. , Cai H.

Acta Geophysica

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2021

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tom Vol. 69, no. 6

2261--2274

EN

The prior information constrained impedance inversion is an important tool to improve the inversion effect. With the traditional constrained prior information extracted from logging data by the analytic formula, it is difficult to accurately describe the information of a complex reservoir. In addition, the traditional inversion method is trace-by-trace, which ignores the lateral information contained in seismic data. This paper presents a multichannel seismic impedance inversion method combining logging and seismic. In this method, the dictionary learning method is used to extract the vertical prior information of the formation from the logging data. At the same time, we can learn the dip information from seismic data cube. Under the framework of multichannel inversion, regularization and sparse representation technology are used to simultaneously add the vertical and the transverse distribution prior information into the inversion process. Block coordinate descent method is used to solve the multichannel inversion problem, making the seismic inversion efficient. This method excavates the spatial prior information in a data-driven way and is used for constrained inversion, avoiding the false prior cognition caused by manual interpretation. Through the model and field data testing, it is verified that this method is effective.

3

Pore structure characterization and deliverability prediction of fractured tight glutenite reservoir based on geophysical well logging

88%

Hu T. , Pan T. , Chen L. , Li J. , Liu Y.

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tom Vol. 72, no. 1

273--286

EN

Tight glutenite reservoirs characterization and effective hydrocarbon-bearing formation identification faced great challenge due to ultra-low porosity, ultra-low permeability and complicated pore structure. Fracturing fracture-building technique always needed to obtain deliverability because of poor natural productive capacity. Pore structure characterization and friability prediction were essential in improving such type of reservoir evaluation. In this study, fractured tight glutenite reservoirs in Permian Jiamuhe Formation that located in northwest margin of Junggar Basin, northwest China, were chosen as an example, and 25 typical core samples were drilled and simultaneously applied for mercury injection capillary pressure (MICP), nuclear magnetic resonance (NMR) and whole-rock mineral X-ray diffraction experiments. A novel method of synthetizing pseudo-pore-throat radius (Rc) distribution from porosity frequency spectra was established to characterize fractured formation pore structure. Quartz and calcite were considered as the fragile mineral, and rock mineral component ratio method was used to predict brittleness index. Meanwhile, the statistical model raised by Jin et al. (SPE J 20:518-526, 2015) was used to predict two types of fracture toughness. And then, brittleness index and fracture toughness were combined to characterize tight glutenite reservoirs friability. Combining with maximal pore-throat radius (Rmax, reflected rock pore structure) and friability, our target formations were classified into four clusters. In addition, relationships among pore structure, friability and daily hydrocarbon production per meter (DI) were analyzed, and a model to predict DI from welllogging data was established. Comparison of predicted DI with the extracted results from drill stem test (DST) data illustrated the reliability of our raised models. This would be valuable in determining optimal hydrocarbon production intervals and formulating reasonable developed plans.

4

Reliability assessment of wind turbine generators by fuzzy universal generating function

75%

Huang T. , Xiahou T. , Li Y.-F. , Qian H.-M. , Liu Y. , Huang H.-Z.

Eksploatacja i Niezawodność

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2021

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tom Vol. 23, no. 2

308--314

EN

Wind power has been widely used in the past decade because of its safety and cleanness. Double fed induction generator (DFIG), as one of the most popular wind turbine generators, suffers from degradation. Therefore, reliability assessment for this type of generator is of great significance. The DFIG can be characterized as a multi-state system (MSS) whose components have more than two states. However, due to the limited data and/or vague judgments from experts, it is difficult to obtain the accurate values of the states and thus it inevitably contains epistemic uncertainty. In this paper, the fuzzy universal generating function (FUGF) method is utilized to conduct the reliability assessment of the DFIG by describing the states using fuzzy numbers. First, the fuzzy states of the DFIG system’s components are defined and the entire system state is calculated based the system structure function. Second, all components’ states are determined as triangular fuzzy numbers (TFN) according to experts’ experiences. Finally, the reliability assessment of the DFIG based on the FUGF is conducted.

5

Construction of pore network model based on computational geometry

75%

Niu W. , Zhao Y. , Song X. , Yu Z. , Liu Y. , Gong Y.

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2023

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tom Vol. 71, no. 5

2197--2216

EN

The digital core and pore network model (PNM) are the basis of studying porous media. At present, the voxel-based maximal ball (MB) method has been widely used in the construction of PNM. However, due to the dependence on discrete data and the fuzziness of size definition, the PNM by using this method may not be accurate. The construction of PNM is essentially a geometric problem. Therefore, a computational geometry method was proposed in this paper to construct the PNM. A grid-based core surface model was constructed by using the moving cubes (MC) algorithm, the maximal inscribed ball of the grid space was extracted by using the computational geometry method, and a PNM was built by judging 12 types of dependency relationships of the master and servant spheres in the inscribed ball. Finally, combined with Berea sandstone, the physical parameters of cores obtained by the proposed method and the MB method were compared. The throat length results show that the proposed algorithm has improved the defect of small throat length when the MB method is used to partition core pore space. Meanwhile, the results of other parameters tend to be consistent, which proves the reliability of the proposed algorithm. Besides, by comparing the seepage simulation results of the two methods with the physical experiments, it was proved that the permeability calculated by the method in this paper is closer to the measured value of the physical experiment than that by the MB method.