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

Hu Tingting, Pan Tuo, Chen Liang, Li Jing, Liu Yu

Acta Geophysica

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2024

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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.

2

A discrete variable based methodology for topology optimization considering spatially uneven manufacturing errors

Xia Meng, Li Jing

Archives of Electrical Engineering

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2023

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Vol. 72, nr 4

1121--1133

EN

Manufacturing errors (MEs) are unavoidable in product fabrication. The omnipresence of manufacturing errors (MEs) in product engineering necessitates the development of robust optimization methodologies. In this research, a novel approach based on the morphological operations and interval field (MOIF) theory is proposed to address MEs in the discrete-variable-based topology optimization procedures. On the basis of a methodology for deterministic topology optimization (TO) based on the Min-Cut, MOIF introduces morphological operations to generate geometrical variations, while the dimension of the structuring element is dynamically set by the interval field function’s output. The effectiveness of the proposed approach as a powerful tool for accounting for spatially uneven ME in the TOs has been demonstrated.

3

Modified friction stir clinching-brazing of brass to AA5083 aluminum alloy using Zn interlayer

Li Jing, Tang Fei, Paidar Moslem

Archives of Civil and Mechanical Engineering

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2021

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Vol. 21, no. 1

219--229

EN

The modified friction stir clinching (MFSC) of 5083 aluminum alloy to brass using pure Zn interlayer has been explored and elucidated for the first time. By that, the influence of the Zn interlayer thickness on the microstructure and the mechanical properties of the 5083/brass joint was investigated. The attained data have revealed that the intermetallic compound (IMC) layer thickness was mainly influenced by the Zn interlayer. The use of the Zn interlayer restrained the creation of brittle Al–Cu IMCs such as Al4Cu9 during the MFSC process and, in return, softer phases such as Cu4Zn, CuZn5, and CuZn were formed. It was also found that with increasing the thickness of the Zn interlayer from 50 to 100 µm, the thickness of the brazed zone increased and the tensile/shear strength of the spot welds significantly improved from 5250 to 8490 N (approximately 60% increment over the welded sample with 50-µm-thick Zn) which can be ascribed to supreme bonding and homogeneous brazing zone at the interface.

4

A practical pretreatment planning method of multiple puncturing for thermal ablation surgery

Li Jing, Xu Yuanqi, Shen Nanyan, Feng Lanyun, Ran Zhuang, Deng Zongqian

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 4

1469--1485

EN

Thermal ablation surgery serves as one of the main approaches to treat liver tumors. The pretreatment planning, which highly demands the experience and ability of the physician, plays a vital role in thermal ablation surgery. The planning of multiple puncturing is necessary for avoiding the possible interference, destroying the tumor thoroughly and minimizing the damage to healthy tissue. A GPU-independent pretreatment planning method is proposed based on multi-objective optimization, which takes the most comprehensive constraints into consideration. An adaptive decision method of closing kernel size based on Jenks Natural Breaks is utilized to describe the final feasible region more accurately. It should be noted that the reasonable procedure of solving the feasible region and the use of KD tree based high dimensional search approach are used to enhance the computational efficiency. Seven constraints are handled within 7 s without GPU acceleration. The Pareto front points of nine puncturing tests are obtained in 5 s by using the NSGA-II algorithm. To evaluate the maximum difference and similarity between the planning results and the puncturing points recommended by the physician, Hausdorff distance and overlap rate are respectively developed, the Hausdorff distances are within 30 mm in seven out of nine tests and the average value of overlap rate is 73.0% for all the tests. The puncturing paths of high safety and clinical-practice compliance can be provided by the proposed method, based on which the pretreatment planning software developed can apply to the interns' training and ability evaluating for thermal ablation surgery.

5

A fully automatic computer-aided diagnosis system for hepatocellular carcinoma using convolutional neural networks

Li Jing, Wu Yurun, Shen Nanyan, Zhang Jiawen, Chen Enlong, Sun Jie, Deng Zongqian, Zhang Yuchen

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

238--248

EN

The cancer of liver, which is the leading cause of cancer death, is commonly diagnosed by comparing the changes of gray level of liver tissue in the different phases of the patient's CT images. To aid the doctor in reducing misdiagnosis or missed diagnosis, a fully automatic computer-aided diagnosis (CAD) system is proposed to diagnose hepatocellular carcinoma (HCC) using convolutional neural network (CNN) classifier. The automatic segmentation and classification are two core technologies of the proposed CAD system, which are both realized based on CNN. The segmentation of liver and tumor is implemented by a fully convolutional networks (FCN) based on a fine tuning VGG-16 model with two additional 'skip structures' using a weighted loss function which helps to solve the problem of inaccurate tumor segmentation caused by the inevitably unbalanced training data. HCC classification is implemented by a 9-layer CNN classifier, whose input is a 4-channel image data constructed by combining the segmentation result of FCN with the original CT image. A total of 165 venous phase CT images including 46 diffuse tumors, 43 nodular tumors, and 76 massive tumors are used to evaluate the performance of the proposed CAD system. The classification accuracy of CNN classifier for diffuse, nodular and massive tumors are 98.4%, 99.7% and 98.7% respectively, which are significantly improved in contrast with the traditional feature-based ANN and SVM classifiers. The proposed CAD system, which is unaffected by the difference of preprocessing method and feature type, is proved satisfactory and feasible by the test set.

6

Effects of Al doping on the morphology of ZnO nanowires and the properties of dye-sensitized solar cells

Wang Yanxiang, Li Jing, Sun Jing

Materiały Ceramiczne

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2019

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T. 71, nr 4

334--340

EN

ZnO nanowire photoanodes were prepared by a simple chemical bath method. The influence of doping Al into ZnO seed layer, dipping times of seed layers and the growth times of ZnO nanowires on the morphology of ZnO nanowires and photoelectric performance of dye-sensitized solar cells were mainly investigated. The results showed that when the ZnO seed layer was doped with 9 at.% Al, both dipping times of seed layer solution and growth times of films were 9; ZnO photoanodes with nanowires and nanosheets composite structure were obtained. The length of the ZnO nanowires reached about 15μm. The power conversion efficiency, open circuit voltage, short-circuit photocurrent density and fill factor of the corresponding cells were 2.36%, 0.66 V, 5.28 mA•cm-2, and 0.62, respectively.

PL

Fotoanody zbudowane z nanodrutów ZnO zostały przygotowane prostą metodą kąpieli chemicznej. Badano głównie wpływ domieszkowania Al warstwy zarodkowej ZnO, czasu zanurzenia warstw zarodkowych i czasu wzrostu nanodrutów ZnO na morfologię nanodrutów ZnO i parametry fotoelektryczne ogniw słonecznych uświatłoczulonych barwnikiem. Wyniki pokazały, że gdy warstwa zaszczepiająca ZnO była domieszkowana 9% at. Al, zarówno czasy zanurzania w roztworze zaszczepiającym warstwę, jak i czasy wzrostu filmów wynosiły 9; otrzymano wówczas fotoanody ZnO z nanodrutami i strukturą kompozytową nanoskładników. Długość nanodrutów ZnO osiągnęła około 15 μm. Efektywność konwersji mocy, napięcie w obwodzie otwartym, gęstość zwarciowa fotoprądu i współczynnik wypełnienia odpowiednich ogniw wynosiły odpowiednio 2,36%, 0,66 V, 5,28 mA•cm-2 i 0,62.