For microseisimic monitoring it is difficult to determine wave modes and their propagation velocity. In this paper, we propose a new method for automatically inverting in real time the source characteristics of microseismic events in mine engineering without wave mode identification and velocities. Based on the wave equation in a spherical coordinate system, we derive a tomographic imaging equation and formulate a scanning parameter selection criterion by which the microseisimic event maximum energy and corresponding parameters can be determined. By determining the maximum energy positions inside a given risk district, we can indentify microseismic events inside or outside the risk districts. The synthetic and field examples demonstrate that the proposed tomographic imaging method can automatically position microseismic events by only knowing the risk district dimensions and range of velocities without identifying the wavefield modes and accurate velocities. Therefore, the new method utilizes the full wavefields to automatically monitor microseismic events.
Although full waveform inversion in the frequency domain can overcome the local minima problem in the time direction, such problem still exists in the space direction because of the media subsurface complexity. Based on the optimal steep descent methods, we present an algorithm which combines the preconditioned bi-conjugated gradient stable method and the multi-grid method to compute the wave propagation and the gradient space. The multiple scale prosperity of the waveform inversion and the multi-grid method can overcome the inverse problems local minima defect and accelerate convergence. The local inhomogeneous three-hole model simulated results and the Marmousi model certify the algorithm effectiveness.
Although high resolution can be provided by electrical logging, the measured electrical log range is narrow and is limited to near the well. Borehole-surface electric potential measurements are able to detect a wide enough range but its resolution is limited, particularly for reservoirs with complex oil and water distribution or complicated structure. In this study, we attempt to accurately locate the 3-D reservoir water and oil distribution by combining borehole-surface and crosswell electric potentials. First, the distributions of oil and water in both vertical and horizontal directions are detected by the borehole-surface and erosswell electric potential methods, respectively, and then the measured crosswell potential result is used to calibrate the measured borehole-surface electric potential data to improve vertical resolution so that the residual oil distribution is determined in a lower half-space with three dimensions. The evaluation of residual oil distribution is obtained by investigation of differences between the simulation results of the reservoir with and without water flooding. The finite difference numerical simulation results prove that the spatial residual oil distribution can be effectively determined by combining the crosswell and borehole-surface electric potentials.
