基于分频成像的小尺度溶洞检测

针对塔里木盆地小尺度缝洞储层识别的难题，提出一种基于叠前分频成像的小尺度溶洞识别技术。首先结合地震分辨率概念，通过不同主频地震子波正演模拟，说明高频地震资料对于提高小尺度缝洞体识别精度的必要性和实际意义；然后通过分析实际资料小尺度“串珠状”反射特征，确定小尺度溶洞频带范围，得到分频参数；再对CMP道集进行分频叠前时间偏移，得到高频数据体；最终利用高频数据体检测小尺度溶洞。实际地震数据处理结果表明，叠前分频（高频）数据体能很好地识别常规全频带数据体上难以识别的小尺度溶洞，大大提高了小尺度溶洞的预测精度，更有利于溶洞边界、轮廓的描述，预测结果与实际钻井数据相吻合，可进一步降低勘探、开发风险。

Small-scale cave detection based on frequency-segmented imaging

Aimed at the difficulties of small-scale fracture-cavern reservoir detection in Tarim Basin,we propose in this paper a new small-scale cave detection method.First with the concept of seismic resolution,we demonstrate the importance of high frequency seismic data for improving the detection accuracy of small-scale fracture-carven reservoirs through forward modeling with different dominant frequency.Then we analyze the small-scale bead-like reflection to determine the bandwidth of small-scale caves and obtain frequency segmenting parameters.After that,we carry out the frequency segmenting and prestack time migration for CMP gathers and get high frequency data volume.Finally we conduct small-scale cave detection based on the high frequency data volume.Based on seismic data processing results,small-scale caves can be effectively detected on high frequency data volume,but they cannot be detected on conventional data,and it is also very helpful to characterize cave boundaries.Our prediction is highly consistent with drilling results,which greatly avoids risks in the exploration and development.