China
Africa
Explore chapters and articles related to this topic
Chapter 10: Wavelets
Published in Abul Hasan Siddiqi, Mohamed Al-Lawati, Messaoud Boulbrachene, Modern Engineering Mathematics, 2017
Abul Hasan Siddiqi, Mohamed Al-Lawati, Messaoud Boulbrachene
Seismic tomography has several applications in exploration and global geophysics. Seismic tomography can also be used to characterize fractured bedrock, map groundwater reservoirs, and locate ore bodies. Global seismic tomography is used to interpret ancient subducted slabs, locate the sources of hotspots, and model convection patterns in the mantle.
Communication-efficient decentralised algorithms for seismic tomography with sensor networks
Published in International Journal of Parallel, Emergent and Distributed Systems, 2020
Seismic tomography is a technique for imaging Earths subsurface characteristics in an effort to understand deep geologic structure. It involves massive data collection, often manually retrieval, from hundreds to thousands geophones to a central place for post-processing. Real-time subsurface imaging is in great demand today as it is essential to assess the sustainability and potential hazards of geological structures, and reduce the costs and risks of exploration and production activities. Sensor network has been an effective approach for real-time remote environment monitoring. However, collecting massive raw seismic data through a sensor network in real-time is infeasible, due to severe bandwidth and sensor energy constraints. This paper is thus proposing a novel decentralised in-situ computing method for imaging earth subsurface in real-time. It is based on the principle of travel-time seismic tomography [2].
Numerical studies of the statistics of seismic waveform propagation in random heterogeneous media
Published in Waves in Random and Complex Media, 2023
Huo Lei, Chuang Hei, Mingzhang Luo, Xiao Zou, Aimin Wang, Guofeng Du, Yifei Nie
Seismic waves will generate scattered waves when propagating through heterogeneous media. Although geological formations are often considered as layered media in seismic exploration [1–3], heterogeneities in the geological bodies are also observed at the microscopic level. Heterogeneity inside the Earth is usually divided into two different types, namely the long-wavelength and short-wavelength heterogeneity [4]. Long-wavelength heterogeneity is regarded as the target heterogeneity that describes the average characteristics of the medium, which is the geological model in the traditional sense. Short-wavelength heterogeneity is regarded as the fluctuation of the physical properties of the target heterogeneity, describing the heterogeneity of the medium on a smaller scale [5–7]. Previous research on seismic propagation has been performed by earthquake simulation [8–10]. In modern seismology, the variation of seismic waveforms caused by long-wavelength heterogeneity is considered to be well understood [11]. At large scale lengths, seismic tomography is used to map earth structure deterministically. At small scale lengths, structure can be imaged deterministically, but because it is impractical to image short-wavelength heterogeneity everywhere, we often resort to statistical methods to depict its variability [12]. Short-wavelength heterogeneity is often referred to as random heterogeneity. When seismic waves propagate through a heterogeneous medium, random heterogeneity produces incoherent scattered waves that overlap with the source signal, and the complex waveforms are observed at the receiving [13–15]. The heterogeneity of the rock is often indicated by the existence of scattered waves, and this characteristic can be used to evaluate the fracturing effect of the reservoir [16–19]. Scattered waves are signal-induced waves associated with the interaction between wave sources and random heterogeneity [20], therefore, it is important to study the relationship between them. Since the scattered waves are incoherent and the rock heterogeneity is assumed to be random, the statistical properties of seismic wave fluctuations will be closely related to the statistical properties of random heterogeneities.