The prediction and distribution of reservoir porosity and permeability are of paramount importance for the exploration and development of regional oil and gas resources. In order to optimize the prediction methods of porosity and permeability and better guide gas field development, it is necessary to identify the most effective approaches. Therefore, based on the extreme gradient boosting (XGBoost) algorithm, laboratory test data of the porosity and permeability of cores from the southern margin of the Ordos Basin were selected as the target labels, conventional logging curves were used as the input feature variables, and the mean absolute error (MAE) and the coefficient of determination (R²) were used as the evaluation indicators. Following the selection of the optimal feature variables and optimization of the hyper-parameters, an XGBoost porosity and permeability prediction model was established. Subsequently, the innovative application of homogeneous clustering (K-means) data preprocessing was applied to enhance the XGBoost model’s performance. The results show that logarithmically preprocessed (LOG(PERM)) target labels enhanced the performance of the XGBoost permeability prediction model, with an increase of 0.26 in its test set R². Furthermore, the application of K-means improved the performance of the XGBoost prediction model, with an increase of 0.15 in the R² of the model and a decrease of 0.017 in the MAE. Finally, the POR_0/POR_1 grouped porosity model was selected as the final predictive model for porosity in the study area, and the Arctan(PERM)_0/Arctan(PER0M)_1 grouped model was selected as the final predictive model for permeability, which has better prediction accuracy than logging curves. The combination of K-means and the XGBoost modeling method provides a new approach and reference for the efficient and relatively accurate evaluation of porosity and permeability in the study area.

By analyzing the chemical characteristics of the formation water in the tight sandstone reservoirs of the P2x8 and P1s1 in the southern Ordos Basin, combined with rock mineral composition, reservoir physical properties, and well gas testing data, the genesis mechanism of formation water and its guiding role in gas reservoir development were discussed. The results show that the formation water is derived from the mixture of syngenetic seawater and meteoric water and has undergone remarkable modification by water-rock interactions, showing characteristics of Ca²⁺ enrichment and Mg²⁺ and SO₄ ^2- depletion. The albitization of plagioclase in reservoir rock components causes Ca excess and Na deficiency in formation water, while the chloritization of albite leads to the increase of Na⁺. The dolomitization of calcite contributes to the decrease of Mg²⁺ in the formation water, while later ankerite formation makes the correlation of Ca excess-Mg deficit worse. In addition, the chloritization of dolomite and the formation of calcified debris by the metasomatism of ferrocalcite further increase the Ca²⁺ content of the formation water. Fe reduction and pyrite formation in reservoir minerals reduce the concentration of SO₄ ^2-. The study also show that reservoirs endowed with Ca-Cl type formation water has more production potential. Chlorite fill, argillaceous debris, and calcareous debris are negatively correlated with face rate, porosity, and permeability. It is innovatively proposed that the specific formation chemical characteristics combinations and can effectively characterize reservoir porosity and permeability, while combinations and are strongly correlated with gas production and water production. In conclusion, the hydrochemical characteristics of geological formations are important references for reservoir evaluation and development indicators, which is helpful to accurately evaluate the development potential of reservoirs and guide exploration strategies of gas reservoirs.