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变系数的强反射分离技术及应用
引用本文:陈科,王鹏燕,郑连弟,向坤,肖仁睿,伍国勇,王潇然.变系数的强反射分离技术及应用[J].科学技术与工程,2024,24(13):5358-5363.
作者姓名:陈科  王鹏燕  郑连弟  向坤  肖仁睿  伍国勇  王潇然
作者单位:中石化石油物探技术研究院有限公司
基金项目:国家科技重大专项(2017ZX05036-005-010)资助
摘    要:基于地震多子波分解的强反射识别与分离技术已广泛应用于地震解释性处理环节中,该技术能够去除强屏蔽影响,提高隐蔽储层的识别精度。针对多子波分解技术在分解效率和分解精度上的问题,引入地震信号的瞬时特性作为初始值,根据小波参数之间的关系减少局部扫描参数,提出了一种三参数快速子波分解技术提高了子波分解精度和效率。通过模型正演分析了地层厚度与强屏蔽能量的关系,建立了地层厚度与分离系数的关系,探索了一种变系数的强反射分离应用思路。将新技术和新思路应用于实际地震数据,分离结果削弱了强屏蔽的影响,突出了隐蔽储层的有效信号,提高了储层预测精度;由于强反射分离过程充分考虑了不同厚度的煤层与分离系数的关系,分离结果更加符合实际地质情况。

关 键 词:三参数    多子波分解    强反射    变分离系数    储层预测
收稿时间:2023/3/1 0:00:00
修稿时间:2024/2/5 0:00:00

Variable Coefficient Strong Reflection Separation Technology and its Application
Chen Ke,Wang Pengyan,Zheng Liandi,Xiang Kun,Xiao Renrui,Wu Guoyong,Wang Xiaoran.Variable Coefficient Strong Reflection Separation Technology and its Application[J].Science Technology and Engineering,2024,24(13):5358-5363.
Authors:Chen Ke  Wang Pengyan  Zheng Liandi  Xiang Kun  Xiao Renrui  Wu Guoyong  Wang Xiaoran
Institution:Sinopec Geophysical Research Institute
Abstract:Strong reflection recognition and separation technology based on seismic multiwavelet decomposition has been widely used in seismic interpretive processing. This technology can remove the influence of strong shielding and improve the identification accuracy of concealed reservoir. Aiming at the issues of decomposition efficiency and accuracy of multi-wavelet decomposition technology, the instantaneous characteristics of seismic signal were introduced as the initial value, and local scanning parameters were reduced according to the relationship between wavelet parameters. A three-parameter fast wavelet decomposition technology was proposed to improve the accuracy and efficiency of wavelet decomposition. The relationship between formation thickness and strong shielding energy was analyzed through model forward modeling, and the relationship between formation thickness and separation coefficient was established. A new application idea of strong reflection separation with variable coefficient was explored. The new technology was applied to the actual seismic data, and the separation results weakened the influence of strong shielding, highlighted the effective signal of concealed reservoir, and improved the accuracy of reservoir prediction. The strong reflection separation process fully considered the relationship between coal seams with different thickness and separation coefficient, and the separation result was more consistent with the actual geological conditions than conventional methods.
Keywords:three-parameters      mul-wavelet decomposition      strong reflection separation      variable separate coefficient      reservoir prediction
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