A five component land seismic sensor for measuring lateral gradients of the wavefield

We built a five-component (5C) land seismic sensor that measures both the threecomponent (3C) particle acceleration and two vertical gradients of the horizontal wavefield through a pair of 3C microelectromechanical accelerometers. The sensor is a small cylindrical device planted vertically just below the earth’s surface. We show that seismic acquisition and processing 5C sensor data has the potential to replace conventional seismic acquisition with analogue geophone groups by single 5C sensors placed at the same station interval when combined with a suitable aliased ground roll attenuation algorithm. The 5C sensor, therefore, allows for sparser, more efficient, data acquisition. The accuracy of the 5C sensor wavefield gradients depends on the 3C accelerometers, their sensitivity, self-noise and their separation. These sensor component specifications are derived from various modelling studies. The design principles of the 5C sensor are validated using test data from purpose-built prototypes. The final prototype was constructed with a pair of 3C accelerometers separated by 20 cm and with a self-noise of 35 ng Hz−1/2. Results from a two-dimensional seismic line show that the seismic image of 5C sensor data with ground roll attenuated using 5C sensor gradient data was comparable to simulated analogue group data as is the standard in the industry. This field example shows that up to three times aliased ground roll was attenuated. The 5C sensor also allows for correcting vertical component accelerometer data for sensor tilt. It is shown that a vertical component sensor that is misaligned with the vertical direction by 10° introduces an error in the seismic data of around –20 dB with respect to the seismic signal, which can be fully corrected. Advances in sensor specifications and processing algorithms are expected to lead to even more effective ground roll attenuation, enabling a reduction in the receiver density resulting in a smaller number of sensors that must be deployed and, therefore, improving the operational efficiency while maintaining image quality.