Prediction of Young Modulus of coal using artificial neural networks in Qinshui Basin,China  

作　　者：GUO Xiaoqian LIU Dameng YAO Yanbin 

机构地区：[1]School of Energy Resources, China University ofGeosciences, Beijing 100083, China [2]Coal Reservoir Laboratory of National CBMEngineering Center, China University ofGeosciences, Beijing 100083, China

出　　处：《Acta Geologica Sinica(English Edition)》2015年第A01期339-341,共3页地质学报（英文版）

基　　金：supported by the National Major Research Program for Science and Technology of China(2011ZX05034-001);National Natural Science Foundation of China(40972107);Program for Excellent Doctoral Dissertation Supervisor of Beijing(YB20101141501);Program for New Century Excellent Talents in University(NCET-11-0721);PetroChina Innovation Foundation(2010D-5006-0101);A Foundation for the Author of National Excellent Doctoral Dissertation of PR China

摘　　要：1 Introduction Mechanical properties of coal are most important parameters in controlling fluid storage and flow before and after coal extraction [1-2].Reservoir simulation design and wellbore stability analysis are influenced by elastic and strength character of coal rocks[3].Young＇s modulus, and shear modulus are usedwhen deformations in underground mines need to be computed. Thus accurate assessment of elastic properties of coal rocks is extremely important for ground mining.1 Introduction Mechanical properties of coal are most important parameters in controlling fluid storage and flow before and after coal extraction [1-2].Reservoir simulation design and wellbore stability analysis are influenced by elastic and strength character of coal rocks[3].Young＇s modulus, and shear modulus are usedwhen deformations in underground mines need to be computed. Thus accurate assessment of elastic properties of coal rocks is extremely important for ground mining.

分 类 号：TD17[矿业工程—矿山地质测量]