Geophysical Prospecting - Volume 73, Issue 3, 2025

The Kyushu–Palau Ridge and adjacent basins are ideal locations for investigating the formation and evolution of marginal seas and initiation of plate subduction. In this study, the tectonic–sedimentary features and crustal structure of the Kyushu–Palau Ridge and adjacent basins were investigated using newly obtained deep seismic reflection and borehole data. The initial mechanism of subduction in the West Philippine Sea and its tectonic evolution are discussed. Two sets of sedimentary strata with different provenances occur in the eastern Philippine Basin. The thickness of the lower strata is variable, and most of the sediment was sourced from island arc volcanism on the Kyushu–Palau Ridge. These strata thicken towards the Kyushu–Palau Ridge, and volcaniclastic rock aprons are developed near the foot of the Kyushu–Palau Ridge. The upper strata have a relatively uniform thickness and comprise fine‐grained, deep‐water marine sediments. The crustal thickness of the West Philippine and Parece Vela Basins is 6–7 km, which is similar to the global average thickness of oceanic crust. The Moho beneath the West Philippine Basin has a broad and undulating form that mimics the thickness of the oceanic crust beneath the sediments. The depth to the Moho decreases towards the Central Basin Spreading Center. The Moho beneath the Parece Vela Basin is planar, which is in contrast to the undulating nature of the oceanic crust base in this area. The West Philippine Basin may have been located at the northern margin of Australia in the Southern Hemisphere during the Mesozoic. It developed gradually in a continental margin arc as a result of Palaeogene inter‐arc and oceanic extension and contains fragments of continental crust. Seismic profiles and drillhole data in the West Philippine Basin reveal that compression occurred during the Eocene. Subduction along the paleo‐Izu–Bonin–Mariana arc may have been caused by the far‐field effects of the India–Asia collision. Subduction was accompanied by lateral propagation and a compressive stress field until the break‐up of the island arc at ca. 30 Ma.

High‐resolution shallow oceanic crust velocity models provide crucial information on the tectonothermal history of the oceanic crust. The ocean bottom seismometers record wide‐angle seismic reflection and refraction data to image deeper structures compared with streamer data set. However, most ocean bottom seismometers experiments produce low‐resolution velocity models with limited shallow crustal structure due to sparse ocean bottom seismometers spacing. Multichannel seismic data recorded by towed streamers provide complementary seismic images of the oceanic crust but yield little information on subseafloor velocity because most subseafloor refractions are masked by seafloor reflections. Therefore, it is difficult to obtain fine‐scale velocity structure of shallow upper oceanic crust with both ocean bottom seismometers and multichannel seismic data. Downward continuation technique redatumed the shots and receivers to the seafloor to collapse the seafloor reflections to the zero offset and extract refractions as first arrivals from nearly zero offset, enabling dense ray coverage at the shallow crust. We applied the downward continuation and traveltime tomography methods to two synthetic models, Marmousi and SEAM Phase I Salt models, to demonstrate the performance of the strategy in the situations of flat seafloor and rough seafloor topography. We conducted the first‐arrival traveltime tomography on downward continued towed‐streamer multichannel seismic data across a slow‐spreading ridge of the South China Sea, providing unprecedented details of shallow velocity structure in the sediments. The low velocity sediments revealed by traveltime tomography match well with the prestack depth migration profile.

The propagation of seismic waves in attenuating anisotropic media exhibits amplitude dissipation and phase dispersion. To describe its effects, the fractional Laplacian pure visco‐acoustic wave equations capable of producing stable and noise‐free wavefields have been derived. However, except for acoustic approximation, previous wave equations utilize the approximations with lower accuracy in simplifying the denominator of the approximate complex‐valued dispersion relation, resulting in reduced accuracy. To address this concern, we use a combination of complex stiffness coefficients to replace the denominator term of the approximate complex‐valued dispersion relation. This approximation effectively reduces the loss of accuracy caused by ignoring the influence of the velocity anisotropy parameter ε and the attenuation anisotropy parameter εQ in the denominator term, leading to a wave equation with high accuracy in media with large anisotropic parameters ε and δ. In addition, the new wave equation only contains two high‐order spatial partial derivatives and has high computational efficiency. Theoretical analysis and numerical examples demonstrate that the proposed pure visco‐acoustic tilted transversely isotropic wave equation outperforms the previous pure visco‐acoustic wave equation in terms of simulation accuracy. The newly developed wave equation is well suited for the application of Q‐compensated reverse time migration and full waveform inversion in attenuating anisotropic media.

We examine the value of the nine‐component seismic survey by generating the Kirchhoff depth migration images of compressional wave (P‐wave), converted wave (PS‐wave) and horizontally polarized shear wave (SH shear wave) data simulated from the SEAM II Barrett unconventional model. We first utilize full waveform inversion to obtain a P‐wave velocity model from P‐wave data and an S‐wave velocity model from SH‐wave data. Both P‐wave and SH‐wave data are generated with the maximum frequency of 20 Hz while assuming that the subsurface is isotropic. To implement full waveform inversion, we use a two‐dimensional time‐domain finite‐difference method and the L2 norm to measure the data misfit. We use both refractions and reflections in P‐ and SH‐wave data to reconstruct the P‐ and S‐wave velocity models from the surface to the reservoir. The inverted P‐ and S‐wave velocities contain the main features of the model (e.g., major faults and channels) but have some difficulties in estimating high‐frequency velocity variation within the first 300‐m depth of the model due to the frequency constraint. We then use the inverted P‐ and S‐wave velocities to generate Kirchhoff depth migration gathers and images from the P‐, PS‐ and SH‐wave data. The flat P‐ and SH‐wave common‐image offset gathers suggest that SH‐ and P‐wave full waveform inversion can generate adequate S‐ and P‐wave velocities for migration. Flat PS‐wave gathers and the clear PS‐wave migration image are also obtained using the inverted P‐ and S‐wave velocities simultaneously. This result indicates that obtaining S‐wave velocities from SH‐wave data can aid PS‐wave data processing and imaging. Moreover, the SH‐wave images and S‐wave images of the radial component provide better delineation of fault planes and small‐scale geobodies within the reservoir since the wavelength of the S‐wave is smaller compared to P‐wave when similar frequency ranges are recorded. Therefore, our study shows that S‐wave velocities can be successfully constructed by the two‐dimensional full waveform inversion application of the SH‐wave data. The subsequent imaging of multicomponent seismic data improves the delineation of certain unconventional reservoirs compared to the traditional P‐wave imaging.

Seismic technique is widely used to image the subsurface geology for oil and gas exploration. The image quality depends on the spatial sampling density. However, it is challenging and expensive to acquire high‐density seismic data, particularly in the marine environment. Distributed acoustic sensing data are increasingly used in data acquisition because of their low cost and dense spatial sampling. Here, we present a novel type of high‐density towed streamer based on distributed acoustic sensing technology and report the results of a sea trial. This sea trial was conducted in a gas hydrate province as the major driver to develop this technique is to better characterize gas hydrate deposits. Throughout the experiment, several high‐quality datasets were obtained, and parameters like source energies and filler materials were examined. The trace interval of distributed acoustic sensing streamer data reaches 1 m, which is a significant improvement over the usual 3.125 or 6.25 m in the conventional towed streamer. A detailed analysis was carried out from three different perspectives: amplitude, noise and frequency. One of the datasets was further processed following a routine workflow to obtain the final image. Though direct comparison with the image obtained by a conventional towed streamer along a coincident line is not available, the comparison with the previous image from a nearby line shows the improvement in resolution. The final image is of good quality and the presence of gas hydrate could be inferred. The sea trial results demonstrate the feasibility of the use of a distributed acoustic sensing optical fibre streamer in acquiring high‐density seismic data in the marine environment.

Removal of water‐layer‐related multiples in shallow water remains a challenge due to a lack of near‐offset data. We have developed a shallow water multiple attenuation approach by constructing the impulse response of the water bottom for the removal of water‐layer‐related multiples. The impulse response of the seafloor is formed by the convolution of its traveltime response and amplitude response. It uses the superposition of the original shallow water demultiple operator to obtain traveltime information and uses the deconvolution method to estimate its dynamic components from the original shallow water demultiple operator to build new operators. The impulse response can be correctly constructed not only for near offsets but for moderate and far offsets as well. A three‐term subtraction strategy by predicting source‐side, receiver‐side and both source‐side and receiver‐side multiples is adopted in our approach for attenuating shallow multiples without over‐prediction. Numerical examples with two synthetic datasets and 2D and 3D field datasets demonstrate that our approach gives a desirable performance.

Seismic wave forward modelling is a crucial method for studying the propagation characteristics of seismic waves in subsurface media and is a key component of full waveform inversion. Compared to time‐domain forward modelling, frequency‐domain forward modelling offers advantages such as not being constrained by stability limits and reducing the dimension of the solution space. However, forward algorithms based on the rotation coordinate system in the frequency domain cannot adapt to situations with unequal spatial sampling intervals. To enhance the adaptability of the forward modelling algorithm in the frequency domain, we derived a 21‐point finite‐difference scheme based on the average derivative method and calculated the difference coefficients and dispersion conditions. Additionally, to address the significant computational cost in frequency domain forward modelling, we developed an improved 25‐point finite‐difference scheme. The improved 25‐point format is more accurate than the conventional 25‐point format. Building on this foundation, we applied the two derived differential schemes to full waveform inversion to synthesize the shot records of the inversion data. Additionally, we introduced a frequency compensation factor into the gradient processing, which effectively compensates for the deep layer while suppressing noise in the shallow gradient field. Finally, we demonstrated the effectiveness of our approach through a full waveform inversion application on the Marmousi model showcasing its capability in invertig fine subsurface structures.

The reflection waveform inversion has the capability to reconstruct the background velocity model using only the reflection data by employing a migration/demigration process. Utilizing the waveform discrepancy to update the background velocity model, the conventional reflection waveform inversion method heavily relies on the true‐amplitude migration/demigration technique to reproduce the primary amplitude information from the observed reflections. We can reproduce the amplitude of observed reflections by performing least‐squares reverse time migration to estimate the reflectivity in each iteration. However, this strategy is quite time‐consuming. To avoid the need for the true‐amplitude migration/demigration or least‐squares reverse time migration, we develop an amplitude‐independent reflection waveform inversion method that uses an envelope‐normalized objective function. The envelope‐normalized waveform difference can extract the phase residuals accurately as a function of time. Compared with the global energy–normalized misfit, our proposed envelope‐normalized objective function is essentially a phase‐matched measurement. At the same time, due to the amplitude independence of our proposed objective function, the subsequent weak reflections contribute with a similar weight to the total value of the misfit as the strong early reflections do. This makes it possible to recover the deep subsurface velocity. Synthetic data of the Sigsbee model and marine streamer field data applications validate that our amplitude‐independent reflection waveform inversion method can further improve the resolution and accuracy by aligning the reflection events of synthetic and observed data phase to phase without the need to perform true‐amplitude migration/demigration or least‐squares reverse time migration as in conventional reflection waveform inversion.

The computational efficiency of cross‐correlation reflection waveform inversion can be improved by utilizing the outcomes of reverse time migration instead of the least‐squares reverse time migration results in each iteration. However, the inversion effect of cross‐correlation reflection waveform inversion needs to be optimized as the inversion results may not be optimal. The conventional cross‐correlation operator tends to produce interference values that can compromise the precision of time‐shift estimations. Moreover, the time shift obtained through dynamic image warping can exhibit spiky disturbances, making it difficult to determine accurate time‐shift values. These challenges can cause the inversion process to converge to a local minimum, thereby affecting the quality of the inversion results. To address these limitations, this paper proposes a new approach called cross‐correlation reflection waveform inversion based on dynamic image warping. The proposed method integrates a weighted norm derived from dynamic image warping to effectively regulate the time‐shift values throughout the inversion process. The effectiveness of the proposed cross‐correlation reflection waveform inversion based on the dynamic image warping method is validated through simulations using a simple two‐layer model and a resampled Sigsbee 2A model. A comparative analysis is performed to evaluate the performance of cross‐correlation reflection waveform inversion based on dynamic image warping in mitigating cross‐correlation interference, demonstrating its superior capability compared to the conventional cross‐correlation reflection waveform inversion method.

Elastic full‐waveform inversion enables the quantitative inversion of multiple subsurface parameters, significantly enhancing the interpretation of subsurface lithology. Simultaneously, with the ongoing advancements in ocean bottom node technology, the application of elastic full‐waveform inversion to marine ocean bottom node data is receiving increasing attention. This is attributed to the capability of ocean bottom node to acquire high‐quality four‐component data. However, elastic full‐waveform inversion of ocean bottom node data typically encounters two challenges: First, the presence of low S‐wave velocity layers in the seabed leads to weak energy of converted S‐waves, resulting in significantly poorer inversion results for S‐wave velocity compared to those for P‐wave velocity; second, the cross‐talk effect of multiple parameters further exacerbates the difficulty in inverting S‐wave velocity. To effectively recover the S‐wave velocity using ocean bottom node data, we modify the S‐wave velocity gradient in conventional elastic full‐waveform inversion to alleviate the impact of cross‐talk from multiple parameters on the inversion of S‐wave velocity. Furthermore, to invert for density parameters, we adopt a two‐stage inversion strategy. In the first stage, P‐wave and S‐wave velocities are updated simultaneously with a single‐step length. Because the initial density model is far from the true one, density is updated using an empirical relationship derived from well‐log data. In the second stage, velocities and density are updated simultaneously with multi‐step length to further refine the models obtained in the first stage. The high effectiveness of the improved elastic full‐waveform inversion is validated by numerical examples.

Wide azimuth seismic data play an important role in deep reservoir prediction. According to the Paleogene clastic rock reservoir prediction, the high‐density and wide azimuth 3D seismic data acquisition of ocean bottom nodes was first carried out in a Chinese offshore oilfield in 2019. After high precision amplitude‐preserving processing, we obtained the high‐quality wide azimuth gathers. However, the research on anisotropy and reservoir prediction using wide azimuth seismic data mainly focuses on carbonate and bedrock intervals, which is not suitable for clastic rock reservoir prediction. Therefore, this paper innovatively proposes a clastic rock reservoir prediction method, which studies prestack reservoir prediction in the ray parameter domain based on wide azimuth ocean bottom node seismic data. Based on the azimuth gathers, we can obtain elastic parameters through prestack amplitude versus offset inversion, which is used to characterize the reservoir, so it is significant to obtain high precision elastic parameters in order to get highly reliable reservoir prediction results. In this paper, we develop an amplitude versus offset inversion method based on the Bayesian theory in ray parameter domain, the output of which is density, P‐wave impedance and Vp/Vs. These elastic parameters have high precision, and density data are valuable input for reservoir characterization because they are sensitive to the lithology of clastic rock reservoir at different orientations. In ray parameter domain inversion, the ray path of seismic wave propagation is considered polyline, which is more consistent with the actual situation; thus, extracted amplitudes of P gathers used in inversion are more accurate. In addition, the reflection coefficient formula in ray parameter domain has higher precision when the incident angle is large. The inversion based on the Bayesian theory can improve the stability of the inversion. Test on the actual data shows that the result of ray parameter domain inversion with a Bayesian scheme is more accurate, stable and reliable. Based on the above high precision density inversion results, an innovative wide azimuth data reservoir prediction technology based on elliptical short‐axis fitting was proposed. The actual prediction of the deep reservoir in the Bohai oilfield shows that sand thickness fitting prediction results in the short axis can best match the actual drilling sandstone thickness. The coincidence rate is 86% and the short‐axis fitting results are more in agreement with geological laws. Theoretical research and practical applications have shown that this method is feasible and effective, with high prediction accuracy, computational efficiency and strong application value.

Limitations in acquisition technologies lead to insufficient low‐frequency signals in field seismic data. Local optimization methods are the common approaches for full‐waveform inversion. Inaccurate initial velocity models and lack of low‐frequency signals in seismic data typically cause the local‐gradient‐based full‐waveform inversion to converge to a local minimum due to cycle‐skipping. The existing energy‐based objective functions can generate artificial low‐frequency signals successfully by squaring the pressure but overlook the law of energy conservation, which may mislead model updates. To overcome this issue, we combine acoustic wave potential energy and kinetic energy to develop a new objective function that fits the acoustic wave energy. The new acoustic‐wave‐energy‐based full‐waveform inversion considers the law of energy conservation. The new system creates low‐frequency signals to avoid cycle‐skipping and produce an accurate smooth background velocity model, which provides a sufficient starting model for conventional full‐waveform inversion. Numerical examples demonstrate that the combination of acoustic‐wave‐energy‐based full‐waveform inversion and conventional full‐waveform inversion can deliver more faithful and accurate final results than conventional full‐waveform inversion alone.