摘要
Gas-bearing volcanic reservoirs have been found in the deep Songliao Basin, China. Choosing proper interpretation parameters for log evaluation is difficult due to complicated mineral compositions and variable mineral contents. Based on the QAPF classification scheme given by IUGS, we propose a method to determine the mineral contents of volcanic rocks using log data and a genetic algorithm. According to the QAPF scheme, minerals in volcanic rocks are divided into five groups： Q（quartz）, A （Alkaline feldspar）, P （plagioclase）, M （mafic） and F （feldspathoid）. We propose a model called QAPM including porosity for the volumetric analysis of reservoirs. The log response equations for density, apparent neutron porosity, transit time, gamma ray and volume photoelectrical cross section index were first established with the mineral parameters obtained from the Schlumberger handbook of log mineral parameters. Then the volumes of the four minerals in the matrix were calculated using the genetic algorithm （GA）. The calculated porosity, based on the interpretation parameters, can be compared with core porosity, and the rock names given in the paper based on QAPF classification according to the four mineral contents are compatible with those from the chemical analysis of the core samples.
在松辽盆地深层发现了含气火成岩储层。由于火成岩矿物组成复杂和含量的变化,使得选择用于测井评价的解释参数很困难。基于IUGS提出的QAPF分类方案,本文提出了采用遗传算法,利用测井数据确定火成岩矿物含量的方法。根据QAPF分类方案,将火成岩中的矿物分为五类:Q-石英;A-碱性长石;P-斜长石和方柱石;F-副长石(研究区未出现);M-铁镁矿物。本文提出用包括孔隙度在内的QAPM模型对储层进行分析。建立密度、视中子孔隙度、声波时差、自然伽玛和体积光电吸收截面指数的测井响应方程,各矿物参数从斯伦贝谢的矿物参数手册中得到。用遗传算法计算骨架中四种矿物的体积,根据四种矿物的体积含量,依据QAPF分类对火成岩命名。基于解释参数计算的孔隙度可与岩心分析的孔隙度相比,本文给出的火成岩命名与岩心化学分析的命名相一致。
基金
National Natural Science Foundation of China (No. 49894194-4)
