Effects of Shear Fracture on In-depth Profile Modification of Weak Gels

Two sand packs were filled with fine glass beads and quartz sand respectively. The characteristics of crosslinked polymer flowing through the sand packs as well as the influence of shear fracture of porous media on the indepth profile modification of the weak gel generated from the crosslinked polymer were investigated. The results indicated that under the dynamic condition crosslinking reaction happened in both sand packs, and the weak gels in these two cases became small gel particles after water flooding. The differences were： the dynamic gelation time in the quartz sand pack was longer than that in the glass bead pack. Residual resistance factor （FRR） caused by the weak gel in the quartz sand pack was smaller than that in the glass bead pack. The weak gel became gel particles after being scoured by subsequent flood water. A weak gel with uniform apparent viscosity and sealing characteristics was generated in every part of the glass bead pack, which could not only move deeply into the sand pack but also seal the high capacity channels again when it reached the deep part. The weak gel performed in-depth profile modification in the glass bead pack, while in the quartz sand pack, the weak gel was concentrated with 100 cm from the entrance of the sand pack. When propelled by the subsequent flood water, the weak gel could move towards the deep part of the sand pack but then became tiny gel particles and could not effectively seal the high capacity channels there. The in-depth profile modification of the weak gel was very weak in the quartz sand pack. It was the shear fracture of porous media that mainly affected the properties and weakened the in-depth profile modification of the weak gel.

A numerical approach for pressure transient analysis of a vertical well with complex fractures

A new well test model for a vertical fractured well is developed based on a discrete-fracture model in which the fractures are discretized as one dimensional（1-D） entities.The model overcomes the weakness of complex meshing,a large number of grids, and instability in conventional stripe-fracture models. Then, the discrete-fracture model is implemented using a hybrid element finite-element method.Triangular elements are used for matrix and line elements for the fractures. The finite element formulation is validated by comparing with the semi-analytical solution of a single vertical fractured well. The accuracy of the approach is shown through several examples with different fracture apertures,fracture conductivity, and fracture amount. Results from the discrete-fracture model agree reasonably well with the stripefracture model and the analytic solutions. The advantages of the discrete-fracture model are presented in mesh generation, computational improvement, and abilities to handle complex fractures like wedge-shaped fractures and fractures with branches. Analytical results show that the number of grids in the discrete-fracture model is 10 % less than stripefracture model, and computational efficiency increases by about 50 %. The more fractures there are, the more the computational efficiency increases.

Real-time prediction of tunnel face conditions using XGBoost Random Forest algorithm

Real-time perception of rock conditions based on continuously collected data to meet the requirements of continuous Tunnel Boring Machine(TBM)construction presents a critical challenge that warrants increased attention.To achieve this goal,this paper establishes real-time prediction models for fractured and weak rock mass by comparing 6 different algorithms using real-time data collected by the TBM.The models are optimized in terms of selecting metric,selecting input features,and processing imbalanced data.The results demonstrate the following points.(1)The Youden's index and area under the ROC curve(AUC)are the most appropriate performance metrics,and the XGBoost Random Forest(XGBRF)algorithm exhibits superior prediction and generalization performance.(2)The duration of the TBM loading phase is short,usually within a few minutes after the disc cutter contacts the tunnel face.A model based on the features during the loading phase has a miss rate of 21.8%,indicating that it can meet the early warning needs of TBM construction well.As the TBM continues to operate,the inclusion of features calculated from subsequent data collection can continuously correct the results of the real-time prediction model,ultimately reducing the miss rate to 16.1%.(3)Resampling the imbalanced data set can effectively improve the prediction by the model,while the XGBRF algorithm has certain advantages in dealing with the imbalanced data issue.When the model gives an alarm,the TBM operator and on-site engineer can be reminded and take some necessary measures for avoiding potential tunnel collapse.The real-time predication model can be a useful tool to increase the safety of TBM excavation.