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世界地质 2021, 40(1) 140-145 DOI: ISSN: 1004-5589 CN: 22-1111/P

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	地震资料
	小波变换
	多尺度
	旋回识别
	本文作者相关文章
	陈思民
	朱建伟
	孟庆涛
	PubMed
	Article by Chen S
	Article by Zhu J
	Article by Meng Q

基于地震资料的多尺度小波变换识别沉积旋回技术

1. 吉林大学地球科学学院，长春130061;

2. 吉林省油页岩与共生能源矿产重点实验室，长春130061;

3. 东北亚生物演化与环境教育部重点实验室( 吉林大学) ，长春130061

摘

摘要：为探究基于地震资料的不同尺度小波变换方法下的沉积旋回识别特点，秉承前人运用测井数据连续小波变换进行地层旋回划分的依据和思路，以合成记录标定为桥梁，成功利用地震资料对歧口坳陷古近系沙三段31 砂组进行旋回划分。通过建立理想声波曲线模型，总结了旋回界面和旋回内转换界面与能谱图和不同尺度小波系数曲线对应特征，并对实际测井资料进行连续小波变换完成旋回划分。同时提取井旁地震道，获得旋回与地震道不同尺度小波系数曲线关系图，总结利用地震资料不同尺度小波变换系数曲线划分旋回最优方法。实际应用效果表明，利用地震资料大尺度( a100) 小波系数控制旋回界面范围条件下，运用小尺度( a5) 小波系数曲线可进行精细旋回划分，该方法充分发挥了地震资料横向分辨率较好的特点，同时提高了地震资料纵向分辨率，使得利用地震资料对沉积旋回进行识别更加精细。

关键词：地震资料小波变换多尺度旋回识别

Identification of sedimentary cycles using multi － scale wavelet transform based on seismic data

1. College of Earth Sciences，Jilin University，Changchun 130061，China;

2. Key Lab of Oil Shale and Coexistent Energy Minerals of Jilin Province，Changchun 130061，China;

3. Key Laboratory for Evolution of Past Life and Environment in Northeast Asia ( Jilin University) ，Ministry of Education，Changchun 130061，China

Abstract: In order to explore the characteristics of sedimentary cycle identification under different scale wavelet transform methods based on seismic data，following the basis and idea of using continuous wavelet transform of logging data to divide stratigraphic cycles，synthetic record is used as a bridge to successfully use seismic data to divide 31 sand groups of the 3rd Member of Paleogene Shahejie Formation in the Qikou depression into cycles． Through the establishment of an ideal acoustic curve model，the corresponding characteristics of the cycle interface and the transition interface within the cycle，the energy spectrum and the wavelet coefficient curves of different scales are summarized，and the actual logging data are subjected to continuous wavelet transform to complete the cycle division． At the same time，the seismic trace beside the well was extracted，and the relationship between the cycle and the wavelet coefficient curve of the seismic trace at different scales was obtained，and the optimal method for dividing the cycle using the wavelet transform coefficient curve of the seismic data at different scales was summarized． Practical application results show that under the condition that the large-scale ( a100) wavelet coefficients of

seismic data are used to control the range of the cycle interface，the small-scale ( a5) wavelet coefficient curve can be used to perform fine cycle division． This method gives full play to the characteristics of better lateral resolution of

seismic data，and at the same time improves the vertical resolution of seismic data，which makes the identification of sedimentary cycles with seismic data more precise．

Keywords: seismic data wavelet transform multiscale cycle identification

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