Abstract: Rotation data and translational data are received. A calibration operator is determined based on the rotation data and translational data, where the calibration operator is useable to relatively calibrate the rotation data and the translation of data.

Abstract: A sensor assembly includes a housing structure, a seismic sensor in the housing structure to measure seismic waves propagated through a subterranean structure, and a pressure sensor in the housing structure. A processor in the housing structure is configured to receive a first signal based on an output of the seismic sensor, and a second signal based on an output of the pressure sensor. First and second digital filters are applied to the first and second signals. Application of the first and second digital filters to the first and second signals causes production of a substantially zero output in response to input that includes just noise data detected at the seismic sensor and the pressure sensor.

Abstract: Seismic data relating to a subterranean structure is received from at least one translational survey sensor, and gradient sensor data is received from at least one gradient sensor. A P wavefield and an S wavefield in the seismic data are separated, based on combining the seismic data and the gradient sensor data.

Abstract: Measured seismic data is received from a seismic sensor. Rotation data is also received, where the rotation data represents rotation with respect to at least one particular axis. The rotation data is combined, using adaptive filtering, with the measured seismic data to attenuate at least a portion of a noise component from the measured seismic data.

Abstract: Translational data acquired by at least one translational survey sensor is received, and rotation data is received.

Abstract: Divergence data is received from a divergence sensor and seismic data is received from seismic sensors, where the divergence sensor and seismic sensors are part of a sensor assembly. A calibration term is computed based on combining the divergence data and the seismic data, where the calibration term includes a first parameter that is related to a characteristic of the sensor assembly, and a second parameter that is related to a characteristic of a near-surface subterranean medium.

Abstract: A method of processing multi-component seismic data is provided that comprises determining, in the time-offset domain, a first partition rate for a first event from the multi-component seismic data. Information about near-receiver properties of the earth may be obtained from the first partition rate. The method may further comprise determining, in the time-offset domain, at least a second partition rate for the first event from the multi-component seismic data and/or at least a third partition rate for a second event. Further information about near-receiver properties of the earth can be obtained from the second and/or third partition rate.

Abstract: A sensor assembly has first sensors spaced apart along a first direction, and second sensors oriented in a second direction generally orthogonal to the first direction. Differencing of outputs of the first sensors is performed, and differencing of outputs of the second sensors is performed. A signal output is produced by combining the differenced outputs of the first sensors and the differenced outputs of the second sensors, where the signal output represents a seismic response of a subterranean structure.

Abstract: A sensor assembly includes a housing structure, a seismic sensor in the housing structure to measure seismic waves propagated through a subterranean structure, and a pressure sensor in the housing structure. A processor in the housing structure is configured to receive a first signal based on an output of the seismic sensor, and a second signal based on an output of the pressure sensor. First and second digital filters are applied to the first and second signals. Application of the first and second digital filters to the first and second signals causes production of a substantially zero output in response to input that includes just noise data detected at the seismic sensor and the pressure sensor.

Abstract: Passive seismic data is collected from measurements of seismic sensors in respective sensor assemblies, where the passive seismic data is based on measurements collected during periods when no active seismic source was activated. Attenuation of surface noise in the passive seismic data is performed using data from divergence sensors in at least some of the sensor assemblies. The passive seismic data with surface noise attenuated is output to allow for performing an operation related to a subterranean structure using the passive seismic data with the surface noise attenuated.

Abstract: A sensor assembly having improved characteristics for use in surveying a subterranean structure includes a divergence sensor for positioning at or below a ground surface, where the divergence sensor includes a container containing a material and a pressure sensor immersed in the material. In addition, the sensor assembly includes a single-component seismic sensor that is external to the container of the divergence sensor.

Abstract: To perform noise attenuation for seismic surveying, a sensor assembly is deployed on a ground surface, where the sensor assembly has a seismic sensor to measure seismic waves propagated through a subterranean structure, and a divergence sensor comprising a pressure sensor to measure noise. First data is received from the seismic sensor, and second data is received from the divergence sensor. The first data and the second data are combined to attenuate noise in the first data.