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保德煤矿煤层瓦斯赋存参数精准预测及智能分析

Accurate prediction and intelligent analysis of coal seam gas occurrence parameters in Baode Coal Mine
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摘要 针对高瓦斯、突出矿井瓦斯参数测定时间长、工艺复杂等问题,提出了煤层瓦斯参数精准预测及智能分析方法,并在保德煤矿进行了试验。首先,开发了DGC瓦斯含量自动采集接口,研制了WTC-1瓦斯出数据采集仪,实现了瓦斯参数的自动采集;其次,建立煤层瓦斯多源数据融合分析方法,实现了地勘、生产实测和反演计算等多渠道瓦斯数据的互馈验证、自动甄别与校正,提高瓦斯基础数据的可靠性;再次,分析了保德煤矿8号煤层瓦斯赋存影响因素及主控因素,并划分了地质单元,基于此,建立了保德煤矿8号煤层瓦斯参数精准预测模型并验证其准确性;最后,开发瓦斯地质动态分析系统,实现了瓦斯参数信息化管理、瓦斯参数预测等值线及栅格的智能生成、动态修正及剖面分析等功能。通过该技术的应用,显著提升了保德煤矿瓦斯参数预测的准确性和智能分析能力,为煤矿安全高效开采及智能化建设提供了技术支撑。 In response to the problems of long measurement time and complex process for gas parameters in high gas and outburst mines,proposes a precise prediction and intelligent analysis method for coal seam gas parameters,and has conducted experiments in Baode Coal Mine.Firstly,the DGC automatic gas content acquisition interface and WTC-1 gas output data acquisition instrument are developed to realize automatic gas parameter acquisition.Secondly,a fusion analysis method of coal seam gas multi-source data is established to realize the mutual feed verification,automatic identification and correction of multi-channel gas data such as geological prospecting,production measurement and inversion calculation,so as to improve the reliability of basic gas data.Thirdly,the influencing factors and main controlling factors of gas occurrence in No.8 coal seam of Baode Coal Mine are analyzed,and geological units are divided.Based on this,the accurate prediction model of gas parameters in No.8 coal seam of Baode Coal Mine is established and its accuracy is verified.Finally,the dynamic analysis system of gas geology is developed to realize the information management of gas parameters,intelligent generation,dynamic correction and profile analysis of gas parameter prediction isoline and grid.The application of this technology significantly improves the accuracy of gas parameter prediction and intelligent analysis ability of Baode Coal Mine,and provides technical support for the safe and efficient mining and intelligent construction of coal mine.
作者 程晓阳 CHENG Xiaoyang(China Coal Research Institute,Beijing 100013,China;State Key Laboratory of Gas Disaster Monitoring and Emergency Technology,Chongqing 400037,China;China Coal Technology and Engineering Group Chongqing Research Institute,Chongqing 400037,China)
出处 《中国矿业》 2023年第8期115-122,共8页 China Mining Magazine
基金 国家自然科学基金项目资助(编号:51974358) 重庆市自然科学基金(杰出青年基金)项目资助(编号:cstc2019jcyjjqX0019) 重庆市自然科学基金面上项目资助(编号:CSTB2022NSCQ-MSX1080)。
关键词 瓦斯参数 多源数据融合 精准预测 智能分析 gas parameter multi-source data fusion precision prediction intelligent analysis
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