| 大倾角煤层时深转换精度分析及改进方法 |
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| 引用本文： | 王惠风,符超,李果,陈同俊.大倾角煤层时深转换精度分析及改进方法[J].煤田地质与勘探,2022,50(10):145-150. |
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| 作者姓名： | 王惠风 符超 李果 陈同俊 |
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| 作者单位： | 1.国能神东煤炭集团有限责任公司，陕西 神木 719315 |
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| 基金项目： | 国家重点研发计划项目(2021YFC2902003)；国家自然科学基金项目(41774128) |
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| 摘 要： | 平均速度法是煤田地震勘探中应用最广泛的时深转换方法，但对于大倾角煤层来说，其平均速度横向变化快，插值精度差异大，无法有效保障煤矿智能化开采。通过分析大倾角倾斜煤层模型和实际三维采区，讨论多种平均速度插值方法的精度，并提出相应改进方法。正演模型计算结果表明，克里金法和多项式法直接插值时，生成的煤层底板高程精度受插值点位置影响巨大，无法达到大倾角煤层时深转换精度要求。为此，以叠加速度计算的平均速度为参考，综合多项式、克里金和支持向量机等方法，提出适合大倾角煤层时深转换的改进插值方法。将相关方法应用到二维模型数据和三维实例采区，发现改进方法插值生成的平均速度精度明显提高，插值误差远小于行业标准要求，适合大范围推广应用。
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| 关 键 词： | 地震勘探 大倾角煤层 时深转换 平均速度 插值精度 |
| 收稿时间： | 2022-01-10 |
Time-to-depth conversion accuracy analysis and improvement method for inclined coal bed |
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| Institution: | 1.Shendong Coal Group, CHN Energy, Shenmu 719315, China2.Key Laboratory of CBM Resource & Reservoir Formation Process, Ministry of Education, Xuzhou 221008, China3.School of Resource and Earth Science, China University of Mining and Technology, Xuzhou 221116, China |
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| Abstract: | The average-velocity method is the most commonly-used time-to-depth conversion technology for the seismic survey of coalbed. But for the steeply-inclined coalbed, the average velocity changes rapidly laterally, and the interpretation accuracy varies greatly, so that the intelligent coal mining could not be assured effectively. Herein, the accuracy of various average-velocity-interpolation methods was discussed by analyzing a steeply-inclined coalbed model and a practical 3D seismic mining area and appropriate improvement methods were proposed accordingly. The calculation results of a forward model show that the bottom elevation accuracy of coalbed is greatly affected by the locations of interpolation points in the case of direct interpolation using Kriging and Polynomial methods, which cannot meet the high-accuracy requirements of time-to-depth conversion for steeply-inclined coalbeds. Therefore, referring to the stack-velocity derived average velocity, an improved interpolation method of time-to-depth conversion applicable to the steeply-inclined coalbed was proposed by integrating the polynomial, Kriging and Support Vector Machine (SVM) methods, with reference to the average velocity calculated by stacking velocity. By applying the relevant methods to the 2D model data and the 3D example of mining area, it is found that the accuracy of average velocity generated by the improved interpolation method is significantly improved, with the interpolation error much smaller than the requirement of the industrial standard. Hence, the proposed method is suitable for large-scale popularization and application. |
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