2) coalbed gas content
煤层含气量
1.
Prediction of coalbed gas content based on support vector machine regression;
基于支持向量机回归的煤层含气量预测
2.
Put forward in this paper is the model using back-propagation artificial neural networks to predict coal quality parameters and coalbed gas content.
提出利用ＢＰ神经网络预测煤质参数及煤层气含量的模型和算法，预测的煤质参数以及煤层含气量与煤样分析结果比较表明，预测与煤样分析参数之间的平均绝对误差和相对误差都较小，精度满足定量计算的要
3) oxygen-bearing coal mine methane
含氧煤层气
1.
In order to make use of the oxygen-bearing coal mine methane(CMM)effectively,sulfide oxidation is introduced,and the impact of reaction temperature,flow velocity,catalyst and other factors on the deoxygenation process is investigated using TG technology and fixed-bed reator.
为了充分利用含氧煤层气,采用硫化物氧化法,利用热重和固定床反应器研究了含氧煤层气脱氧过程中温度、流速及催化剂等因素的影响。
4) coal seam gas containing feature
煤层含气性
1.
discusses the coal seam gas containing features,gas bearing control factors and evolution course of hydrocarbon based on coal bearing.
通过城子河组含煤性、煤层的煤体结构、煤裂隙发育特征、渗透性与孔隙度、储层压力、煤的吸附性等储层特征探讨煤层含气性、含气控制因素及煤生烃历程勺演化。
5) seam dustiness
煤层含尘量
6) adsorbed methane-coal system
含吸附煤层气煤
补充资料：煤层气(见煤成气)
煤层气(见煤成气)
coal-bed gas:see coal derived gas
于煤煤层气(c oal一bed gas)以吸附状态赋存 层内部的煤成气。见谋成气。-
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条