Deep shale gas reservoirs have geological characteristics of high temperature, high pressure, high stress, and inferior ability to pass through fluids. The multi-stage fractured horizontal well is the key to exploiting the deep shale gas reservoir. However, during the production process, the effectiveness of the hydraulic fracture network decreases with the closure of fractures, which accelerates the decline of shale gas production. In this paper, we addressed the problems of unclear fracture closure mechanisms and low accuracy of shale gas production prediction during deep shale gas production. Then we established the fluid–solid–heat coupled model coupling the deformation and fluid flow among the fracture surface, proppant and the shale matrix. When the fluid–solid–heat coupled model was applied to the fracture network, it was well solved by our numerical method named discontinuous discrete fracture method. Compared with the conventional discrete fracture method, the discontinuous discrete fracture method can describe the three-dimensional morphology of the fracture while considering the effect of the change of fracture surface permeation coefficient on the coupled fracture–matrix flow and describing the displacement discontinuity across the fracture. Numerical simulations revealed that the degree of fracture closure increases as the production time proceeds, and the degree of closure of the secondary fractures is higher than that of the primary fractures. Shale creep and proppant embedment both increase the degree of fracture closure. The reduction in fracture surface permeability due to proppant embedment reduces the rate of fluid transfer between matrix and fracture, which has often been overlooked in the past. However, it significantly impacts shale gas production, with calculations showing a 24.7% cumulative three-year yield reduction. This study is helpful to understand the mechanism of hydraulic fracture closure. Therefore, it provides the theoretical guidance for maintaining the long-term effectiveness of hydraulic fractures.

Due to the complexity and variability of carbonate formation leakage zones, lost circulation prediction and control is one of the major challenges of carbonate drilling. It raises well-control risks and production expenses. This research utilizes the H oilfield as an example, employs seismic features to analyze mud loss prediction, and produces a complete set of pre-drilling mud loss prediction solutions. Firstly, 16 seismic attributes are calculated based on the post-stack seismic data, and the mud loss rate per unit footage is specified. The sample set is constructed by extracting each attribute from the seismic trace surrounding 15 typical wells, with a ratio of 8:2 between the training set and the test set. With the calibration results for mud loss rate per unit footage, the nonlinear mapping relationship between seismic attributes and mud loss rate per unit size is established using the mixed density network model. Then, the influence of the number of sub-Gausses and the uncertainty coefficient on the model's prediction is evaluated. Finally, the model is used in conjunction with downhole drilling conditions to assess the risk of mud loss in various layers and along the wellbore trajectory. The study demonstrates that the mean relative errors of the model for training data and test data are 6.9% and 7.5%, respectively, and that R² is 90% and 88%, respectively, for training data and test data. The accuracy and efficacy of mud loss prediction may be greatly enhanced by combining 16 seismic attributes with the mud loss rate per unit footage and applying machine learning methods. The mud loss prediction model based on the MDN model can not only predict the mud loss rate but also objectively evaluate the prediction based on the quality of the data and the model.

The presence of micro-fractures in shale reservoirs is vital for economic production. While a number of models have been proposed to predict the propagation pressure of pre-existing micro-fractures, few models have considered capillary pressure, which may play a significant role in the presence of micro-fractures with nano-scale width. In this study, a new model was developed to predict the propagation pressure of micro-fractures. It is assumed that pre-existing micro-fractures are arbitrarily intersected with the propagated hydraulic fractures. The model was derived based upon linear elastic fracture mechanics under the condition of mode I fracture propagation coupled with capillary pressure. Furthermore, this paper also conducted sensitivity analyses to predict the micro-fracture propagation pressure as a function of the contact angle, surface tension and the width of micro-fracture. The results demonstrated that decreasing the contact angle reduces the propagation pressure of micro-fractures, implying that a hydrophilic system may yield a lower fracture propagation pressure compared with the hydrophobic counterpart. Moreover, for a hydrophilic system, further decreasing the contact angle shifts the propagation pressure to a negative value, implying that the capillary pressure may induce the propagation of micro-fractures without external fluid injection. The propagation pressure is also affected by the surface tension and the width of micro-fracture.