Integrated Geological-Engineering Logging Evaluation and Application of "Six Properties" for Deep Coalbed Methane Reservoirs
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摘要: 针对深层煤层气储层高温高压、强非均质性、孔裂隙系统复杂及地应力约束显著等特点，构建了岩性、生烃性、物性、含气性、可压性和应力特性“六性”地质-工程协同评价体系.岩性表现为低自然伽马、低密度、高中子、高声波时差和相对高电阻率；生烃性可由元素测井、密度、声波和电阻率联合表征；物性受孔裂隙结构控制，可通过密度、声波、核磁共振、电成像和电阻率识别；含气性表现为高电阻率、中子-密度异常和核磁响应差异；可压性由阵列声波、密度和元素测井约束；应力特性通过阵列声波、电成像、密度测井评价.基于上述认识，构建了由有机显微组分、无机矿物和孔隙流体组成的煤岩测井评价体积模型，形成岩性识别、生烃性评价、孔渗参数计算、吸附气-游离气含量预测、可压性表征及地应力评价方法.电性响应受岩性组成、生烃演化、孔裂隙结构、含气状态、可压性特征和应力作用共同控制，具有综合性和多解性；与密度、声波、核磁、元素和成像测井联合应用，可降低单一参数解释不确定性，提高“六性”关键参数解释精度.大吉区块应用结果表明，优质储层具有低灰分、高镜质组含量、煤体结构较完整、煤层厚度大、含气量高、孔裂隙系统有效、可压性较好及应力差适中等特征，测井上表现为高阻-高时差型.该方法可为甜点预测、水平井部署和压裂层段优选提供支撑.Abstract: To address the high temperature and pressure, strong heterogeneity, complex pore-fracture system, and significant in-situ stress constraints of deep coalbed methane reservoirs, this study establishes a geological-engineering collaborative evaluation framework based on six properties: lithology, hydrocarbon generation potential, petrophysical properties, gas-bearing property, fracability, and stress characteristics. The results show that lithology is characterized by low natural gamma, low density, high neutron response, high acoustic slowness, and relatively high resistivity. Hydrocarbon generation potential can be jointly characterized by elemental logging, density, acoustic, and resistivity logs. Petrophysical properties are controlled by pore-fracture structure and can be identified using density, acoustic, nuclear magnetic resonance, electrical imaging, and resistivity logs. Gas-bearing property is indicated by high resistivity, neutron-density anomaly, and nuclear magnetic resonance response differences. Fracability is constrained by array acoustic, density, and elemental logs, while stress characteristics are evaluated using array acoustic, electrical imaging, and density logs.Based on these understandings, a logging evaluation volume model composed of organic macerals, inorganic minerals, and pore fluids is constructed. Methods are developed for lithology identification, hydrocarbon generation evaluation, porosity and permeability calculation, adsorbed gas and free gas prediction, fracability characterization, and in-situ stress evaluation. Electrical responses are jointly controlled by lithologic composition, hydrocarbon generation evolution, pore-fracture structure, gas-bearing state, fracability, and stress conditions, showing strong comprehensiveness and non-uniqueness. Integrated application of electrical, density, acoustic, nuclear magnetic resonance, elemental, and imaging logs can reduce single-parameter interpretation uncertainty and improve the accuracy of key "six-properties" parameters. Application in the Daji Block shows that high-quality reservoirs are characterized by low ash content, high vitrinite content, relatively intact coal structure, large coal thickness, high gas content, effective pore-fracture systems, favorable fracability, and moderate stress difference, with high-resistivity and high-slowness logging responses. This method provides support for sweet spot prediction, horizontal well deployment, and fracturing interval optimization.
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图 1 煤层气与常规油气储层和页岩储层体积模型对比
Fig. 1. Comparison of volumetric models among coalbed (coal rock) gas, conventional oil and gas reservoirs, and shale reservoirs
图 2 测井曲线参数交会识别岩性
Fig. 2. Lithology identification using crossplots of logging parameters
图 4 宏观煤岩类型测井定性与定量识别成果
Fig. 4. Qualitative and quantitative identification results of macrolithotypes from well logs
图 5 煤层总有机碳含量测井表征
Fig. 5. Well-log characterization of total organic carbon (TOC) content in coals
图 6 深层煤层气储层孔隙度、渗透率测井综合评价成果
Fig. 6. Integrated well-log evaluation of porosity and permeability in deep coalbed methane reservoirs
图 7 深层煤岩样品等温吸附‒核磁共振联测实验
Fig. 7. Combined isothermal adsorption and nuclear magnetic resonance (NMR) measurements on deep coal samples
图 8 深层煤储层测井解释含气量成果
Fig. 8. Well-log interpretation results of gas content in deep coal reservoirs
图 9 深层煤储层含气含水测井识别图版
Fig. 9. Well-log crossplots for gas-water identification in deep coal reservoirs
图 10 大吉区块深层煤层气“成像+声波”测井的双轨联动地应力评价成果
Fig. 10. Integrated evaluation results of in-situ stress from image and sonic logs in the Daji Block deep coalbed methane reservoirs
图 11 大吉X井“六性”关键参数综合测井评价成果
Fig. 11. Integrated well-log evaluation results of key six-property parameters in Well Daji-X
表 1 “六性”参数体系科学内涵
Table 1. Scientific connotation of the "six properties" parameter system
六性 核心内涵 关键评价内容 地质属性 岩性 工业组分、显微组分、煤岩类型、夹矸与夹层识别 显微组分（镜质组、惰质组）；矿物组成（黏土、石英、黄铁矿等）；工业组分（灰分、水分、挥发分、固定碳）；宏观煤岩类型 生烃性 生气能力与有机质演化 总有机碳含量（TOC）；镜质体反射率（Ro）；有机质成熟度、有机质类型 物性 储集空间与渗流能力 孔隙度；渗透率；孔隙结构、割理 含气性 气体赋存与资源丰度 含气量；吸附气/游离气比例；含气饱和度 工程属性 可压性 岩石力学特征与可压裂性 可压性指数；杨氏模量、泊松比；脆性矿物含量（石英、方解石等） 应力特性 地应力场及其对裂缝的控制 三向主应力；应力方向；各向异性 
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表 2 “六性”参数测井响应特征
Table 2. Logging response characteristics of the "six properties" parameters
测井方法 主要测量参数 核心响应特征与“六性”评价应用 常规测井 GR、DEN、CNL、AC、RT、CAL、SP、Pe 岩性识别：煤层表现为“三高（AC、CNL、RT）三低（GR、DEN、Pe）”；含气性：RT升高与“气测效应”指示含气；物性：DEN、AC、CNL用于计算孔隙度 核磁共振 T2谱、孔隙度、可动流体 物性：T2谱表征孔隙结构，评价孔隙度、渗透率；含气性：孔隙度亏损与T1‒T2谱识别吸附气与游离气 电成像 动静态成像 岩性/结构：识别煤体结构、层理与宏观裂隙；应力特性：井壁崩落与诱导缝指示地应力方向 阵列声波 DTC、DTS、快横波方位 脆性：计算动态杨氏模量与泊松比；应力特性：横波各向异性反演应力方向，结合模型预测应力大小 元素测井 Si、Ca、Al、Fe、C、O等 岩性：定量计算矿物组成与工业组分等；生烃性：计算TOC等；
脆性：脆性矿物（石英、方解石）含量计算
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表 3 煤岩与页岩、常规油气储层骨架差异性
Table 3. Matrix differences among coal, shale, and conventional oil and gas reservoirs
特征 常规油气储层 页岩气储层 煤岩储层 有机骨架占比 ＜1% 5%~30%（中等） ＞80%（绝对主导） 无机矿物占比 ＞95%（主导） 70%~95%（主要） ＜20%（次要杂质） 核心有机组分 无（干酪根可忽略） 干酪根（Ⅰ/Ⅱ型） 煤基质（镜质组为主） 孔隙主导类型 粒间孔/溶蚀孔（＞50 nm） 有机孔+无机孔（5~100 nm） 微孔（＜2 nm） 流体赋存主导形式 游离态（100%） 吸附态（30%~60%）+游离态 吸附态（＞80%）
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表 4 不同岩性测井参数响应特征
Table 4. Logging parameter response characteristics of different lithologies
测井参数岩性 电阻率（Ω·m） 自然伽玛（API） 补偿密度（g/cm3） 补偿中子（%） 声波时差（μs/m） 煤层 100~3 000 15.0~100.0 1.20~1.60 40.0~60.0 350.0~450.0 泥岩 5.0~40.0 150.0~300.0 2.15~2.76 20.0~55.0 200.0~330.0 砂岩 40.0~200.0 18.0~110.0 2.35~2.79 2.5~20.0 197.0~260.0 灰岩 200.0~2 000 18.0~95.0 2.50~2.88 0~7.0 150.0~200.0
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表 5 深层煤层气储层宏观煤岩类型判别标准
Table 5. Identification criteria for macrolithotypes in deep coalbed methane reservoirs
宏观煤岩类型 宏观煤岩类型判别指数 光亮煤 ＞0.6 半亮煤 0.4~0.6 半暗煤 0.2~0.4 暗淡煤 ＜0.2
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表 6 深层煤岩气储层脆性评价理论基础与参数体系
Table 6. Theoretical basis and parameter framework for brittleness evaluation in deep coal reservoirs
参数类型 测井响应参数 物理意义 常规测井 自然伽马（GR） 泥质含量与成熟度指示 补偿密度（DEN） 体积密度与孔隙度计算 伽马能谱测井 钾(K)、钍(Th)、铀(U)含量 有机质与放射性矿物指示 阵列声波测井 纵波时差（Δtp）、横波时差（Δts） 孔隙度与岩性表征 元素测井 硅(Si)、铝(Al)、钙(Ca)含量 矿物组分定量表征
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表 7 基于“六性”关系的深层煤层气储层测井综合评价分类指标
Table 7. Classification criteria for comprehensive well-log evaluation of deep coalbed methane reservoirs based on the six-property relationships
评价参数 评价指标 Ⅰ类 Ⅱ类 Ⅲ类 岩性 灰分 ＜15% 15~30% ＞30% 镜质组 ＞70% 50~70% ＜50% 宏观煤岩类型 光亮煤 光亮煤+半亮煤 半亮煤+半暗煤 煤岩厚度（m） ＞5.0 5.0~3.0 ＜3.0 顶底板岩性组合 灰‒煤‒泥组合 泥‒煤‒泥组合 砂‒煤‒泥组合 生烃性 镜质体反射率Ro, max（%） 1.9~4.0 1.9~2.5 ＜1.9 TOC（%） ＞70 50~70 ＜50 物性 孔隙度（%） ＞5.0 3.0~5.0 ＜3.0 渗透率（mD） ＞0.2 0.1~0.2 ＜0.1 含气性 总含气量（m3/t） ＞20 15~20 ＜15 可压性 煤体结构 原生‒碎裂 碎裂‒碎粒 碎粒‒糜棱 脆性指数 ＞40 25~40 ＜25 应力特性 顶板应力差（MPa） ＞15 10~15 ＜10 底板应力差（MPa） ＞10 7~10 ＜7 两向应力差（MPa） ＜2 2~4 ＞4
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