Joint inversion of water velocity and node position for ocean-bottom node data

Abstract

Variation of sound wave velocity in water (water velocity) and node positioning errors can cause strong 4D noise in ocean bottom node (OBN) time-lapse processing if they are not addressed correctly. Here we proposed a method to jointly invert the water velocity and the node position from the recorded direct arrival time in the data. We validated this method using synthetic and real OBN data examples from deep-water Gulf of Mexico.

Quality control for the geophone reorientation of ocean bottom seismic data using k‐means clustering

“…Since the accurate positioning of sources and receivers is the basic premise of proposed workflow, erroneous source/receiver positions hinder the estimation of the direct arrivals and analytical solutions for the direct P ‐wave azimuth and incident angle, resulting in ‘abnormal’ labels, which indicate either a false decision or an actual abnormal receiver. Thus, to ensure further reliability of the proposed workflow, additional efforts will be required to adjust the positioning of sources and receivers (Oshida et al ., 2008; Amini et al ., 2016). Furthermore, when the direct arrivals are poorly captured, the proposed workflow yields ‘abnormal’ labels.…”

OBN for pre-salt imaging and reservoir monitoring – Potential and road ahead

“…This change of velocity can lead to time-shifts of 5.4 ms in the upgoing wavefield and 16 ms in the downgoing wavefield measured at the water bottom for zero-offset recording. Water velocity and tidal variations can be jointly inverted with node/shot positions and node clock drift (Amini et al, 2016) and corrected for base and monitor surveys respectively (Huang et al, 2016).…”

The structure of water-layer sensitivity kernels in OBN-type acquisition geometries

“…Similarly, corrections of water velocity are also necessary in OBN surveys, with some additional care to shot and receiver positions, and timing (UDENGAARD and CRAFT, 2012). Here, joint inversion seems to be recommended, to avoid error leakage to each separated variable (AMINI et al, 2016). Nonetheless, the usual treatment of water layer velocity appears to also assume a homogeneously (spatially-averaged) time-dependent quantities (BOELLE et al, 2010;DOCHERTY and HAYS, 2012;AHMED et al, 2013;AMINI et al, 2016), though further development considers time-dependent corrections of an overall (interpolated) 1D sound velocity profile (DOCHERTY and HAYS, 2012).…”

“…Here, joint inversion seems to be recommended, to avoid error leakage to each separated variable (AMINI et al, 2016). Nonetheless, the usual treatment of water layer velocity appears to also assume a homogeneously (spatially-averaged) time-dependent quantities (BOELLE et al, 2010;DOCHERTY and HAYS, 2012;AHMED et al, 2013;AMINI et al, 2016), though further development considers time-dependent corrections of an overall (interpolated) 1D sound velocity profile (DOCHERTY and HAYS, 2012). Alternatives to even more detailed velocity reconstructions involve some additional input, as the information of multiples (reverberation) trapped in the water column (DUNN, 2015), or simultaneous data from vertical cables (ZOU et al, 2018).…”