Donghong Pei

Velocity calibration for microseismic monitoring: A very fast simulated annealing (VFSA) approach for joint-objective optimization

To accurately locate microearthquakes that are genetically related to hydraulic fracture stimulation, a thorough knowledge of the velocity structure between monitoring and fracturing treatment wells is essential. Very fast simulated annealing (VFSA) is implemented to invert for a flat-layered velocity model between wells using perforation or string-shot data. A two-point ray-tracing method is used to find the ray parameter p for a ray traveling from a source to a receiver. The original traveltime-calculation formula is modified to account for the borehole source-receiver geometry. VFSA is used as a tool to optimize P- and S-wave velocities simultaneously. Unlike previous applications of VFSA, two improvements result from a new study: (1) both P- and S-wave arrival-time misfits are considered in a joint-objective function, and (2) P- and S-wave velocities are perturbed simultaneously during annealing. The inverted velocities follow the true values closely with a very small root-mean-square error, indicating the inverted model is close to the global minimum solution whose rms error should be zero for synthetic examples. Data noise contaminates inverted models, but not substantially in synthetic test results. A comparison of models inverted using VFSA and Occams inversion technique indicates that inverted models using VFSA are superior to those using Occams method in terms of velocity accuracy.

Three-dimensional traveltime tomography via LSQR with regularization

This article described a 3D traveltime tomography algorithm using LSQR with regularization and apply it to a synthetic example. Models consist of uniformly gridded cells in three dimensions with a constant velocity for each cell. Traveltimes of the model are calculated by applying finite-difference methods of the seismic-ray eikonal equation. The inversion minimizes a functional that includes a least-square penalty function and horizontal and vertical roughness constraints. The minimization leads to a very large system of linear equations that is solved through LSQR. Normally distributed random numbers are generated and added to the synthetic arrival-times to create noisy synthetic data. The inversion works on these noisy data to produce a 3D model. The velocity anomaly of the inverted model is clearly defined, indicating that the algorithm is valid and effective.

Improved Methods for Hydrofrac Event Detection and Phase Picking

The ability to detect small microseismic events and identify their P and S phase arrivals is a key issue in hydraulic fracture monitoring because of the low signal-to-noise ratios. We propose a array-based waveform correlation approach to detect small magnitude events with similar mechanisms and locations as a nearby master event. For the phase picking part, a transformed spectrogram method is used to identify the weak P arrivals. We have applied the technique to a downhole monitoring dataset of the microseismic events induced by hydraulic fracturing. The results show a better phase identification.