We applied the reflectivity method and the constrained sparse spike inverse modeling(CSSI) method to the interpretation of coal field lithologic seismic data.After introducing the principles of these two methods we di...We applied the reflectivity method and the constrained sparse spike inverse modeling(CSSI) method to the interpretation of coal field lithologic seismic data.After introducing the principles of these two methods we discuss some parameters of a geological model involving possible gas enriched areas or intruded igneous rock.The geological model was constructed and a 60 Hz seismic response profile was obtained looking for igneous rock intrusion and coked areas of the coal seam using the reflectivity method.Starting from synthesized logging data from two wells and a synthesized seismic wavelet we calibrated the model to show accurate strata.Finally,we predicted the lithology within a 10 m igneous rock area,a 3 m coal seam area,and a coked area using the CSSI technique.The results show that the CSSI technique can identify hard to recognize lithologic features that normal profil-ing methods might miss.It can quantitatively analyze and evaluate the intrusive area,the coked area,and the gas-enriched area.展开更多
All coal mine disasters are dynamic geological phenomenon and affected by many factors. However, locating the enriched areas of CSM (coal seam methane) may be the precondition for the successful prediction of such dis...All coal mine disasters are dynamic geological phenomenon and affected by many factors. However, locating the enriched areas of CSM (coal seam methane) may be the precondition for the successful prediction of such disasters. Traditional methods of investigating CSM enriched areas use limited data and only consider a few important factors. Their success rate is low and cannot meet practical needs. In this paper, an alternative method is proposed. The proce- dure is given as follows: 1) fracture attributes derived from azimuth variations of P-wave data in coal seams and wall rocks can be extracted; 2) AVO attributes, such as the intercept P and gradient G parameters can be extracted from different azimuths from 3D seismic data; 3) seismic cubes can be inverted and the relative attributes of imped- ance cubes can be extracted; 4) using a GIS platform, multi-source information can be obtained and analyzed; these include fracture attributes of coal seams and wall rocks, the thickness of coal seams, the distribution of faults and structures, the depth of coal seams, the inclination and exposure of coal seams and the coal rank. Through this processing procedure, methane enriched areas can be systematically detected.展开更多
基金Projects 40874054 and 40804026 supported by the National Natural Science Foundation of Chinathe National Basic Research Program of China (2007CB209400 and 2009CB219603)the National Key Scientific and Technological Project (2008ZX05035)
文摘We applied the reflectivity method and the constrained sparse spike inverse modeling(CSSI) method to the interpretation of coal field lithologic seismic data.After introducing the principles of these two methods we discuss some parameters of a geological model involving possible gas enriched areas or intruded igneous rock.The geological model was constructed and a 60 Hz seismic response profile was obtained looking for igneous rock intrusion and coked areas of the coal seam using the reflectivity method.Starting from synthesized logging data from two wells and a synthesized seismic wavelet we calibrated the model to show accurate strata.Finally,we predicted the lithology within a 10 m igneous rock area,a 3 m coal seam area,and a coked area using the CSSI technique.The results show that the CSSI technique can identify hard to recognize lithologic features that normal profil-ing methods might miss.It can quantitatively analyze and evaluate the intrusive area,the coked area,and the gas-enriched area.
基金Project 40574057 supported by the National Natural Science Foundation of China and CUMT Youth Foundation
文摘All coal mine disasters are dynamic geological phenomenon and affected by many factors. However, locating the enriched areas of CSM (coal seam methane) may be the precondition for the successful prediction of such disasters. Traditional methods of investigating CSM enriched areas use limited data and only consider a few important factors. Their success rate is low and cannot meet practical needs. In this paper, an alternative method is proposed. The proce- dure is given as follows: 1) fracture attributes derived from azimuth variations of P-wave data in coal seams and wall rocks can be extracted; 2) AVO attributes, such as the intercept P and gradient G parameters can be extracted from different azimuths from 3D seismic data; 3) seismic cubes can be inverted and the relative attributes of imped- ance cubes can be extracted; 4) using a GIS platform, multi-source information can be obtained and analyzed; these include fracture attributes of coal seams and wall rocks, the thickness of coal seams, the distribution of faults and structures, the depth of coal seams, the inclination and exposure of coal seams and the coal rank. Through this processing procedure, methane enriched areas can be systematically detected.