Groundwater is the most important water resource, on which depends human geo-economic development and survival. Recent environmental changes and anthropogenic activities render groundwater severely vulnerable. Groundwater in Central Sindh, Pakistan, is facing a similar situation. Hydrogeochemical characteristics of the groundwater in the said region were investigated by analyzing 59 groundwater samples via agricultural and drinking indices, using various statistical methods and graphical approaches to identify factors affecting groundwater. Major reactions occurring in the groundwater system were quantified by hydrogeochemical modeling. A statistical summary reveals the abundance of cations is Na⁺ > Ca²⁺ > Mg²⁺ > K⁺, while the abundance of anions is HCO₃⁻ > Cl⁻ > SO₄². Groundwater chemistry is mainly of rock dominance. Correlation analysis and graphical relationships between ions reveal that ion exchange and rock weathering such as the dissolution of halite, albite, and dissolution of carbonate minerals are important rock–water interactions, governing the evolution of groundwater chemistry. Hydrochemical facies are predominantly of mixed CaMgCl and Na-Cl type, with few samples of Ca-HCO₃ type, which constitutes fresh recharged water. Based on the Water Quality Index (WQI), 28.82% samples were found to be unsuitable for drinking. A United States Salinity Laboratory (USSL) diagram, Wilcox diagram, and other agricultural indices indicate that majority of the groundwater samples fall within the acceptable range for irrigation purposes.

This paper presents an integrated approach of discrete fracture network modelling for a naturally fractured buried-hill carbonate reservoir in the Jingbei Oilfield by using a 3D seismic survey, conventional well logs, and core data. The ant tracking attribute, extracted from 3D seismic data, is used to detect the faults and large-scale fractures. Fracture density and dip angle are evaluated by observing drilling cores of seven wells. The fracture density distribution in spatiality was predicted in four steps; firstly, the ant tracking attribute was extracted as a geophysical log; then an artificial neural network model was built by relating the fracture density with logs, e.g., acoustic, gamma ray, compensated neutron, density, and ant tracking; then 3D distribution models of acoustic, gamma ray, compensated neutron and density were generated by using a Gaussian random function simulation; and, finally, the fracture density distribution in 3D was predicted by using the generated artificial neural network model. Then, different methods were used to build the discrete fracture network model for different types of fractures of which large-scale fractures were modelled deterministically and small-scale fractures were modelled stochastically. The results show that the workflow presented in this study is effective for building discrete fracture network models for naturally fractured reservoirs.

Hydrogeochemical processes and quality assessment for shallow groundwater are pivotal issues to be solved in many regions over the world due to the easy access of shallow groundwater. In this study, eighty-six water samples were collected from shallow aquifers of Chongqing, China, during July–September 2019. Multivariate statistical techniques, major ion ratios, and geochemical modeling were integrated to investigate hydrogeochemical characteristics and controlling factors. Afterwards, groundwater quality in spatial was classified by entropy-weighted water quality index and geographic information system (GIS) spatial analysis. Groundwater samples were alkaline and possessed high total dissolved solids (TDS) values. Two-group samples were distinguished as mix cations-HCO₃-SO₄ (group 1) and Ca-Mg-SO₄ (group 2) facies. Hydrogeochemical compositions of group 1 samples were dominated by silicate dissolution and ion exchange, while sulfate and calcite dissolution were the main factors influencing the hydrogeochemical characteristics of group 2. The overall quality of groundwater samples varied greatly from excellent quality to extremely poor quality. Group 1 samples were found with excellent and good quality and suitable for drinking purposes. Group 2 samples were all unsuitable for direct drinking purposes as the quality varied from medium to extremely poor, but were spatially limited. Groundwaters with relatively poor quality were due to dissolution of sulfate that were locally enriched in the aquifers. The new findings of this study are expected to provide the reference for future management and sustainable exploitation of groundwater in Chongqing.