观音山勘探区煤层含气量灰色关联预测

煤层含气量受多种地质因素影响,往往难以准确预测。以云南观音山勘探区为例,利用灰色关联度法识别出影响煤层含气量的主要因素,先后建立了煤层含气量预测的GM (1,N)模型和GM (1,1)模型。进一步分析揭示,煤层埋藏深度、煤层顶板5 m内砂岩厚度和顶板岩性是影响观音山勘探区煤层含气量的3个关键因素,利用残差尾段序列建立的GM (1,1)模型具有较高的预测精度。 

Grey relational prediction of coalbed methane content in Guanyinshan exploration district

Gas content, one of the key indicators used to measure CBM-reservoiring effect, controlled by a variety of geological factors, is often difficult to predict. Taking the Guanyinshan exploration district as a case, the authors identified the main geological controlling factors of CBM content with the gray degree related method, and established GM (1, N) and GM (1,1) models for the gas content prediction in succession in the paper. Further analysis revealed that the burial depth of coal seams, sandstone thickness within 5 meters of roof and roof lithology are key to gas content in the exploration district, and that the GM (1,1) model established from the residual empennage sequence has higher prediction accuracy.