Applications of Data Processing Techniques in Geophysical Exploration

Dear Colleagues,

Geophysical exploration is crucial for energy transition, natural hazard mitigation, and planetary science, playing an irreplaceable role in revealing subsurface structures, exploring energy resources, and assessing geological disaster risks. With the advancement of wide-band, wide-azimuth, and high-density seismic acquisition technologies, geophysical exploration has entered the big data era, generating massive multi-source heterogeneous data (e.g., seismic, gravity, magnetic, and electrical data). However, raw field data is often contaminated by noise (environmental interference, instrument errors, etc.) and features high dimensionality, redundancy, and non-linear correlation, making it hard to directly extract effective geological information.

The growing demand for exploration accuracy and efficiency, especially in deep/ultra-deep energy exploration and complex structural areas, highlights the limitations of traditional data processing methods. Conventional techniques struggle to handle massive high-dimensional data, failing to balance efficiency and accuracy, which restricts the accurate identification of subsurface targets (e.g., oil and gas reservoirs, faults) and the reliable evaluation of geological parameters. Additionally, fragmented workflows hinder the integration of multi-source data, limiting the exploitation of their potential value.

Considering this background, research on the applications of data processing techniques in geophysical exploration is of great necessity and practical significance. Advanced data processing techniques, including signal denoising, feature extraction, data fusion, and intelligent interpretation, can effectively eliminate noise interference in raw data, enhance the signal-to-noise ratio of data, and accurately extract key geological information hidden in massive data. This not only helps to improve the accuracy and efficiency of geophysical exploration, reduce exploration costs and risks, but also provides reliable technical support for breaking through the bottlenecks in deep and ultra-deep exploration and complex structural interpretation. Moreover, the rational application of data processing techniques can promote the integration of multi-source geophysical data, realize the organic combination of qualitative analysis and quantitative evaluation, and further promote the transformation of geophysical exploration from "data-driven" to "intelligence-driven", which is crucial for promoting the high-quality development of geophysical exploration and supporting related fields such as energy security and natural hazard prevention.

Prof. Dr. Chun-Xia Zhang
Guest Editor

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