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摘要:目的
富油煤作为一种集煤、油、气属性为一体的煤基油气资源，对于保障我国油气资源供应、实现煤炭清洁高效利用具有重要意义。目前富油煤的识别主要依靠格金干馏试验测量的焦油产率来判断，而利用地球物理手段准确识别与评价富油煤的研究则相对薄弱。
方法以新疆三塘湖盆地侏罗系西山窑组和八道湾组煤层为研究对象，基于岩石物理实验，在明确富油煤典型测井响应特征基础上，创新建立了一种煤焦油产率测井定量评价方法。
结果和结论结果表明：(1) 相比含油煤，富油煤具有富氢结构物质含量高、孔隙结构差的特点，这造成富油煤具有“低密度、高中子和高电阻率”的常规测井响应特征；(2) 通过多状态二维核磁共振实验测量分析，明确了富油煤具有“二维核磁T1谱双峰，T2<1、T1/ T2>10区域信号强”的核磁测井响应特征，而含油煤相应区域信号不明显，这与富油煤中富氢结构物质含量高有关；(3) 基于富油煤典型测井响应特征，提出利用电阻率和中子2个参数构建富油煤指示因子Z，Z越大，表明煤焦油产率越高。在煤焦油产率刻度基础上，建立了煤焦油产率与指示因子间的线性关系，实现了煤焦油产率的准确方便计算，可操作性强。上述认识为基于地球物理测井手段识别和评价富油煤提供了理论指导。
Abstract:ObjectiveAs a kind of coal-based oil and gas resource, tar-rich coal is significant for the supply of oil and gas resources, as well as the clean and efficient utilization of coals. Presently, the identification of tar-rich coals primarily depends on the Gray-King assay. In contrast, there is a lack of studies on the accurate identification and evaluation of tar-rich coal using geophysical methods.
MethodsThis study investigated coals in the Jurassic Xishanyao and Badaowan Formations in Santanghu Basin, Xinjiang. Based on petrophysical experiments, as well as the typical log response characteristics of tar-rich coal, this study developed a new log-based method for quantitatively evaluating the tar yield of tar-rich coal.
Results and ConclusionsKey findings are as follows: (1) Compared to tar-bearing coal, tar-rich coal features a high content of materials with hydrogen-rich structures and unfavorable pore structures, which contribute to the log response characteristics of low density, high compensated neutron logging, and high resistivity. (2) The multistate 2D NMR experiments reveal that tar-rich coal is characterized by double peaks of the T1 spectrum and strong signals in zones with T2<1 and T1/T2>10, while oil-rich coal shows insignificant singles in these zones. This contrast is related to the high content of materials with hydrogen-rich structures in tar-rich coal. (3) Based on the log response characteristics of tar-rich coal, this study established indicator Z for tar-rich coal using resistivity and neutron log curves, with a higher Z value indicating higher tar yield of the coal. Building on tar yield calibration, this study determined the linear relationship between the coal tar yield and Z, achieving the accurate, convenient, and practical calculation of the tar yield of tar-rich coal. The above understanding offers theoretical guidance for identifying and evaluating tar-rich coal based on geophysical logs.
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图 3 煤灰分产率与焦油产率、真密度关系
Fig. 3 Relationships of ash yield with tar yield and true density of coals
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图 4 煤的H/C与焦油产率、真密度关系
Fig. 4 Relationships of H/C with tar yield and true density of coals
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图 5 煤深侧向电阻率值与焦油产率关系
Fig. 5 Relationship between the laterolog resistivity and tar yield of coals
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图 6 不同煤孔隙结构特征对比
Fig. 6 Comparison of the pore structure characteristics of different types of coals
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图 7 煤电阻增大率与含水饱和度关系
Fig. 7 Relationship between the resistivity increasing rate and water saturation of coals
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图 8 不同煤二维核磁T1-T2特征
Fig. 8 2D NMR experiments-derived T1-T2 spectra of different types of coals
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图 9 不同状态下富油煤和含油煤二维核磁T1-T2谱图特征
Fig. 9 2D NMR experiments-derived T1-T2 spectra of tar-rich and tar-bearing coals under different states
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图 10 X1井西山窑组富油煤层识别与焦油产率计算
Fig. 10 Tar-rich coal seam identification and tar yield calculation of the Xishanyao Formation in well X1
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图 11 X2井八道湾组富油煤层识别与焦油产率计算
Fig. 11 Tar-rich coal seam identification and tar yield calculation of the Badaowan Formation in well X2
表 1 煤的基础数据
Table 1 Basic data of coal samples
样品
编号工业分析w/% 元素分析w/% 低温干馏成分质量分数/% 真密度/
(g·cm−3)Mad Ad Vdaf FCad Cd Hd Nd Od 水分 焦油产率 半焦产率 C1 10.77 7.58 32.35 55.79 75.04 3.86 0.63 12.75 16.5 3.9 68.7 1.45 C2 12.36 2.21 38.23 52.94 77.91 4.85 0.88 13.99 18.0 6.8 62.8 1.38 C3 8.77 4.03 50.44 43.39 74.03 5.77 0.77 15.26 11.0 18.7 57.9 1.29 C4 7.12 2.33 53.40 42.28 76.46 6.03 0.76 14.27 13.0 16.2 57.0 1.25 C5 6.00 6.45 55.01 39.56 74.11 6.06 0.81 12.37 14.0 16.9 55.4 1.27 C6 7.72 2.08 52.17 43.22 76.55 5.92 0.76 14.56 14.5 17.5 55.3 1.31 C7 5.92 2.44 57.70 40.12 77.51 6.68 0.83 12.39 12.5 22.5 52.3 1.24 C8 5.24 6.67 60.56 38.45 73.81 6.18 0.87 12.25 11.5 21.9 53.7 1.29 C9 10.24 4.61 28.10 61.56 76.74 3.32 0.69 14.52 16.5 1.7 70.1 1.52 C10 8.27 3.70 29.77 62.04 76.57 3.66 0.70 15.24 15.5 2.2 69.7 1.50 C11 7.97 2.91 31.72 61.01 76.74 3.87 0.83 15.49 15.0 2.2 70.7 1.48 C12 9.54 5.81 32.19 57.78 73.96 3.69 0.82 15.51 17.0 3.0 68.4 1.49 C13 4.21 1.57 50.19 46.97 76.23 6.12 0.71 15.23 13.0 13.2 59.6 1.30 C14 3.44 1.76 51.55 45.96 75.58 5.97 0.77 15.77 13.0 13.0 60.1 1.32 C15 2.66 2.75 61.74 36.22 75.79 7.29 2.85 13.05 11.5 23.8 50.4 1.26 
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表 2 不同煤样品实验分析数据及对应测井参数值
Table 2 Experimental data and corresponding log parameter values for different types of coal samples
样品编号 煤类型 焦油产率Tarad/% 氢质量分数/% 水分质量分数/% 孔隙率φ/% 电阻率值RT/(Ω·m) 中子值CNL/% C1 含油煤 3.9 3.86 10.77 22.4 150 55 C2 含油煤 6.8 4.85 12.36 21.0 1770 58 C3 富油煤 18.7 5.77 8.77 17.6 114500 63 C4 富油煤 16.2 6.03 7.12 14.7 150000 65
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表 3 不同煤样品MAPS图像分析结果
Table 3 Analytical results of MAPS images for different types of coal samples
样品
编号煤类型 总孔隙
面孔率/%有机孔隙
面孔率/%有机裂缝
面孔率/%有机质
体积分数/%C1 含油煤 12.25 6.44 5.81 85.71 C3 富油煤 0.71 0.25 0.46 98.74
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