Detection of Tectonically Deformed Coal Using Model-Based Joint Inversion of Multi-Component Seismic Data

Jun Lu, Yun Wang and Jingyi Chen
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Jun Lu: Key Laboratory of Marine Reservoir Evolution and Hydrocarbon Accumulation Mechanism, Ministry of Education, China University of Geosciences, Beijing 100083, China
Yun Wang: School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China
Jingyi Chen: Department of Geosciences, The University of Tulsa, Tulsa, OK 74104, USA

Energies, 2018, vol. 11, issue 4, 1-17

Abstract: Tectonically-deformed coal (TDC) is a potential source of threats to coal-mining safety. Finding out the development and distribution of TDCs is a difficult task in coalfield seismic explorations. Based on the previous investigations, the P- to S-wave velocity ratio ( ? / ? ) is a stable parameter for the identification of TDCs and most TDCs have ? / ? values of less than 1.7. Here, a TDC detection method using a model-based joint inversion of the multi-component seismic data is proposed. Following the least square theories, the amplitude variation with offset gathers of the PP- and PS-waves are jointly inverted into the corresponding ? / ? values. The prior models generated from the P- and S-wave velocity and density logs are employed in the joint inversion to enhance the inversed models. Model test results show that the model-based inversion is of high anti-noise ability and has a good recognition ability of TDCs. The proposed method is applied to a work area of the Guqiao mine in China. The TDCs developed in coal seam 13-1 are effectively identified according to their inverted ? / ? values of less than 1.7. The detection result is verified by the well and tunnel excavation information.

Keywords: tectonically deformed coal; outburst; joint inversion; multi-component seismic; amplitude variation with offset; P- to S-wave velocity ratio (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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