Ocean Bottom Node Research Articles

On efficient frequency-domain full-waveform inversion with extended search space

Efficient frequency-domain full-waveform inversion (FD-FWI) of wide-aperture data is designed by limiting inversion to a few frequencies and by solving the Helmholtz equation with a direct solver to process multiple sources efficiently. Some variants of FD-FWI, which process the wave equation as a weak constraint, have been proposed to increase the computational efficiency or extend the search space. Among them, the contrast-source reconstruction inversion (CSRI) reparameterizes FD-FWI in terms of contrast sources (CS) and contrasts and updates them in an alternating mode. This reparameterization allows for one lower-upper (LU) decomposition of the Helmholtz operator to be performed per frequency inversion hence further improving the computational efficiency of FD-FWI. However, iteratively refined wavefield reconstruction inversion (IR-WRI) relies on the alternating-direction method of multipliers to extend the search space by matching the data from the early iterations via an aggressive relaxation of the wave equation while satisfying it at the convergence point thanks to the defect correction performed by the Lagrange multipliers. In contrast to CSRI, IR-WRI requires redoing one LU decomposition when the subsurface model is updated. In both methods, the CSs or the wavefields are computed by solving in a least-squares sense an overdetermined linear system gathering an observation equation and a wave equation. A drawback of CSRI is that CSs are estimated approximately with one iteration of a conjugate gradient method, whereas the wavefields are reconstructed exactly by IR-WRI with a Gauss-Newton method. We have combined the benefits of CSRI and IR-WRI to decrease the number of LU decomposition during IR-WRI with a fixed-point (FP) algorithm while preserving its search space extension capability. Application on the 2D complex Marmousi and the BP salt models shows that our FP-based IR-WRI manages to reconstruct these models as accurately as the classic IR-WRI while reducing the number of LU factorizations considerably. A theoretical complexity analysis and a recent application of 3D FD-FWI based upon direct solver suggest that the FP algorithm should reduce the cost of IR-WRI by a factor of approximately 2 and 10 for 3D dense ocean bottom cable and sparse ocean bottom node acquisitions, respectively.

Computational aspects of finite-frequency traveltime inversion kernels

Finite-frequency traveltime inversion offers higher accuracy for velocity model building than ray-based traveltime inversion. The adjoint force is the key for the computation of inversion kernels. Starting at the definition of inversion kernels for the acoustic wave equation, we have derived the explicit formula for the spectral distribution density function used in the adjoint force computation. Two formulations are developed for the computation of adjoint forces for receiver-side extrapolation, frequency-domain representation, and time-domain representation. The accuracy of finite-frequency traveltime inversion kernels is benchmarked with the analytical solutions for homogeneous isotropic media. We use wavefront construction to compute the first Fresnel zones for kernel conditioning. Based on dynamic ray tracing, we design a processing procedure guided by synthetic data tests to extract the desired events for wavefield backward extrapolation from the data. Unlike ray-based velocity tomography, finite-frequency inversion can resolve the velocity structures comparable with the size of Fresnel zones as we demonstrate on a marine salt model using ocean-bottom node acquisition geometry. Despite the fact that the inversion kernels are based on Born approximation, velocities with errors up to 20% can be well-resolved. For practical purposes, a simple formulation is given for the determination of the shot spacing. Our workflow for finite-frequency inversion is efficient and converges in only very few iterations.

New-generation simultaneous shooting sparse OBN survey and FWI delineate deep subsalt structures in the Greater Mars-Ursa area

The U.S. Gulf of Mexico (GoM) geology is well known for prolific structural hydrocarbon traps created by salt tectonics. In many areas, these structures lie below salt overhangs or thick canopies, requiring advanced seismic imaging to identify prospects and plan exploration wells. Ever-evolving geophysical technologies, such as 3D seismic, wide azimuth, multiwide azimuth, coil, and ocean-bottom node (OBN) acquisition designs, have unlocked the image for some of these structures over the past three decades. Recently, automatic velocity model building methods, particularly full-waveform inversion (FWI), introduced another step change in the subsalt image quality and refocused the acquisition methods on the need to acquire long-offset data. To make such a long-offset program affordable, a new survey geometry was set up with sparse OBN nodes and simultaneous shooting. The actual survey was acquired in 2019 and fully processed within 15 months from the end of the acquisition. Offsets up to 65 km were recorded, enabling FWI velocity updates down to 15 km depth. To provide the reader with a glimpse of the geologic insight that the new technology enabled, we report a few examples of deep geology revealed by this survey in a hydrocarbon- and seismic-data-rich area of the GoM — the Greater Mars-Ursa Basin.

Seismic imaging of S-wave structures of shallow sediments in the East China Sea using OBN multicomponent Scholte-wave data

The shear-wave (S-wave) structures of shallow marine sediments are important for offshore geotechnical studies, deep crustal S-wave imaging, multicomponent seismic exploration, and underwater acoustics studies. We have applied the multicomponent Scholte-wave analysis technique to an active-source shallow marine seismic profile in the East China Sea. Scholte waves have been excited by shots from a 5450 inch3air-gun array and their recordings have been conducted at the seafloor using ocean bottom nodes (OBNs). First, we extract the common-receiver gathers (CRGs) and correct for the time drift simultaneously using a forward and inverse fast Fourier transform resampling algorithm. Three CRGs of seismic sensors are used for Scholte-wave analysis. Raw sensor CRGs are rotated to the inline, crossline, and vertical coordinate system. The rotated tilt and roll angle are directed using the inner electric compass log value, and the shot inline azimuth is estimated using the particle motion method. Then, the velocity spectra are calculated from the inline and vertical components using the phase-shift method. Higher Scholte-wave modes dominate on the horizontal components, whereas the stronger fundamental mode dominates on the vertical components. The multicomponent velocity spectrum stacking method is adopted to produce the final dispersion energy image. Up to four modes of dispersion curves are retrieved within the 1.1–4.3 Hz frequency band. The multimode dispersion curve inversion is constructed for imaging the shallow sediments. The results suggest a low [Formula: see text] of 180–650 m/s and few lateral variations within the top 0.5 km of shallow marine sediments in the East China Sea. This model can provide an important reference for offshore geotechnical investigations, especially for OBN multicomponent seismic exploration data processing. The use of OBNs has high feasibility in [Formula: see text] imaging for shallow marine sediments when combined with the Scholte-wave dispersion-curve inversion.

Deep learning-based artificial bandwidth extension: Training on ultrasparse OBN to enhance towed-streamer FWI

The lack of seismic low frequencies in towed-streamer data is known to have an outsized detrimental effect on advanced velocity model building techniques such as full-waveform inversion (FWI). Since seabed acquisition records ultralow frequencies (1–4 Hz) with high signal-to-noise ratio, this presents an opportunity to learn, in a supervised machine learning fashion, a bandwidth extension function to enrich towed-streamer data with low frequencies. We use recent advances in training deep neural networks to develop a novel method for learning low-frequency reconstruction from an ultrasparse set of ocean-bottom nodes (OBNs). This bandwidth extension is tested on two large field data sets (from an OBN survey and a wide-azimuth towed-steamer survey) acquired over a complex-shaped salt region in the Gulf of Mexico. The reconstructed low frequencies, although not perfect, enable FWI to more effectively correct the shape of salt bodies and result in improved subsalt imaging. Well-tie analysis shows an improvement in phase stability around the wellbore and a fit to within half a cycle at reservoir level. This work links together towed-streamer and seabed acquisitions, providing a cost-effective solution to help offshore seismic exploration with higher-quality low frequencies.

Inpainting of local wavefront attributes using artificial intelligence for enhancement of massive 3-D pre-stack seismic data

SUMMARYWe propose an advanced version of non-linear beamforming assisted by artificial intelligence (NLBF-AI) that includes additional steps of encoding and interpolating of wavefront attributes using inpainting with deep neural network (DNN). Inpainting can efficiently and accurately fill the holes in waveform attributes caused by acquisition geometry gaps and data quality issues. Inpainting with DNN delivers excellent quality of interpolation with the negligible computational effort and performs particularly well for a challenging case of irregular holes where other interpolation methods struggle. Since conventional brute-force attribute estimation is very costly, we can further intentionally create additional holes or masks to restrict expensive conventional estimation to a smaller subvolume and obtain missing attributes with cost-effective inpainting. Using a marine seismic data set with ocean bottom nodes, we show that inpainting can reliably recover wavefront attributes even with masked areas reaching 50–75 per cent. We validate the quality of the results by comparing attributes and enhanced data from NLBF-AI and conventional NLBF using full-density data without decimation.

First time-lapse OBN in Bonga deepwater offshore field

Time-lapse seismic data from Bonga Field, located in deepwater Nigeria, have delivered excellent results previously from dedicated streamer seismic surveys (2000, 2008, and 2012) that image changes in amplitude due to water replacing oil. One challenge with the streamer data is the presence of a floating production storage and offloading (FPSO) unit. It is difficult to accurately repeat streamer acquisition geometry in economically important updip regions of reservoirs that lie beneath the FPSO. To ensure an accurate repeat of this area, we acquired an ocean-bottom node (OBN) survey in 2010 and carried out the first time-lapse OBN repeat of the survey in 2018. Time-lapse processing of the OBN data produced excellent results. We obtained an OBN-on-OBN normalized root mean square (NRMS) difference repeatability of 6%. This was an improvement over the 12% NRMS for streamer-on-streamer repeats. The OBN data quality was unaffected by the FPSO, enabling us to properly image the changes occurring in this area. The 4D OBN interpretation was used to identify bypassed oil opportunities. The data also were used to derisk well placement, optimize water injection, and update the dynamic reservoir models. The new models are essential to enhance predictability and field performance. We also analyzed an area northwest of the field where we extended the 2018 OBN acquisition and compared it to streamer data to optimize a new injection well location.

The value of high-density blended OBN seismic for drilling and reservoir description at the Tangguh gas fields, Eastern Indonesia

The Tangguh gas fields in Eastern Indonesia are overlain by a complex overburden, including a thick, heavily faulted, and intensely karstified carbonate interval that tends to scatter and attenuate seismic energy. Development drilling is challenging, with the potential for pack-offs and stuck pipe when drilling into unstable, partially collapsed caves or karstified fault planes while on total losses. Ideally, these karst features are to be avoided when planning and drilling wells, but avoiding them depends on having a well-resolved seismic image. Historical towed-streamer and sparse ocean-bottom cable seismic is low fold and does not give a satisfactory image for well planning. Advances in ocean-bottom node technology, computer processing, and capacity coupled with efficient survey design and blended acquisition utilizing multiple source vessels allowed a step change in data density. This provided a new high-quality seismic image to support future development activities. The advantages of densely sampled, full-azimuth data include rapid delivery of fast-track products (because high-quality images can be constructed with relatively simple processing flows), greatly improved overburden imaging, and a corresponding uplift in deeper imaging leading to enhanced reservoir characterization.

Traveltime computation and OBN seismic record simulation for rugged seafloor in VTI medium

ABSTRACT To improve the computational accuracy of seismic traveltime for complex structures in inhomogeneous media, a mesh generation method that is adaptive to a rugged seafloor or interface is presented. A hybrid mesh discrete velocity model consisting of conventional rectangular mesh and irregular quadrilateral mesh is also proposed. The local traveltime equations for the hybrid mesh are derived from the linear traveltime interpolation (LTI) method and are shown to be stable. The relationship between the group velocity and group angle is converted into that between group velocity and interpolated point coordinates, extending the LTI ray tracing algorithm to multiwave simulation in vertical transversely isotropic (VTI) medium by multi-stage partitioning. Computations of the first arrival, reflection, multiple reflection, multiple transmission conversion, and multiple reflection conversion seismic waves in the VTI medium with rugged seafloor and complex structural interfaces are realised. The results show that the proposed method can adapt to the rugged seafloor and velocity interfaces of complex structures, resulting in higher computational accuracy of the traveltime and ray paths for ocean bottom node (OBN) seismic wave simulation. The accuracy of the proposed method is verified by comparison with the finite-difference method. This method will be useful for modelling of seismic waves, wavefield identification, and study of seismic wave propagation in OBN seismic observations.

The Golden Eagle, Peregrine and Solitaire fields, Blocks 14/26a and 20/01, UK North Sea

Abstract The Golden Eagle Field is located 18 km north of the Buzzard Field in the Moray Firth, and consists of oil accumulations in the Lower Cretaceous Punt and Upper Jurassic Burns Sandstone members. The development area comprises three fields, Golden Eagle, Peregrine and Solitaire, but up to 90% of the oil-in-place and ultimate recovery are in Golden Eagle. The two satellite fields are primarily structural closures, while the Golden Eagle Field reservoirs have a major element of stratigraphic pinchout. Production commenced in October 2014 and approximately 140 MMbbl of recoverable oil is anticipated over its field life from the 19 development wells (14 producers and 5 injectors) that form the initial development phase. Production performance to date has exceeded expectations, aided through the use of completions that provide zonal control of the reservoir units which has successfully supported reservoir management and improved sweep efficiency. A number of significant lessons have been learned during the early stages of the field life from the integration of dynamic data (real-time downhole fibre-optic reservoir monitoring instruments, inter- and intra-well tracers, and well interference tests) and seismic data improvements (post-start-up acquisition of high-density ocean-bottom node seismic and depth-conversion improvements).

On the role of diffractions in velocity model building: a full-waveform inversion example

Imaging of small-scale heterogeneities is important for the geological exploration in complex environments. It requires a processing sequence tuned to high-resolution model building. Conventional methods which use refractions or reflections might face problems in resolving small-scale features since they are visually close to the resolution of the reflection images. Additional information or an unconventional technology, which supports the reflection imaging, is thus of great interest. An unconventional method based on seismic diffractions naturally complements specular reflection imaging. Diffracted waves represent a direct seismic response from small-scale subsurface heterogeneities, such as inclusions with a characteristic size of the prevailing wavelength, or discontinuities in geological interfaces, such as faults and fractures. We investigate the rule of diffracted part of the wavefield on velocity model building using a full-waveform inversion (FWI) example. In order to best acknowledge refracted and reflected parts of the wavefield in FWI, we chose a synthetic data example which mimics the ocean-bottom nodes acquisition survey as it provides almost perfect conditions for FWI of diving waves, a standard tool for high-resolution model building. We show, that FWI using diving waves produces a well-resolved anomaly. Including other part of the wavefield, reflected waves, further improves the resolution of the velocity anomaly but also leads to a gentle overfitting due to missing illumination from the very steep anomaly flanks. Considering diffracted events in FWI improves the model resolution even further resulting in a detailed velocity model and correctly imaged anomaly in both vertical and lateral directions.

Normalized shaping regularization for robust separation of blended data

Simultaneous source acquisition has attracted more and more attention from geophysicists because of its cost savings, whereas it also brings some challenges that have never been addressed before. Deblending of simultaneous source data is usually considered as an underdetermined inverse problem, which can be effectively solved with a least-squares (LS) iterative procedure between data consistency ([Formula: see text]-norm) and regularization ([Formula: see text]-norm or [Formula: see text]-norm). However, when it comes to abnormal noise that follows non-Gaussian distribution and possesses high-amplitude features (e.g., erratic noise, swell noise, and power line noise), the [Formula: see text]-norm is a nonrobust statistic that can easily lead to suboptimal deblended results. Although abnormal noise can be attenuated in the common source domain at first, it is still challenging to apply a coherency-based filter due to the sparse receiver or crossline sampling, e.g., that commonly found in ocean bottom node (OBN) acquisition. To address this problem, we have developed a normalized shaping regularization to make the inversion-based deblending approach robust for the separation of blended data when abnormal noise exists. Its robustness comes from the normalized shaping operator defined by the confidence interval of normal distribution, which minimizes the abnormal risk to a normal level to satisfy the assumption of LS shaping regularization. In special cases, the proposed approach will revert to the classic LS shaping regularization once the normalized coefficient is large enough. Experimental results on synthetic and field data indicate that the proposed method can effectively restore the separated records from blended data at essentially the same convergence rate as the LS shaping regularization for the abnormal noise-free scenario, but it can obtain better deblending performance and less energy leakage when abnormal noise exists.

Semipermanent ocean-bottom seismic node: Toward practical reservoir monitoring

Seismic reservoir monitoring has been found to be effective with recent ocean-bottom seismic techniques. The technology of ocean-bottom nodes can be extended to a semipermanent ocean-bottom-node (SPN) acquisition type, which is fixed on the seabed and activated on demand for reservoir monitoring. A newly developed SPN method allows a high-speed underwater optical to communicate with a remotely operated vehicle or an autonomous underwater vehicle to stably harvest seismic data on multiple repeat surveys. Long-term capabilities of deployment life, cumulative recording time, and internal clock characteristics are also key technologies for practical use of SPN acquisition. This is an alternative to fixed ocean-bottom cables that are currently a major tool of permanent reservoir monitoring. SPN acquisition will present more flexibility for receiver spreads, low installation cost, and fewer risks for asset management compared with existing seabed technologies.

Reverse-Time Migration of Converted S-Waves of Varying Densities

Ocean-Bottom Node (OBN) acquisitions provide both non-converted and converted reflection energy. There is a clear advantage to independently imaging both P- and S-waves, as they provide more information collectively than either does alone. In many conventional converted-wave pre-stack migration algorithms, density is treated as a constant, which is not the real-life case on earth. S-wave velocity and density information is crucial for hydrocarbon detection because it helps in the identification of pore-filling fluids. In this paper, we focused on the effect of density on imaging, and developed a method of reverse-time migration (RTM) on converted s-waves of varying densities (VD-RTMCS). Phase correction was required prior to pre-stack migration to avoid constructive interference between data from adjacent sources. Synthetic data examples showed that when density variations were included, image profiles showed advantages in signal-to-noise ratio, vertical resolution and imaging of complex structures.

Common reflection point stacking for ocean-bottom node data

Due to the asymmetrical ray paths caused by the large elevation differences between source and receiver locations in ocean-bottom node (OBN) survey, conventional common midpoint (CMP) stacking is unsuitable for processing OBN data. To mitigate this problem, we propose a common reflection point (CRP) stacking method, which enables us to efficiently produce accurate CRP-stacked image and stacking velocity model for subsequent processing workflow. For each input trace, we estimate the samples representing the reflection points in the output time section using stacking velocity, and then use a modified double-square-root (DSR) formula to map the amplitudes of input trace to these samples, which are progressively accumulated to form moveout-corrected CRP gathers. We can save computational costs by restricting the samples that need to be processed based on OBN reflection geometry, and use conventional moveout analysis of the CRP gathers to iteratively update the stacking velocity model. With tests on synthetic and field-data examples, we demonstrate the advantages of the proposed CRP stacking over conventional CMP stacking.

A study of full waveform inversion of seismic velocity structure under a rugged seafloor by using joint OBN and VSP synthetic seismic data

A numerical study of full waveform inversion (FWI) of seismic velocity structure was carried out by using synthetic ocean-bottom node (OBN) and vertical seismic profile (VSP) data. Based on an undulating seafloor modified from the commonly known Marmousi2 model, seismic forward modeling was performed to synthesize seismic P-wave data for the study. FWI experiments were performed using synthetic VSP, OBN and combined VSP + OBN data, separately, for the inversion of the velocity structure. The results show that the joint inversion of using the combined VSP + OBN synthetic data resulted in a very good velocity structure. Its accuracy is significantly higher than either using the VSP or OBN data alone. This suggests that the joint FWI using combined VSP + OBN data is a better image processing technique for the rugged seabed and complex structure below.

High frequency full waveform inversion as an interpretation solution

The amount of available data to help us characterise the subsurface is ever increasing. Large seismic surveys, long offsets, multi- and full-azimuth datasets, including 3D and 4D, marine, ocean-bottom nodes and extremely high fold land surveys, are now common. In parallel, computing power is also increasing and, in combination with better data, this enables us to develop better tools and to use better physics to build models of the subsurface. Wave-equation based techniques, such as full waveform inversion (FWI), have therefore become a lot more practical. FWI uses the entire wavefield, including refractions and reflections, primaries and multiples, to generate a refined, high resolution Earth model. This technique is now commonly used at lower frequencies (up to 12 Hz) to derive more accurate models for improved seismic imaging and reduced depth conversion uncertainty. By including higher frequencies in FWI, we can attempt to resolve for finer and finer details. FWI models using the entire bandwidth of the seismic data constitute an interpretation product in itself, with applications in both structural interpretation and reservoir characterisation. Incorporating more physics within the FWI implementation, combined with modern supercomputer facilities, promises to increase the focus on very high frequency FWI in the coming years. In this paper, through a series of field examples, we illustrate the applications and rewards of high frequency FWI: from improved imaging, improved quantitative interpretation and depth conversion to a direct interpretation of the FWI models.

Marine vibrators: the new phase of seismic exploration

ABSTRACTMarine seismic vibrators are generally considered to be less intrusive than airguns from an environmental perspective. This is because they emit their energy spread out in time, rather than in a single, high‐intensity pulse. There are also significant geophysical benefits associated with marine vibrators, and they stem from the ability to specify in detail the output acoustic waveform. The phase can be specified independently at each frequency. Such detailed control cannot be achieved with conventional airgun sources, where the phase can only be modified using simple overall time delays. The vibrator phase can be employed in several different ways: it can be applied to the overall source phase in a sequence so that it varies from one source point to the next; it can be applied to the individual vibrators within the source array so the source directivity is changed; it can be applied to the overall source phase of each source in a simultaneous source acquisition. Carefully designed phase sequences can attenuate the residual source noise, and this in turn allows extra source points to be interleaved between the conventional ones. For these extra source points, the relative phase of the vibrators within the array can be chosen to create a transverse gradient source, which illuminates the earth predominantly in directions out of the plane of the sail line without left/right ambiguity. If seismic vibrator data are acquired using interleaved conventional and transverse gradient sweeps, more information is collected per kilometre of vessel travel than is the case in conventional acquisition. This richer data acquisition leads to the possibility of acquiring all the necessary seismic data in a shorter time. Three‐dimensional reconstruction techniques are used to recover the same image quality that would have been obtained using the conventional, more time‐consuming acquisition. For a marine vibrator to be suitable for these techniques it must, in general terms, have ‘high fidelity’. The precise device specifications are defined through realistic end‐to‐end simulations of the physical systems and the processing. The specifications are somewhat more onerous than for a conventional vibrator, but they are achievable. A prototype vibrator that satisfies these requirements has been built. In a simulated case study of a three‐dimensional deep‐water ocean bottom node survey, the seismic data could have been acquired using marine vibrators in one third of the time that it would have taken using airguns.

3D acoustic least-squares reverse time migration using the energy norm

We have developed a least-squares reverse time migration (LSRTM) method that uses an energy-based imaging condition to obtain faster convergence rates when compared with similar methods based on conventional imaging conditions. To achieve our goal, we also define a linearized modeling operator that is the proper adjoint of the energy migration operator. Our modeling and migration operators use spatial and temporal derivatives that attenuate imaging artifacts and deliver a better representation of the reflectivity and scattered wavefields. We applied the method to two Gulf of Mexico field data sets: a 2D towed-streamer benchmark data set and a 3D ocean-bottom node data set. We found LSRTM resolution improvement relative to RTM images, as well as the superior convergence rate obtained by the linearized modeling and migration operators based on the energy norm, coupled with inversion preconditioning using image-domain nonstationary matching filters.

Advances in 4D Seismic and Geophysical Monitoring of Deepwater Fields

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 27828, “Advances in 4D Seismic and Geophysical Monitoring of Deepwater Fields,” by Kanglin Wang, Paul Hatchell, David Chalenski, and Jorge Lopez, Shell, prepared for the 2017 Offshore Technology Conference, Houston, 1–4 May. The paper has not been peer reviewed. Copyright 2017 Offshore Technology Conference. Reproduced by permission. Integrated surveillance is critical for understanding reservoir dynamics and improving field management. A key component of the surveillance is areal monitoring of subsurface changes by use of time-lapse geophysical surveys such as 4D seismic. The complete paper reviews the advances in these technologies with recent examples from the Gulf of Mexico (GOM) and deepwater Brazil. Data-Quality Improvement 4D seismic has played a pivotal role in monitoring offshore fields for some time. However, until recently, its application in the GOM had been limited, largely because the effects of the Loop Current and infrastructures make it difficult to repeat the feathering of streamers used in conventional 4D-seismic acquisition. The key for 4D success is to repeat everything in baseline and monitor surveys to make sure the time-lapse difference observed in the data reflects real subsurface changes rather than differences in data-acquisition conditions or processing work flows. To solve the challenge of streamer-positioning repeatability, an operator used ocean-bottom nodes (OBNs) to achieve highly repeated surveys at the Mars Field, and excellent 4D results were obtained. Since then, 4D seismic has been deployed successfully at the portfolio scale in the GOM and that operator’s 4D surveillance strategy has been changed from streamer seismic to ocean-bottom seismic (OBS), which includes OBNs and ocean-bottom cables. In addition to source and receiver positions, other conditions in data acquisition can play important roles in 4D repeatability—for example, the variation of water properties during a seismic survey and between different surveys including water depth (tides) and seismic velocity in water. Such variations have been a well-known issue that limits the repeatability of 4D seismic, in particular for OBS data where multiple migration is often used. Seismic travel-time analysis is traditionally used to estimate errors and make corrections, but the process is often complicated by coupled factors including tides, water velocities, positioning errors, and the clock drift of OBNs, which collectively make it difficult to achieve precise water static corrections. To address this challenge, a seafloor device called the Pressure Inverted Echo Sounder (PIES) was developed for direct measurement and continuous monitoring of water- column properties during marine seismic surveys. A PIES is deployed at the seafloor and monitors two-way water time by transmitting an acoustic signal and measuring the time it takes to be reflected back from the surface. Such information has been used to make travel-time corrections of seismic data for enhanced data repeatability in the operator’s 4D processing projects.