Abstract 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.

Abstract Cepstral decomposition is beneficial for highlighting certain geological features within the particular quefrency bands which may be deeply buried within the wide quefrency range of the seismic data. Converting seismic traces into the corresponding cepstrum components can better analyse some characteristics of underground strata than the traditional spectral decomposition methods. We propose the sliding windowed differential cepstrum–based coherence analysis approach to delineate the fault features. First, the data are decomposed using a sliding windowed differential cepstrum, which results in multi‐cepstrum data of corresponding quefrency of certain bandwidth. These different multi‐cepstrum data may highlight the different stratigraphic features in a certain quefrency band. We select the first‐order common quefrency volume as the featured attribute. Then, eigenstructure‐based coherence is applied on the first‐order common quefrency data volume to statistically obtain the fault detection result with a finer and sharper image. Synthetic data and field data examples show that the proposed method has the ability to better visualize all the possible subtle and minor faults present in the data more accurately and discernibly than the traditional coherence method. Compared with the ant‐tracking method, the proposed method is more effective in revealing the major faults. It is hoped that this work will complement current fault detection methods with the addition of the cepstral‐based method.

Abstract The extension of the seismic bandwidth to lower frequencies enhances impedance contrasts that can be poorly represented by the broadband acquisition wavelet. Furthermore, long filters that are used to shape the wavelet of processed data can cause issues with noise, phase and interference between seismic events. In this paper, we use a mathematical technique known as mollification to resolve impedance variations with the highest detail allowed by the bandwidth of the data. The mollifier is integrated and windowed to match the low‐frequency content of the data to yield a convenient conversion to relative impedance. Synthetic data created from wedge models show that the windowed mollifier provides an improved representation of the impedance profile. This is replicated by application to an acoustic well log and a regular seismic dataset recorded in the Southern North Sea as well as a broadband dataset recorded in the North Sea.

Abstract Time‐lapse seismic data processing is an important technique for observing subsurface changes over time. The conventional time‐lapse seismic exploration has been conducted using a large‐scale exploration system. However, for efficient monitoring of shallow subsurface, time‐lapse monitoring based on the small‐scale exploration system is required. Small‐scale exploration system using a sparker source offers high vertical resolution and cost efficiency, but it faces challenges, such as inconsistent waveforms of sparker sources, inaccurate positioning information and a low signal‐to‐noise ratio. Therefore, this study proposes a data processing workflow to preserve the signal and enhance the repeatability of small‐scale time‐lapse seismic data acquired using a sparker source. The proposed workflow has three stages: pre‐stack, post‐stack and machine learning–based data processing. Conventional seismic data processing methods were applied to enhance the quality of the sparker seismic data during the pre‐stack data processing stage. In the post‐stack processing stage, the positions and energy correction were performed, and the machine learning–based data processing stage attenuated random noise and applied a matched filter. The data processing was performed using only the seismic signals recorded near the seafloor, and the results confirmed the improvement in the repeatability of the entire seismic profile, including that of the target area. According to the repeatability quantification results, the predictability increased and the normalized root mean square decreased during data processing, indicating improved repeatability. In particular, the repeatability of the data was greatly improved through vertical correction, energy correction and matched filtering approaches. The processing results demonstrate that the data processing method proposed in this study can effectively enhance the repeatability of high‐resolution time‐lapse seismic data. Consequently, this approach could contribute to a more accurate understanding of temporal changes in subsurface structure and material properties.

Abstract 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.

Abstract We present a 3D numerical modelling analysis evaluating the deployment of a borehole electromagnetic measurement tool to detect and image a stimulated zone at the Utah Frontier Observatory for Research in Geothermal Energy geothermal site. As the depth to the geothermal reservoir is several kilometres and the size of the stimulated zone is limited to several 100 m, surface‐based controlled‐source electromagnetic measurements lack the sensitivity for detecting changes in electrical resistivity caused by the stimulation. To overcome the limitation, the study evaluates the feasibility of using a three‐component borehole magnetic receiver system at the Frontier Observatory for Research in Geothermal Energy site. To provide sufficient currents inside and around the enhanced geothermal reservoir, we use an injection well as an energized casing source. To efficiently simulate energizing the injection well in a realistic 3D resistivity model, we introduce a novel modelling workflow that leverages the strengths of both 3D cylindrical‐mesh‐based electromagnetic modelling code and 3D tetrahedral‐mesh‐based electromagnetic modelling code. The former is particularly well‐suited for modelling hollow cylindrical objects like casings, whereas the latter excels at representing more complex 3D geological structures. In this workflow, our initial step involves computing current densities along a vertical steel‐cased well using a 3D cylindrical electromagnetic modelling code. Subsequently, we distribute a series of equivalent current sources along the well's trajectory within a complex 3D resistivity model. We then discretize this model using a tetrahedral mesh and simulate the borehole electromagnetic responses excited by the casing source using a 3D finite‐element electromagnetic code. This multi‐step approach enables us to simulate 3D casing source electromagnetic responses within a complex 3D resistivity model, without the need for explicit discretization of the well using an excessive number of fine cells. We discuss the applicability and limitations of this proposed workflow within an electromagnetic modelling scenario where an energized well is deviated, such as at the Frontier Observatory for Research in Geothermal Energy site. Using the workflow, we demonstrate that the combined use of the energized casing source and the borehole electromagnetic receiver system offer measurable magnetic field amplitudes and sensitivity to the deep localized stimulated zone. The measurements can also distinguish between parallel‐fracture anisotropic reservoirs and isotropic cases, providing valuable insights into the fracture system of the stimulated zone. Besides the magnetic field measurements, vertical electric field measurements in the open well sections are also highly sensitive to the stimulated zone and can be used as additional data for detecting and imaging the target. We can also acquire additional multiple‐source data by grounding the surface electrode at various locations and repeating borehole electromagnetic measurements. This approach can increase the number of monitoring data by several factors, providing a more comprehensive dataset for analysing the deep‐localized stimulated zone. The numerical analysis indicates that it is feasible to use the combination of the energized casing and downhole electromagnetic measurements in monitoring localized stimulated zone at large depths.

Abstract 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.

Abstract The calculation of the vertical derivatives of potential field methods can be carried out in a stable manner by Tikhonov regularization, but this procedure requires the appropriate selection of a regularization parameter. For this purpose, we introduce a criterion based on Morozov's discrepancy principle that uses a preliminary approximation given by the vertical derivative of the smoothed data. The smoothing may be performed by a physical or a mathematically based low‐pass filter. The filtered data are computed only for estimating the regularization parameter; once it is found, we evaluate the regularized vertical derivative from the original data (not from the smoothed one) in the frequency domain. We verified from experiments with noise‐corrupted synthetic data, as well as gravity and magnetic field data, that the regularized vertical derivative has about the same smoothness as the one obtained from filtered data, but true anomalies are more easily distinguished from noise and the shapes of the anomalies are better preserved.