Gas occurrence and production characteristics of deep coal measure gas and reserve estimation method and indicators in Daning-Jixian block
The deep coal measure gas is a new field of CBM exploration,and the scientific estimation of deep coal measure gas reserves is a new challenge.By summarizing the exploration and development achievements in Daning-Jixian block,and analyzing gas accumulation characteristics,occurrence pattern,gas production laws and performance of deep coal measure gas,the unique occurrence characteristics of adsorbed gas+free gas,gas production mechanism of free gas → free gas+adsorbed gas → adsorbed gas,and its significant differences from shallow and medium-shallow coal measure gas have been studied.Furthermore,the inadaptability of the current reserve estimation standards for deep coal measure gas has been pointed out in terms of estimation methods,unit division,estimation parameters,threshold for calculation,and data collection.Based on the above research,the following suggestions are put forward for estimating deep coal measure gas reserves.The volume and volumetric methods can be used to estimate reserves,and the appropriate method should be selected based on the proportion of free gas;The reserve calculation units for free gas should be divided separately;The lower limit for coal gangue thickness deduction is 0.3-0.5 m;When Ro is less than 1.0％,the lower limit for net coal seam thickness should be greater than 1.0 m;When Ro is larger than 1.0％,the lower limit for net coal seam thickness should be greater than 0.8 m;The lower limit for single well gas production should be determined by well depth range and well type;In the early exploration stage,the recovery factor of vertical wells was 30％-45％,while that of horizontal wells was 35％-55％.This study provides technical references for the exploration and development,as well as reserve estimation of deep coal measure gas.
deep coal measure gasgeological characteristicsadsorbed gasfree gasgas production lawreserve calculation parametersrecovery factor
万方数据
维普
