Surveys in Geophysics最新文献

Globally, unconventional hydrocarbons, known for the symbiosis of their hydrocarbon source and reservoir, pose significant seismic exploration challenges due to their confined target regions, extensive burial depth, minimal acoustic impedance variation, marked heterogeneity, and strong anisotropy. Over the past decade, electromagnetic (EM) exploration has evolved markedly, improving resolution and reliability, thus becoming indispensable in unconventional hydrocarbon exploration. Focusing on China's application of the controlled source electromagnetic method (CSEM), this review examines the geological and electrical attributes of these reservoirs, notably the low resistivity, high polarization and strong electrical anisotropy of shale gas reservoirs. Despite the demonstrated positive correlation between induced polarization (IP) parameters and reservoir parameters, current methodologies emphasize the IP effect, inadvertently neglecting electrical anisotropy, which affects data precision. Moreover, single-source CSEM methodologies limit the observational components, acquisition density, and exploration area, impacting the accuracy and efficacy of data interpretation. Recently developed CSEM techniques in China, namely wide-frequency electromagnetic method (WFEM), time–frequency electromagnetic method (TFEM), long offset transient electromagnetic method (LOTEM), and wireless electromagnetic method (WEM), harness high-power pseudo-random binary sequence (PRBS) waveforms, reference observation and processing technology, hybrid inversion, and enhancing operational efficiency and adaptability despite the pressing need for multi-functional software for data acquisition. Case studies detail these methods' applications in shale gas sweet spot detection and continuous hydraulic fracturing monitoring, highlighting the immense potential of EM methods in unconventional hydrocarbon sweet spot detection and total organic content (TOC) predication. However, challenges persist in suppressing EM noise, streamlining 3D inversion processes, and improving the detection and evaluation of sweet spots.

Deep seismic reflection (DSR) profiling is an effective technique for mapping subsurface structures. Generally, reflections in DSR data are used to constrain underground structures at the crustal scale. In addition to reflections, surface waves in DSR data can be used to investigate shallow/near-surface structures. In this study, we extracted multimodal dispersion curves and estimated their uncertainties from the DSR data in the Beijing Plain, North China, using the frequency-Bessel transform method. Compared to other surface wave surveys conducted in this area, the dispersion curves obtained from DSR data have a unique frequency band, which enables an accurate image of the structure to a depth of 200 m. The 2-D shear wave velocity model obtained by surface wave inversion is consistent with the borehole data and existing shallow/near-surface geophysical studies, which can effectively resolve the faults in the study area. Given the extensive deployment of DSR surveys worldwide and the potential of DSR surface wave analysis, we believe that the development of DSR surface wave analysis could be highly beneficial.

The gravity anomalies reflect density perturbations at different depths, which control the physical state and dynamics of the lithosphere and sub-lithospheric mantle. However, the gravity effect of the crust masks the mantle signals. In this study, we develop two frameworks (correction with density contrasts and actual densities) to calculate the gravity anomalies generated by the layered crust. We apply the proposed approaches to evaluate the global mantle gravity disturbances based on the new crustal models. Consistent patterns and an increasing linear trend of the mantle gravity disturbances with lithospheric thickness and Vs velocities at 150 km depth are obtained. Our results indicate denser lithospheric roots in most cratons and lighter materials in the oceanic mantle. Furthermore, our gravity map corresponds well to regional geological features, providing new insights into mantle structure and dynamics. Specifically, (1) reduced anomalies associated with the Superior and Rae cratons indicate more depleted roots compared with other cratons of North America. (2) Negative anomalies along the Cordillera (western North America) suggest mass deficits owing to the buoyant hot mantle. (3) Positive anomalies in the Baltic, East European, and Siberian cratons support thick, dense lithosphere with significant density heterogeneities, which could result from thermo-chemical modifications of the cratonic roots. (4) Pronounced positive anomalies correspond to stable blocks, e.g., Arabian Platform, Indian Craton, and Tarim basin, indicating a thick, dense lithosphere. (5) Low anomalies in the active tectonic units and back-arc basins suggest local mantle upwellings. (6) The cold subducting/detached plates may result in the high anomalies observed in the Zagros and Tibet.

The mission of Advanced Ionospheric Probe (AIP) onboard FORMOSAT-5 (F5) satellite is to detect pre-earthquake ionospheric anomalies (PEIAs) and observe ionospheric space weather. F5/AIP plasma quantities in the nighttime of 22:30 LT (local time) and the total electron content (TEC) of the global ionosphere map (GIM) are used to study PEIAs of an M7.3 earthquake in the Iran–Iraq border area on 12 November 2017, as well as signatures of two magnetic storms on 7 and 21–22 November 2017. Statistical analyses of the median base and one sample test are employed to find the characteristics of temporal PEIAs in GIM TEC over the Iran–Iraq area. The anomalous increases of the GIM TEC and F5/AIP ion density over the epicenter area on 3–4 November (day 9–8 before the M7.3 earthquake) agree with the temporal PEIA characteristics that the significant TEC increase frequently appears on day 14–6 before 53 M ≥ 5.5 earthquakes in the area during 1999–2016. The spatial analyses together with odds studies show that the PEIAs frequently appear specifically over the epicenter day 9–8 before the M7.3 earthquake and day 10–9 before a M6.1 earthquake on 1 December, while proponent TEC increases occur at worldwide high latitudes on the two magnetic storm days. The F5/AIP ion velocity uncovers that the PEIAs of the two earthquakes are caused by associated eastward electric fields, and the two positive storm signatures are due to the prompt penetration electric fields.

Very Long Period (VLP) signals with periods longer than 2 s may occur during eruptive or quiet phases at volcanoes of all types (shield and stratovolcanoes with calderas, as well as other stratovolcanoes) and are inherently connected to fluid movement within the plumbing system. This is supported by observations at several volcanoes that indicate a correlation between gas emissions and VLPs, as well as deformation episodes due to melt accumulation and migration that are followed by the occurrence of VLPs. Moment tensors of VLPs are usually characterized by large volumetric components of either positive or negative sign along with possibly the presence of single forces that may result from the exchange of linear momentum between the seismic source and the Earth. VLPs may occur during a variety of volcanological processes such as caldera collapse, phreatic eruptions, vulcanian eruptions, strombolian activity, and rockfalls at lava lakes. Physical mechanisms that can generate VLPs include the inflation and deflation of magma chambers and cracks, the movement of gas slugs through conduits, and the restoration of gravitational equilibrium in the plumbing system after explosive degassing or rockfalls in lava lakes. Our understanding of VLPs is expected to greatly improve in the future by the use of new instrumentation, such as Distributed Acoustic Sensing, that will provide a much denser temporal and spatial sampling of the seismic wavefield. This vast quantity of data will then require time efficient and objective processing that can be achieved through the use of machine learning algorithms.