Internal magnetic gradient plays a significant role in Nuclear Magnetic Resonance(NMR)measurements of fluid saturated porous media.The quantitative characterization and application of this physical phenomenon could effectively improve the accuracy of NMR measurements and interpretations.In this paper,by using the equivalent magnetic dipole method,the three-dimensional distribution of internal induced magnetic field and its gradients in the randomly packed water saturated glass beads are quantitatively characterized.By simulating the diffusive motion of water molecules in porous media with random walk method,the computational dephasing effects equation related to internal gradients is deduced.Thereafter,the echo amplitudes are obtained and the corresponding T2-G spectrum is also inverted.For the sake of verifying the simulation results,an experiment is carried out using the Halbach core analyzing system(B0=0.18 T,G=2.3 T/m)to detect the induced internal field and gradients.The simulation results indicate the equivalent internal gradient is a distribution of 0.1-0.3 T/m,which matched well with the experimental results.
In contrast to conventional gas-bearing rocks, gas shale has extremely low permeability due to its nano- scale pore networks. Organic matter which is dispersed in the shale matrix makes gas flow characteristics more complex. The traditional Darcy＇s law is unable to estimate matrix permeability due to the particular flow mechanisms of shale gas. Transport mechanisms and influence factors are studied to describe gas transport in extremely tight shale. Then Lattice Boltzmann simulation is used to establish a way to estimate the matrix permeability numerically. The results show that net desorption, diffu- sion, and slip flow are very sensitive to the pore scale. Pore pressure also plays an important role in mass fluxes of gas. Temperature variations only cause small changes in mass fluxes. The Lattice Boltzmann method can be used to study the flow field in the micropore spaces and then provides numerical solutions even in complex pore structure models. Understanding the transport characteristics and establishing a way to estimate potential gas flow is very important to guide shale gas t＇eserve estimation and recovery schemes.
