Coal body structure identification by logging based on coal accumulation environment zoning and its application in Mabidong Block, Qinshui Basin
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摘要: 煤体结构的测井曲线判别是一种高效经济的地球物理判别方法，但是受沉积环境和煤储层物性等因素影响，测井曲线具有多解性，造成煤体结构测井响应不明显，由此得到的判别方法也会有区域局限性。因此，在进行测井判别之前，需要对除煤体结构以外的影响测井曲线的因素加以控制。以沁水盆地马必东区块3号煤为例，首先利用煤心灰分与伽马测井曲线的正相关性进行煤心归位，以确保测井深度与取心深度的一致性；再利用煤心的镜质组与惰质组含量之比(镜惰比)对工区的聚煤环境进行分区，并优选聚煤环境相近分区的测井曲线。结果表明，电阻率系列曲线可以较清晰地反映该地区的煤体结构，受探测深度的影响，声波曲线无法准确地反映该地区煤体结构的变化规律。利用取心井训练的多测井曲线随机森林模型对未取心井煤体结构进行预测和判定，实测压裂曲线检验表明，预测结果与实测数据吻合率高。应用表明，基于聚煤环境分区的煤体结构测井判别方法可以反映煤体结构分布规律，指导压裂工作，降低煤层气开发成本，且有助于指导跨区块的煤体结构测井响应研究。Abstract: Identification of coal body structure by logging curves is an efficient and economical geophysical method. However, due to the influence of sedimentary environment and coal reservoir property, logging curves have multiple solutions, leading to an unclear logging response of coal body structure. And the identification rules acquired in one place cannot be applied in another place. Therefore, before starting logging discrimination, it is necessary to control the factors influencing well logging apart from coal structure. This essay takes an example from No.3 coal seam in Mabidong Block, Qinshui Basin. Firstly, coal cores are relocated to their logging depth by the positive correlation between ash content and gamma logging curves. And then, the coal-accumulating environment is divided by the ratio of vitrinite content to inertinite content. After that, the logging curves of similar environment are selected preferably. The result shows that resistivity logging serial curves can indicate the changes in coal body structure clearly, while acoustic wave logging cannot because of its shallow penetration depth. Finally, the Random Forest Model built by the chosen curves is used to predict other wells' coal body structure. The predicted results and the measured fracturing curves show that the results are in good agreement with the measured data. According to the application, the method can predicate the allocation of coal body structure, instruct hydraulic fracturing, which reduces development cost, and provide guidance to the logging response study on multi-regional coal body structure.
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图 4 西南区镜质组含量与深侧向电阻率交会图
Fig. 4 Crossplot of vitrinite content maceral and deep lateral resistivity
表 1 煤心归位前煤心参数与测井曲线Pearson相关系数
Table 1 Pearson correlation coefficient of coal core parameters and logging curves before position restoring
测井参数 总气含量 水分 灰分 挥发分 全硫 镜质组 惰质组 有机组分 Rmax 孔隙率 声波时差 0.09 0.09 –0.19 0.12 0.12 –0.19 0.06 0.02 –0.25 –0.22 井径 0.07 –0.08 –0.20 0.15 0.15 –0.14 0.10 0.06 –0.24 –0.24 中子 0 0.01 –0.17 0.21 0.21 0.27 0.27 0.24 0 –0.19 密度 –0.01 –0.12 –0.02 –0.14 –0.15 –0.13 0.09 0.04 0.02 –0.03 自然伽马 –0.20 0.02 0.17 –0.12 –0.13 –0.08 –0.04 –0.05 0.07 0.08 自然电位 0.13 0.01 0.01 –0.01 –0.01 –0.18 –0.28 –0.24 –0.13 0.06 深侧向(对数) 0.21 –0.04 –0.01 –0.08 –0.07 –0.18 –0.22 –0.20 –0.08 0.10 浅侧向(对数) 0.12 –0.02 –0.01 0.12 0.12 –0.12 –0.04 –0.03 –0.02 0.03 冲洗带电阻率(对数) –0.01 0.08 0.19 –0.04 –0.05 0.09 –0.04 –0.04 –0.01 0.03 
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表 2 煤心归位后煤心参数与测井曲线Pearson相关系数
Table 2 Pearson correlation coefficient of coal core parameters and logging curves after position restoring
测井参数 总气含量 水分 灰分 挥发分 全硫 镜质组 惰质组 有机组分 Rmax 孔隙率 声波时差 –0.03 0.15 –0.21 –0.26 0.02 –0.09 0.22 0.12 –0.20 0.09 井径 0.05 0.16 –0.02 0.01 0.07 –0.22 0.24 0 –0.21 –0.04 中子 –0.23 0.26 –0.14 –0.27 0.01 –0.01 0.17 0.16 –0.22 0.28 密度 0.07 –0.35 0.14 0.15 –0.12 –0.20 –0.13 –0.36 –0.05 –0.08 自然伽马 –0.40 –0.28 0.59 0.58 –0.06 –0.31 –0.29 –0.64 –0.09 –0.15 自然电位 0.24 –0.08 0.02 0.07 –0.04 –0.23 0.04 –0.22 0 –0.19 深侧向(对数) 0.28 0.25 –0.15 –0.21 0.32 0.45 –0.12 0.38 0.11 0.14 浅侧向(对数) 0.23 0.27 –0.10 –0.16 0.37 0.48 –0.18 0.36 0.13 0.15 冲洗带电阻率(对数) 0.28 0.25 –0.08 –0.15 0.29 0.37 –0.14 0.26 0.46 0.01
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