pure and applied geophysics最新文献

The need for reconstruction of the distribution of physical properties like dielectric permittivity and electrical conductivity of shallow subsurface sedimentary architecture leads to the development of an optimum strategy of GPR data inversion. In this paper, we present finite difference frequency domain (FDFD) full waveform inversion (FWI) method to get high-resolution subsurface model using GPR data. FWI is an optimization technique which involves in search of the minima between recorded and predicted data. The inversion process includes the quasi-Newton method and simultaneous frequency sampling strategy of irregular sampling. The Hessian term in quasi-Newton algorithm is approximated using preconditioned-LBFGS consideration and the search directions are also optimized after following the Wolfe conditions. At the end of each iteration during inversion, permittivity and conductivity models were updated and became ready to be the initial model for the next iteration. The goals of this research were to develop a robust framework for sedimentary-GPR data inversion and to evaluate the efficacy of the novel grid strategy introduced by Layek and Sengupta (2021) proposed for FWI. This paper presents a comparative analysis between conventional and newly proposed technique from Layek and Sengupta (2021), supported by numerical experiments conducted through our own MATLAB programming. Numerical tests conducted on a benchmark from previously published article, established the fact that new grid formulation produces a faster converging rate and required less computation time. This approach demonstrates remarkable efficacy when applied to a comprehensive sedimentary model comprising a lossy medium.

Tsunamis generated by volcanic eruptions have risen to prominence since the December 2018 tsunami generated by the flank collapse of Anak Krakatau during a moderate eruption and then the global tsunami generated by the explosive eruption of the Hunga volcano in the Tongan Archipelago in January 2022. Both events cause fatalities and highlight the lack in tsunami warning systems to detect and warn for tsunamis induced by volcanic mechanisms. Following the Hunga Tonga—Hunga Ha’apai eruption and tsunami, an ad hoc working group on Tsunamis Generated by Volcanoes was formed by the Intergovernmental Oceanographic Commission of UNESCO. Volcanic tsunamis differ from seismic tsunamis in that there are a wide range of source mechanisms that can generate the tsunamis waves and this makes understanding, modelling and monitoring volcanic tsunamis much more difficult than seismic tsunamis. This paper provides a review of both the mechanisms behind volcanic tsunamis and the variety of modelling techniques that can be used to simulate their effects for tsunami hazard assessment and forecasting. It gives an example of a volcanic tsunami risk assessment undertaken for Stromboli, outlines the requirement of volcanic monitoring to warn for tsunami hazard and provides examples of volcanic tsunami warning systems in Italy, the Hawaiian Island (USA), Tonga and Indonesia. The paper finishes by highlighting the need for implementing monitoring and warning systems for volcanic tsunamis for locations with submarine volcanoes or near-shore volcanoes which could potentially generate tsunamis.

The Bida and Anambra Basins are major inland sedimentary basins located in the central and southern part of Nigeria with possible hydrocarbon potential but lack exploratory data. The present study aims at providing base line information on the thermal regime of the sedimentary basins, which would significantly contribute to its hydrocarbon prospect, investment opportunity and exploitation. The spectral analysis of the aeromagnetic anomaly data from the southern Bida Basin, northern Anambra Basin and adjacent basement complex terrain reveals the Curie point depth (CPD), geothermal gradient and heat flow in the region. The data reveals a CPD that varies between 19 and 30 km while the geothermal gradient is from 23 to more than 44 °C/km with heat flow values ranging from 50 to 109 mW/m² in the southern Bida Basin. In the northern Anambra Basin, the CPD values range from 6.8 to 20 km and the heat flow values vary between 59 mWm² and 109 mWm², with a localized shallow CPD value of less than 6.8 km and associated high heat flow of 109 mWm² in the central part of the basin. The delineated thermal patterns in the Bida and Anambra Basins are interpreted to be associated with the intrusions and the presence of deep-seated rift. The interpretation of the aeromagnetic data shows good agreement with the land surface temperature obtained from remote sensing data of the study area. The distribution of heat patterns in the southern Bida and northern Anambra Basins have implications for geothermal, source rock maturation and hydrocarbon generation evaluation of the basins.

The statistical characteristics of the day-to-day variability of the F2-layer peak electron number density, NmF2, measured by the low-latitude Huancayo and Jicamarca ionosondes are studied for each month, M, in a year for geomagnetically quiet conditions at low and moderate solar activity during the time period from 1957 to 2022. The NmF2 statistical parameters under study are the mathematical expectation NmF2_E, the arithmetically average NmF2_A, the standard deviations σ_E(UT,M), and the variation coefficient CV_E(UT,M) of NmF2 relative to NmF2_E, where UT is the universal time. It is found that the value of CV_E(UT,M) that determines the relative day-to-day variability of NmF2 is changed in the intervals of 15–68% and 14–68% for the low and moderate solar activity conditions, respectively. The comparison of CV_E(UT,M) for the low and moderate solar activity conditions under consideration shows for the first time that the increase in the solar activity level increases or decreases the relative day-to-day NmF2 variability in the range from − 24 to 15%. In the vast majority of cases the considered increase in the solar activity level decreases the relative day-to-day NmF2 variability while the longest periods of the corresponding increase in the relative day-to-day NmF2 variability occur in April.

Permeability changes induced by earthquakes have been studied widely. However, basic questions still remain: what are the spatial differences in permeability changes induced by far-field earthquakes? Is there an inevitable relationship between seismic energy density, epicenter azimuth and permeability change? We try to answer the above questions by examining records of 11 years of groundwater hydrographs of 7 wells in the North China plain at large distance from the epicenters of 221 earthquakes during the period 2008 ~ 2018. The results shows permeability changes varied between the different wells, with the permeability variation of the JN well most sensitively responding to seismic events, while the least sensitive wells being SH, JZ and LK. We found that the azimuths of seismic waves can greatly influence the changes in permeability, i.e. mainly concentrated between 25 and 295°. The seismic density energy (SDE) value larger than approximately 10^–9 J/m³ is likely to induce a change in permeability in the NCP aquifer materials. It is found that SDE is not a predictor of permeability change at a given well, by calculating the seismic energy density which did not cause permeability change. While the permeability change ratio before and after the earthquake can be considered as the ability of permeability respond to the dynamic stress and it shows a weak correlation with depth of aquifer. Thus, Factors that probably affect permeability responses changes would have implications for crustal geomechanics.

The derivation of a nonlinear Burgers-type equation for acoustic waves within the ray approximation for an inhomogeneous moving dissipative atmosphere is presented. The equation is applied to investigate the propagation of three-dimensional infrasonic waves, without using significant computational resources. By means of solving the obtained equation, the shapes of infrasonic signals recorded at distances of 295 km and 305 km from the explosion with energy of 30 kt THT were calculated. The observation point at the distance of 295 km (Tsimlyansk) was located in the western direction from the source. At this place, infrasonic signals were recorded corresponding to the sound propagation in the stratospheric and thermospheric acoustic waveguides. The presence of both two stratospheric and two thermospheric rays falling into the same observation point on the Earth's surface is a wave propagation feature result here. The recorded signals in Tsimlyansk also have a complex structure, both for stratospheric and thermospheric infrasonic arrivals. The registration point at a distance of 305 km (Saratov) was located north of the source. For this point, the calculations showed the presence of only thermospheric rays. The calculation results are compared with experimental data. A satisfactory agreement between the calculated and experimental data was obtained for both observation points in Saratov and Tsimlyansk. The calculated data in Tsimlyansk include manifestation features of the multipath structure of infrasound propagation and agree with the complex structure of infrasound signals recorded in Tsimlyansk.

Parwan Gravity Dam is under construction stage in the Jhalawar district of Rajasthan, India. A thin sub-vertical surficial fracture trending N 75°W to S 75°E has been observed in the foundation area of the dam. Geophysical techniques such as electrical resistivity tomography (ERT), seismic refraction tomography (SRT), and multichannel analysis of surface waves (MASW) are utilized extensively in the field of civil engineering, exploration geophysics for the assessment and construction of large-scale infrastructures such as dams. These methods provide critical information about the subsurface conditions without the need of extensive drilling and excavation. The combination of electrical resistivity tomography (ERT), seismic refraction (SR), and multichannel analysis of surface waves (MASW) techniques with the different acquisition parameters have been used to image the extent of shallow subsurface geological structures. Various geophysical Surveys have been carried out along several profiles in the longitudinal direction and along the transverse direction to the fault axis. A total of 13 refraction and resistivity profiles were conducted of which 9 were transverse profiles and 4 were longitudinal profiles. A total of nine MASW profiles were conducted of which 8 are transverse profiles and 1 is a longitudinal profile. In this paper, the subsurface distribution of seismic wave velocity and electrical resistivity have been studied to identify any possible anomalous zone in bedrock and to detect the downward extension of surface fracture of brittle fault using the afore mentioned methods. The vertical and lateral extent of the surface fracture of the fault has been investigated by the analysis of these survey results. The analysis of the results indicates that a very tight and narrow fracture is present in the shallow subsurface.

Adequate estimation of S-wave velocity (Vs) structure is a significant parameter in the seismic micro zonation studies. To this purpose, different techniques, such as down-hole measurements and inversion of surface wave’s dispersion curves are proposed for modeling V_S profile. In the last decade, modeling Vs profile from the Rayleigh wave’s ellipticity curve (H/V) is more applicable owing to its rapid and simple data gathering procedure. However, regarding the ambiguities in the inversion of H/V curves, obtaining the reliable results priori information, such as down-hole measurement, to constrain the final Vs model is vital. This study addressed this challenge, and based on a hybrid artificial intelligence method introduced a new technique to invert the Rayleigh wave ellipticity curve with acceptable performance. To do that, first model parameters (i.e. number of layers and corresponding thicknesses and shear wave velocities) by the ensemble of neural networks (ENN) were predicted, and then further inversion by jellyfish searching (JS) algorithm (named ENN-JS inversion method) was carried out to obtain a more reasonable Vs model. To build the ensemble system, ten base networks were arranged. To train the neural networks, synthetic Rayleigh wave ellipticity data by forward modeling approach were generated. The combination of the outputs of based networks was performed using the averaging method. Then, JS inversion algorithm was applied to estimate the final adequate Vs model. ENNs provide essential information to the JS searching algorithm on the number of layers and proper search spaces for model parameters. Synthetic and actual datasets tested the ENN-JS inversion technique. Findings show the proposed method provides a robust method for the inversion of Rayleigh wave ellipticity data.