Seismic data and nuclear magnetic resonance (NMR) data are two of the highly trustable kinds of information in hydrocarbon reservoir engineering. Reservoir fluids influence the elastic wave velocity and also determine the NMR response of the reservoir. The current study investigates different pore types, i.e., micro, meso, and macropores’ contribution to the elastic wave velocity using the laboratory NMR and elastic experiments on coal core samples under different fluid saturations. Once a meaningful relationship was observed in the lab, the idea was applied in the field scale and the NMR transverse relaxation time (T₂) curves were synthesized artificially. This task was done by dividing the area under the T₂ curve into eight porosity bins and estimating each bin’s value from the seismic attributes using neural networks (NN). Moreover, the functionality of two statistical ensembles, i.e., Bag and LSBoost, was investigated as an alternative tool to conventional estimation techniques of the petrophysical characteristics; and the results were compared with those from a deep learning network. Herein, NMR permeability was used as the estimation target and porosity was used as a benchmark to assess the reliability of the models. The final results indicated that by using the incremental porosity under the T₂ curve, this curve could be synthesized using the seismic attributes. The results also proved the functionality of the selected statistical ensembles as reliable tools in the petrophysical characterization of the hydrocarbon reservoirs.

Bed-separation water hazards are a common and very harmful mining disaster in the mining areas of western China in recent years, which seriously threatens the safe mining of rich and thick coal seam resources in the West. The Yonglong mining area has become a high-risk area for bed-separation water hazards due to its particularly thick coal seams and strong water-rich overlying strata. In view of this, this paper investigates the development height of a water-flowing fractured zone in the fully mechanized caving mining of an ultra-thick coal seam in the Yonglong mining area, the evolution law of the bed separation of overlying strata, and the process of water inrush from a bed separation. Based on the measured water-flowing fractured zone height data of the Yonglong mining area and several surrounding mines, a water-flowing fractured zone height prediction formula suitable for the geological conditions of the Yonglong mining area was fitted. By using discrete element numerical simulation and laboratory similarity simulation, the evolution law of overlying strata separation under the conditions of fully mechanized caving mining in the study area was analyzed, and the space was summarized into “four zones, three arches, and five zones”. Through the stress-seepage coupling simulation of the water inrush process of the roof separation in the fully mechanized caving mining of an ultra-thick coal seam, the migration, accumulation, and sudden inrush of water in the aquifer in overlying strata under the influence of mining were analyzed, and the variation in the pore water pressure in the process of water inrush during coal seam mining separation was summarized. The pore water pressure in the overlying strata showed a trend of first decreasing, then increasing, and, finally, stabilizing. Combined with the height, water inrush volume, and water-rich zoning characteristics of the water-flowing fractured zone of the 1012007 working face of the Yuanzigou Coal Mine, the danger of water inrush from the overlying strata separation of the working face was evaluated. It is believed that it has the conditions for the formation of water accumulation and separation, and the risk of water inrush is high. Prevention and control measures need to be taken on site to ensure mining safety. The research results have important guiding significance for the assessment and prevention of water inrush hazards in overlying strata during fully mechanized longwall top-coal caving of ultra-thick coal seams with similar geological conditions worldwide.

In this study, the effects of surface roughness and Reynolds number (Re) on fluid flow and solute transport are investigated based on a double rough-walled fracture model that precisely represents the natural geometries of rock fractures. The double rough-walled fracture model is composed of two three-dimensional(3D) self-affine fracture surfaces generated using the improved successive random additions (SRA). Simulation of fluid flow and solute transport through the models were conducted by directly solving the Navier-Stokes equation and advection-diffusion equation (ADE), respectively. The results indicate that as the Re increases from 0.1 to 200, the flow regime changes from linear flow to nonlinear flow accompanied with the tortuous streamlines and significant eddies. Those eddies lead to the temporary stagnant zones that delay the solute migration. The increment of Re enhances the transport heterogeneity with the transport mode changing from the diffusion-dominated to the advection-dominated behavior, which is more significant in the fracture with a larger joint roughness coefficient (JRC). All breakthrough curves (BTCs) of rough-walled fractures exhibited typical non-Fickian transport characteristics with “early arrival” and “long tailing” of BTCs. Increasing the JRC and/or Re will enhances the non-Fickian transport characteristics. The ADE model is able to accurately fit the numerical BTCs and residence time distributions (RTDs) at a low Re, but fails to capture the non-Fickian transport characteristics at a large Re. In contrast, the continuous time random walk (CTRW) model provides a better fit to the numerical simulation results over the whole range of Re. Whereas, the fitting error gradually increases with increasing Re.

To investigate dynamic fracture characteristics and failure behavior of different sections of tunnel surrounding rock mass, six kinds of model tunnels were fabricated using green sandstone, and impact tests were performed using a split Hopkinson pressure bar system. The dynamic compressive strength and energy change behaviors of samples comprising different-shaped tunnels were assessed, and crack propagation paths were analyzed employing a digital image correlation method. Numerical calculations were carried out using the software LS-DYNA (v. 2021R1), and the dynamic stress concentration factors of different model tunnel samples were determined. The results of the research indicated that the shape of the tunnel affected the dynamic compressive strength. The elliptical tunnel had the smallest percentage of dissipated energy, and the three-centered circular tunnel had the largest percentage of dissipated energy. The maximum tensile stress concentration factor in the model tunnels consistently occurred at the top or bottom; so, the locations of initiation were most commonly at the bottoms and tops of the tunnels. Sample failure resulted from a combination of tensile and shear cracks, with the failure mode being primarily tensile-dominated. Finally, the inverted arch had an obvious alleviating action on the stress concentration phenomenon at the bottom of the three-centered circle.

The identification and classification of rock discontinuities are crucial for studying rock mechanical properties and rock engineering optimization design and safety assessment. An improved artificial bee colony (ABC) algorithm is proposed and combined with the fuzzy C-means (FCM) clustering method to develop an FCM clustering method for automatically identifying rock discontinuity sets based on the ABC algorithm (FCM-ABC method). All the equations of the method are fully developed, and the methodology is presented in its entirety. Moreover, the rock structural planes are investigated in a gold mine in China using a ShapeMetriX 3D system. Based on the measured structural plane data, the specific calculation process, selection of parameters, effectiveness of grouping, and the dominant orientation of the proposed method for structural plane occurrence classification are analyzed and discussed, and satisfactory clustering results are achieved. This validates the validity and reliability of the method. Furthermore, multiple aspects of the excellent performance of this method for the identification of structural plane sets compared to traditional clustering methods are demonstrated. In addition, the significance of structural plane identification in the prevention and control of rock engineering disasters is discussed. This new method theoretically expands the technology of rock mass structural plane identification and has important application value in practical engineering.