煤田隐伏陷落柱空间形态地震属性解释方法

Seismic Attribute Interpretation Methods for Spatial Form of Hidden Collapse Columns in Coalfields

隐伏陷落柱是煤矿隐蔽致灾的主要地质因素,然而,常规三维反射地震中,单一顺层属性或层间属性难以可靠识别隐伏陷落柱,同时对其垂向展布及伴生断裂等三维空间特征刻画不清。为此,在基于偏移距向量片(OVT)全方位处理数据体的基础上,计算相干、混沌等层间属性(奥灰顶界与目标煤层之间)与顺层两类属性,形成平面属性,采用波形聚类法对两类平面属性中的异常进行叠加处理,提高隐伏陷落柱的平面位置解释精度;其次,引入断层概率体属性处理技术,优选构造导向滤波处理以及数据体融合技术,精细刻画了隐伏陷落柱垂向边界形态、陷落高度及伴生断裂特征。通过融合波形聚类平面属性和断层概率体属性技术,形成了新的煤田隐伏陷落柱空间形态地震属性解释方法,显著提高了隐伏陷落柱的识别精度和空间形态刻画精度,有效提高了隐伏陷落柱解释精度和效率,为隐伏陷落柱的识别提供了新的途径,具有广阔的应用前景。

Hidden collapse column is the primary cause of potential disasters in coalmines.It is difficult to identify hidden collapse columns reliably with only single layer or inter-layer attributes ofconventional three-dimensional seismology.Meanwhile,the three-dimensional features such as the vertical distribution and associated fractures of hidden collapse columns cannot be clearly depicted.To solve these problems,coherence,chaos,and other inter-layer(between Ordovician limestone and upper coal seams)attributes and layer attributes were extracted to form plane attributes.The anomalies were recognized and overlaid by waveform clustering method for improving the interpretation accuracy of position in map of the hidden collapse.Furthermore,the fault-likelihood body attributes were processed,the structure-oriented filtering processing and co-rendering technology were used to finely describe the shape,fall height,and associated fractures of the hidden collapse column.A new method of seismic attribute interpretation for the spatial morphology of hidden collapse columns in coalfields was proposed by fusing waveform clustering planar attributes with fault-likelihood body attribute,which significantly improved the recognition accuracy and spatial morphological characterization of hidden collapse columns,and effectively enhanced the accuracy and efficiency of the hidden collapse column delineation.The results of this study provide a new way for the identification of hidden collapse columns,and have broad application prospects.