Baoyi Zhang

Dr. Baoyi Zhang

Central South University, Changsha, China
orcid
Associate Professor and Doctoral Supervisor at Central South...

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 April 2021 in Water
Verified
Journal Article
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Umair KhanUmair Khan
Umair Khan
HFHaris Faheem
Haris Faheem
JZjiang zhengwen
jiang zhengwen
MWMuhammad Wajid
Muhammad Wajid
MYMuhammad Younas
Muhammad Younas
Baoyi ZhangBaoyi Zhang
Baoyi Zhang
The optimization of groundwater conditioning factors (GCFs), the evaluation of groundwater potential (GWpot), the hydrogeological characterization of aquifer geoelectrical properties and borehole lithological information are of great significance in the complex decision-making processes of groundwater resource management (GRM). In this study, the regional GWpot of the Karak watershed in Northern Pakistan was first evaluated by means of the multi-influence factors (MIFs) model of optimized GCFs through geoprocessing tools in geographical information system (GIS). The distribution of petrophysical properties indicated by the measured resistivity fluctuations was then generated to locally verify the GWpot, and to analyze the hydrogeological and geoelectrical characteristics of aquifers. According to the weighted overlay analysis of MIFs, GWpot map was zoned into low, medium, high and very high areas, covering 9.7% (72.3 km2), 52.4% (1307.7 km2), 31.3% (913.4 km2), and 6.6% (44.8 km2) of the study area. The GWpot accuracy sequentially depends on the classification criteria, the mean rating score, and the weights assigned to GCFs. The most influential factors are geology, lineament density, and land use/land cover followed by drainage density, slope, soil type, rainfall, elevation, and groundwater level fluctuations. The receiver operating characteristic (ROC) curve, the confusion matrix, and Kappa (K) analysis show satisfactory and consistent results and expected performances (the area under the curve value 68%, confusion matrix 68%, Kappa (K) analysis 65%). The electrical resistivity tomography (ERT) and vertical electrical sounding (VES) data interpretations reveals five regional hydrological layers (i.e., coarse gravel and sand, silty sand mixed lithology, clayey sand/fine sand, fine sand/gravel, and clayey basement). The preliminary interpretation of ERT results highlights the complexity of the hydrogeological strata and reveals that GWpot is structurally and proximately constrained in the clayey sand and silicate aquifers (sandstone), which is of significance for the determination of drilling sites, expansion of drinking water supply and irrigation in the future. Moreover, quantifying the spatial distribution of aquifer hydrogeological characteristics (such as reflection coefficient, isopach, and resistivity mapping) based on Olayinka’s basic standards, indirectly and locally verify the performance of the MIF model and ultimately determine new locations for groundwater exploitation. The combined methods of regional GWpot mapping and hydrogeological characterization, through the geospatial MIFs model and aquifer geoelectrical interpretation, respectively, facilitate decision-makers for sustainable GRM not only in the Karak watershed but also in other similar areas worldwide.

16 March 2022 in Minerals
Verified
Journal Article
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Baoyi ZhangBaoyi Zhang
Baoyi Zhang
YTYongqiang Tong
Yongqiang Tong
JDJiangfeng Du
Jiangfeng Du
SHShafqat Hussain
Shafqat Hussain
JZjiang zhengwen
jiang zhengwen
Umair KhanUmair Khan
Umair Khan
A complex structural geology generally leads to significant consequences for hydrocarbon reservoir exploration. Despite many existing wells in the Kadanwari field, Middle Indus Basin (MIB), Pakistan, the depositional environment of the early Cretaceous stratigraphic sequence is still poorly understood, and this has implications for regional geology as well as economic significance. To improve our understanding of the depositional environment of complex heterogeneous reservoirs and their associated 3D stratigraphic architecture, the spatial distribution of facies and properties, and the hydrocarbon prospects, a new methodology of three-dimensional structural modeling (3D SM) and joint geophysical characterization (JGC) is introduced in this research using 3D seismic and well logs data. 3D SM reveals that the field in question experienced multiple stages of complex deformation dominated by an NW to SW normal fault system, high relief horsts, and half-graben and graben structures. Moreover, 3D SM and fault system models (FSMs) show that the middle part of the sequence underwent greater deformation compared to the areas surrounding the major faults, with predominant one oriented S30°–45° E and N25°–35° W; with the azimuth at 148°–170° and 318°–345°; and with the minimum (28°), mean (62°), and maximum (90°) dip angles. The applied variance edge attribute better portrays the inconsistencies in the seismic data associated with faulting, validating seismic interpretation. The high amplitude and loss of frequency anomalies of the sweetness and root mean square (RMS) attributes indicate gas-saturated sand. In contrast, the relatively low-amplitude and high-frequency anomalies indicate sandy shale, shale, and pro-delta facies. The petrophysical modeling results show that the E sand interval exhibits high effective porosity (∅eff) and hydrocarbon saturation (Shc) compared to the G sand interval. The average petrophysical properties we identified, such as volume of shale (Vshale), average porosity (∅avg), ∅eff, water saturation (SW), and the Shc of the E sand interval, were 30.5%, 17.4%, 12.2%, 33.2% and, 70.01%, respectively. The findings of this study can help better understand the reservoir’s structural and stratigraphic characteristics, the spatial distribution of associated facies, and petrophysical properties for reliable reservoir characterization.

31 August 2021 in Frontiers of Earth Science
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Umair KhanUmair Khan
Umair Khan
Baoyi ZhangBaoyi Zhang
Baoyi Zhang
JDJiangfeng Du
Jiangfeng Du
ZJZhengwen Jiang
Zhengwen Jiang

1 May 2021 in Journal of Central South University
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Baoyi ZhangBaoyi Zhang
Baoyi Zhang
MLMan-Yi Li
Man-Yi Li
WLWei-Xia Li
Wei-Xia Li
ZJZheng-Wen Jiang
Zheng-Wen Jiang
Umair KhanUmair Khan
Umair Khan
FWFan-Yun Wang
Fan-Yun Wang

21 September 2018 in Natural Resources Research
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LWLifang Wang
Lifang Wang
XWXiangbin Wu
Xiangbin Wu
Baoyi ZhangBaoyi Zhang
Baoyi Zhang
XLXuefeng Li
Xuefeng Li
AHAnshuo Huang
Anshuo Huang
PDPengyao Dai
Pengyao Dai