Microseismic monitoring is widely used in the analysis of engineering disasters such as mines and tunnels, all of which are based on microseismic source parameters. The calculation of microseismic source spectrum is the basis of source parameter calculation. Once the source spectrum is determined, most of the source parameters can be calculated accordingly. However, research into the calculation process and method of microseismic source spectra is limited. Therefore, we investigated the basic steps and methods of microseismic source spectrum calculation in detail. This includes four main steps: waveform processing and source location; signal spectrum calculation; signal spectrum correction and source spectrum determination. Signal processing involves removing the instrument response, filtering and arrival picking with localisation to provide basic parameters for subsequent calculations. Signal spectrum calculation involves not only common methods such as the discrete Fourier transform, but also the lag-window spectral technique and multi-taper methods. Signal spectrum correction involves geometric spreading, site effects, and attenuation, which are all influenced by multiple and complex factors. Source spectrum determination initially requires the theoretical source spectrum model to be determined, followed by the selection of the objective function and fitting method. This study briefly analyses the impact of these factors on the calculation of the microseismic source spectrum and suggests possible future research directions. These results can be used as a reference for calculating the source spectrum, thereby establishing a foundation for calculating source parameters and ultimately providing theoretical support for standardising and normalising engineering microseismic monitoring and the quantitative warning of engineering disasters.

With the deepening of exploration and development of unconventional oil and gas reservoirs, especially pore-fracture reservoirs with both pore and fracture reservoir structures have become a research hotspot. Due to the complexity of geological conditions and the band limit of seismic data, these reservoirs often show hidden characteristics on longitudinal seismic data, and it is very necessary to carry out multi-wave seismic response analysis of pore-fracture reservoirs. In this paper, we combine the anisotropic fluid substitution theory of Gassmann equation and Thomsen anisotropic parameter theory to carry out equivalent HTI medium petrophysical modeling; use 2.5-dimensional staggered-grid finite-difference method to carry out highly efficient elastic fluctuation orthotropic simulation; and analyze the characteristics and sensitivity of the multi-wave AVO and AVAz responses in a variety of geological conditions. The model characterization shows that the PP wave near-deviation amplitude and PS wave far-deviation amplitude are more sensitive to the changes of fracture density and porosity, which can better reflect the changes of the two parameters; the amplitudes of different offset distances have similar characteristics of the changes with water saturation, and there is a sudden change near 90%; the PP wave AVAz characteristics show that the amplitude amplitude amplitude is near-deviation and far-deviation, and the PS wave shows the opposite trend, and all of them are periodic changes, which can indicate the The PS wave AVAz characteristics show an opposite trend in amplitude, and both of them change periodically, which can indicate the fracture orientation; the defining equation of the PS wave tuned thickness is deduced, which complements the characterization of the multi-wave tuned thickness. The significance of the pore-fracture type reservoir response characteristics to the actual data interpretation is summarized, which provides an important reference for understanding the fluctuation response characteristics of complex pore-fracture reservoirs, helps to understand the actual seismic data phenomena of complex pore-fracture reservoirs, and can effectively assist the design of the interpretation scheme to improve the accuracy of the interpretation.

Geophysical exploration has a wide range of applications in the fields of energy exploration, environmental monitoring and engineering survey by quantitatively processing the observed field source data for subsurface target detection. However, the geophysical exploration method using a single data has the problems of multiple solutions and low resolution in the inversion process. Therefore, joint inversion by synthesizing multiple geophysical observation data has more significant advantages than single inversion. Electromagnetic exploration and seismic exploration are two kinds of geophysical exploration methods based on different physical mechanisms, which typically differ in spatial resolution and sensitivity to the target. Therefore, the combination of the two can significantly improve the reliability of the inversion results. As an important means for quantitatively interpreting electromagnetic and seismic data, joint electromagnetic and seismic inversion can effectively reduce the multiple solutions of single data inversion and improve the prediction accuracy of formation parameters. This paper firstly summarizes the classification of electromagnetic and seismic joint inversion and its development history, then describes the principle and application examples of joint inversion method, and finally discusses its development opportunities and looks forward to the future research direction.

Distributed Acoustic Sensing (DAS) technology leverages the linear response of Rayleigh backscattered light in optical fibers to external acoustic fields, enabling distributed sensing and collection of vibrations. This technology has seen extensive application in seismic exploration. However, conventional straight optical fibers exhibit sensitivity primarily along the fiber axis, limiting their effectiveness in detecting vertically incident seismic waves, thus constraining their use in surface seismic surveys. To address this limitation, a Helically Wound Cable-Based Distributed Acoustic Sensing (HWC-DAS) technique has been proposed. In this approach, the fiber is helically wrapped around a deformable elastic medium, improving directional sensitivity and enhancing its ability to detect vertically incident reflections, significantly boosting sensitivity. Nevertheless, systematic comparisons between HWC-DAS and traditional seismic geophones remain sparse, and the differences in their sensitivity, Signal-to-Noise Ratio (SNR), and frequency-dependent responses are not yet clearly understood. To fill this knowledge gap, we conducted controlled laboratory experiments, including shaking table and vibration-sensing tests, to systematically compare the performance of HWC-DAS with conventional seismic geophones. Results from shaking table experiments indicate that HWC-DAS exhibits vibration response capabilities comparable to those of geophones across various frequency bands. Furthermore, vibration-sensing tests demonstrated that HWC-DAS achieves higher sensitivity and improved SNR compared to single-point geophones. Our study validates the effectiveness and feasibility of HWC-DAS for seismic exploration through laboratory experimentation, laying foundational groundwork for its practical deployment in industry.

In both natural and industrial settings, the issue of underwater gas leakage has received increasing attention. This encompasses leaks resulting from ocean engineering endeavors as well as those that occur naturally. Such leaks have emerged as a major challenge for the protection of marine environments. To accurately obtain information from these emergencies and implement prompt responses, experts across various disciplines have been suggesting and investigating novel, dependable methods for detecting underwater gas leaks over the last few decades. Building upon thorough and detailed research of existing technologies, this article examines carrier detection and marine environmental detection, systematically evaluates the current leading technologies for detecting seabed gas leaks. Furthermore, the article offers a detailed analysis of the various challenges currently faced by gas leak detection and anticipates future development trends, with the aim of providing reference and insights for research and practice in related areas.

To address the three-dimensional (3D) forward modeling problem of transient electromagnetic fields for grounded-wire source, this paper explores a finite element forward modeling method that employs a frequency-time transformation and background-scattered field separation strategy. It utilizes the vector finite element theory, and the 3D model is discretized using structured hexahedral mesh. Subsequently, the frequency-domain numerical response is computed using the MUMPS solver. Ultimately, the time-domain transient electromagnetic response is derived via cosine transformation. On this basis, the reliability of the forward algorithm is validated using both a one-dimensional layered model and an open three-dimensional model, and its computational accuracy is assessed. Theoretical examples show that the calculation results of the 3D transient electromagnetic forward modeling proposed in this paper are accurate and can meet the calculation requirements of 3D inversion research.

Seismic inversion, a critical method for inferring subsurface petrophysical parameters (acoustic impedance) from seismic data, plays a vital role in hydrocarbon exploration and geological research. However, conventional seismic inversion methods heavily rely on low-frequency background models, exhibit sensitivity to noise interference, and suffer from low computational efficiency, making them inadequate for high-precision inversion under complex geological conditions.In recent years, Convolutional Neural Networks (CNN) have been widely adopted in seismic impedance inversion due to their strong nonlinear modeling capabilities and end-to-end learning approaches, enabling effective mapping of seismic data to impedance values. Nevertheless, deep CNN architecture still face challenges such as gradient vanishing, gradient explosion, and overfitting, which compromise the stability and accuracy of inversion results. To address these limitations, this study proposes a ResUNet-based inversion approach by integrating residual blocks into a UNet framework, thereby mitigating gradient vanishing and information loss issues while enhancing inversion accuracy and stability. Synthetic seismic data generated through forward modeling were used to train the ResUNet model, and real seismic data were subsequently input into the trained network to derive impedance inversion results. However, the intelligent inversion outputs may exhibit discrete artifacts and "spiking" phenomena near complex geological features (fault), impairing the smoothness and continuity of the results. To optimize the inversion outputs, a post-processing smoothing technique was further introduced to suppress anomalies and improve stability. Theoretical model testing and real-data validation demonstrate that the ResUNet combined with smoothing effectively enhances the precision and stability of seismic acoustic impedance inversion, offering a feasible novel method for intelligent seismic inversion applications.

The marine exploration environment is generally regarded as a fluid-solid boundary coupling medium. High-precision imaging of the fluid-solid boundary coupling medium can be achieved by using the decoupled elastic wave field for reverse-time migration. Traditional elastic wave decoupling utilizes the Helmholtz principle, but the separated P-waves and S-waves have phase and amplitude issues, which seriously affect the final imaging quality. This paper starts from the first-order velocity-stress elastic medium wave equation, separates the full elastic wave field into pure P-waves and pure S-waves to construct a new coupling equation, avoiding the phase and amplitude problems and crosstalk artifacts caused by the traditional Helmholtz decomposition; analyzes the displacement and stress continuity conditions at the boundary of the fluid-solid boundary coupling medium, and establishes the acoustic-elastic coupling vector separation equation; compares the numerical simulation results with the acoustic wave equation to verify the effectiveness and accuracy of the proposed acoustic-elastic coupling vector separation equation forward modeling method, and compares the results with the conventional reverse-time migration imaging method in a complex seabed model to verify the reliability of the reverse-time migration imaging results.

Carbon Capture, Utilization, and Storage (CCUS) has emerged as a effective strategy for mitigating atmospheric CO₂ emissions. However, the large-scale subsurface injection of CO₂ may induce ground surface deformation, potentially compromising the long-term integrity of CO₂ storage. To investigate surface displacement patterns in CCUS project areas following CO₂ injection, this study employed the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to analyze 45 ascending Sentinel-1A images acquired between January 2022 and August 2024, enabling comprehensive deformation monitoring over a 2.5-year period in a Chinese CCUS geological storage site. Recognizing the impact of tropospheric delay errors on InSAR measurements, we developed an enhanced atmospheric delay correction approach synergizing Global Navigation Satellite System (GNSS) data and ERA5 reanalysis data, specifically optimized for small-scale regional applications. Analysis of the phase-unwrapped interferograms confirms that our GNSS-constrained atmospheric correction approach significantly reduces tropospheric delay artifacts in localized interferometric observations. The derived InSAR deformation field reveals distinct surface displacement patterns in the CO₂ injection zone, with measured vertical deformation rates ranging from 0 to 10 mm/a. Deformation time series analysis at monitoring points adjacent to injection wells reveals a consistent response: initial surface uplift immediately following CO₂ injection, followed by gradual subsidence after several months. This pattern was confirmed through comparative analysis of InSAR-derived vertical displacements (converted from LOS measurements) and independent GNSS observations. This study demonstrates that the synergistic use of GNSS and InSAR technologies enables precise monitoring of millimeter-scale surface deformation in CCUS operational areas. The GNSS infrastructure serves dual purposes: (1) enhancing InSAR measurement accuracy through tropospheric delay correction, and (2) providing independent validation of InSAR-derived deformation results. These findings underscore the critical importance of integrated geodetic monitoring for ensuring the safety and efficacy of CO₂ geological storage operations.

In shallow geological exploration, drilling and geophysical prospecting are two distinct technical methods that play different roles in the acquisition of geological and geophysical data. With the continuous advancement of modern science and technology, the direction is towards green, intelligent, and precise exploration. Integrating drilling and geophysical prospecting technologies can achieve the acquisition of multiple information parameters, such as the structure and physical properties of rock and soil layers, in a single borehole. This integration provides a foundation for the construction of transparent geological models and the precise identification of underground space information. This paper combines the current state of research and development on integrated drilling and geophysical prospecting technologies and equipment to analyze future development trends of intelligent integrated drilling and geophysical prospecting technologies and equipment for shallow layers. It posits that the current period is crucial for the transition from traditional exploration to green and intelligent exploration. By integrating artificial intelligence, big data, and intelligent transmission technologies, and improving traditional drilling processes, the advantages of combined drilling and geophysical prospecting technologies can be effectively leveraged. This can enhance the level of automated and intelligent exploration of shallow geological conditions, providing new technical support for geological disaster prevention, complex condition engineering exploration, and construction. The technical research and engineering practice significance are substantial. Additionally, the paper offers insights and understandings based on drilling-while-prospecting methods, technologies, equipment, and engineering practices to provide a reference for the future development of precise and intelligent geological exploration.