Methods for the Geophysical Exploration and Sustainable Utilisation of Coalbed Methane Resources in Abandoned Mines of Shanxi, China

Abstract

Underground coal mining results in large goafs and numerous abandoned mines that contain substantial amounts of coalbed methane. If this methane is not used and controlled, it will escape into the atmosphere through geological fractures and can result in serious greenhouse gas effects and environmental damage. Exploring and developing the coalbed methane resources of abandoned mines can not only improve coal mine safety and protect the ecological environment but also reuse waste and mitigate energy shortages. Geophysical methods have made some progress in detecting abandoned coal mines, but there are still some challenges and difficulties. The resolution of seismic exploration may not be enough to accurately describe the details of coal seams and CBM rich areas, and the effect of resistivity method in deep CBM exploration is limited. In addition, the geological structure of abandoned coal mines is usually more complex, such as faults, folds, etc., which makes the application of exploration methods more difficult and increases the difficulty of data interpretation. Therefore, it is necessary to develop and perfect exploration technology continuously including the application of geophysical big data, deep learning, and artificial intelligence inversion to realize the accurate detection and evaluation of CBM resources in abandoned coal mines.

Assessment of Near-Surface Geophysical Methods Used to Discover Karst Bauxite Deposits in the Dinarides Using the Example of Posušje Area, Bosnia and Herzegovina

“…In addition, electrical tomography provides a more precise definition of lithological and structural relationships in the explored area. Electromagnetic methods, including the magnetotelluric method, especially controlled-source audio-magnetotellurics (CSAMT) [7] and the transient electromagnetic method (TEM or TDEM), can be also used in such explorations [8,9]. Both methods are also based on rock resistivity measurements, and similar results are expected as with electrical tomography methods, but they have an advantage in greater depth penetrations, those exceeding 100 m. However, their negative side is high sensitivity to electrical noises, which can often be unavoidable in shallow explorations.…”

Accurate Delimitation of Mine Goaves Using Multi-Attribute Comprehensive Identification and Data Fusion Technologies in 3D Seismic Exploration

“…The fine detection and identification of goaf boundaries, locations, and water-richness is key to ensure safe, efficient, and intelligent mining activities [1,2], as well as a comprehensive management of goaves [3,4]. 3D seismic exploration can be applied to coal mines as a fine exploration technology [5][6][7]. In the presence of goaves, however, the accuracy with which any underlying coal strata are recognized diminishes [8].…”