地球物理技术最新进展:高分辨率地震频率和相位属性分析技术研究与应用效果

doi:10.13745/j.esf.sf.2022.8.36

摘要/Abstract

摘要：

随着地震勘探技术在石油勘探开发中的应用和发展,常规地震资料的分辨率已经难以满足精细勘探开发的需要。另外一方面,在复杂的地质条件下,有效提高地震资料定量解释的精度,准确识别含油气的有效储层并圈定有利区也是成功勘探开发的关键因素。经过多年来不断研究和试验,提出了一系列高分辨率定量解释的方法和技术。通过在多个地区碳酸盐岩、碎屑岩和非常规地质背景下的应用情况表明:高分辨率地震频率和相位属性分析技术等定量解释技术应用效果非常显著;地震资料频谱恢复提高分辨率处理技术可以大幅提高薄层、断裂、溶洞等地质细节的识别能力;多尺度断裂检测技术可以在识别大尺度断层的基础上能有效检测出小尺度的微断裂;高分辨率频谱分解和相位分解技术在传统的振幅信息基础上将地震属性分析拓展到频率和相位维度,大幅地增加了反映地下地质特征和含油气性的地震响应信息,还提高了地震解释的可靠性,降低了地质认识的多解性,使基于高分辨率定量解释技术的有效储层识别更加高效、准确。

关键词: 高分辨率地震, 频谱分解, 相位分解, 提高分辨率处理, 多尺度断裂检测

Abstract:

Seismic prospecting for oil and gas exploration and development is limited by seismic data resolution. Improving the accuracy of quantitative interpretation of seismic data in thin layers, thereby identifying effective reservoirs and delineating favorable areas, is often a key factor for successful exploration and development. Historically, the limit of seismic resolution is usually assumed to be about ¼ wavelength of the dominant frequency of the data in the formation of interest. After years of continuous research and testing, this assumed resolution limit of traditional seismic model has been broken, and a series of high-resolution quantitative interpretation methods and techniques have been developed. Case studies in carbonates, clastics, and unconventional reservoirs indicate that the application of quantitative interpretation techniques such as high-resolution seismic frequency and phase attribute analysis has produced remarkable results. Band recovery using high resolution seismic processing technology can greatly improve ability to recognize geological details such as thin layers, faults, and karst caves. Multi-scale fault detection technology can effectively detect small-scale faults in addition to more readily recognized large-scale faults. Based on the traditional seismic amplitude information, high-resolution spectral decomposition and phase decomposition technology expands seismic attribute analysis to the frequency and phase dimensions, boosting the seismic geological information content and reflecting subsurface geological characteristics and hydrocarbon potential, improve the reliability of seismic interpretation, and reduce the non-uniqueness of geological models. These technologies, based on high-resolution quantitative interpretation techniques, make the identification of effective reservoirs more efficient and accurate.

Key words: high-resolution seismic, spectral decomposition, phase decomposition, band recovery high resolution enhancement, multi-scale fault detection

中图分类号:

P597

姜仁旗, 吴键, John CASTAGNA, 周刚. 地球物理技术最新进展:高分辨率地震频率和相位属性分析技术研究与应用效果[J]. 地学前缘, 2023, 30(1): 199-212.

JIANG Renqi, WU Jian, John CASTAGNA, ZHOU Gang. Recent advances in geophysical technology: High-resolution seismic frequency and phase analysis techniques and applications[J]. Earth Science Frontiers, 2023, 30(1): 199-212.

图/表 15

图1 地层模型及反射系数示意图(据文献[3]修改)

Fig.1 Strata model and its reflectivity. Modified after [3].

图2 频率和峰值振幅随厚度变化图(据文献[3]修改)

Fig.2 Frequency and peak amplitude vs. thickness variation. Modified after [3].

图3 频谱恢复提高分辨率处理原理图(据文献[5]修改)

Fig.3 Schema of band recovery high resolution processing. Modified after [5].

图4 单地震道高分辨率频谱分解和其他方法对比(据文献[7]修改)

Fig.4 CLSSA,STFT and CWT spectral decomposition of a seismic trace. Modified after [7].

图5 单道相位分解为相位道集原理图

Fig.5 Schema of phase decomposition of a seismic trace

图6 单道相位分解为相位道集原理图

Fig.6 Schema of phase decomposition of a seismic trace

图7 相干体与多尺度断裂检测3D对比图 a—多尺度断裂检测体三维成果图;b—相干体断裂检测三维成果图。

Fig.7 3D views of fault detect and coherence volumes

图8 提高分辨率前、后地震剖面对比图 a—常规地震剖面;b—提高分辨率处理后地震剖面。

Fig.8 Seismic sections before and after high resolution processing

图9 断裂检测技术对比 a—相干体剖面图;b—多尺度断裂检测体剖面图。

Fig.9 Sections of coherence and fault detect

图10 预测缝洞体与断裂叠合图

Fig.10 Slice of fault detect overlay on Amplitude attribute (delineate caves)

图11 多个井点处原始地震剖面(a)、频率吸收衰减(b)和相位分量体对比剖面图(c) a—原始地震剖面;b—频率吸收衰减剖面;c—-90°相位分量体对比剖面图。

Fig.11 Sections of raw seismic(top), frequency absorption decay(middle) and -90° phase component (bottom)

图12 过SS9井联络线提高分辨率前、后叠合剖面变面积显示为常规剖面;变密度显示为提高分辨率处理后剖面。

Fig.12 Seismic sections of high-resolution processing(wiggle) overlay on raw(color)

图13 P层单频体刻画RMS振幅切片图

Fig.13 Slices of RMS amplitude on P layer in iso-frequency volumes

图14 过产气井原始地震与-90度相位分量剖面对比 a—过A井、B井常规地震剖面;b—过C井常规地震剖面;c—过A井、B井-90°相位剖面;d—过C井-90°相位剖面。

Fig.14 Sections of raw seismic and -90° phase component

图15 井点处提高分辨率前、后对比及波阻抗识别小层

Fig.15 Seismic sections before and after high-resolution processing

参考文献 28

[1]	杜世通. 地震属性分析[J]. 油气地球物理, 2004, 2(4): 12-16.
[2]	吕公河, 于常青, 董宁. 叠后地震属性分析在油气田勘探开发中的应用[J]. 地球物理学进展, 2006, 21(1): 161-166.
[3]	CASTAGNA J P. Recent advances in seismic lithologic analysis[J]. Geophysics, 2001, 66: 42-46. DOI URL
[4]	PURYEAR C I, CASTAGNA J P. Layer-thickness determination and stratigraphic interpretation using spectral inversion: theory and application[J]. Geophysics, 2008, 73(73): 37-48.
[5]	LIANG C, CASTAGNA J P. Tutorial: spectral bandwidth extension: invention versus harmonic extrapolation[J]. Geophysics, 2017, 82(4): 1-16.
[6]	CASTAGNA J P, SUN J, SIEGFRIED R W. Instantaneous spectral analysis: detection of low frequency shadows associated with hydrocarbons[J]. The Leading Edge, 2003, 22: 120-127. DOI URL
[7]	CASTAGNA J P. Comparison of spectral decomposition methods[J]. First Break, EAEG, 2006, 24: 75-79.
[8]	董艳蕾, 朱筱敏, 胡廷惠, 等. 泌阳凹陷核三段地震沉积学研究[J]. 地学前缘, 2011, 18(2): 284-293.
[9]	WIDESS M B. How thin is a thin bed?[J]. Geophysics, 1973, 38(6): 1176-1180. DOI URL
[10]	ZHANG R, CASTAGNA J P. Seismic sparse-layer reflectivity inversion using basis pursuit decomposition[J]. Geophysics, 2011, 76(6): 147-158.
[11]	CASTAGNA J P, OYEM A, PORTNIAGUINE O. Phase Decomposition[J]. Interpretation, 2016, 4(3): 1-10.
[12]	CHOPRA S, CASTAGNA J P. Seismic resolution and thin-bed reflectivity inversion[J]. CSEG Recorder, 2006, 11(2): 19-25.
[13]	MORA D, CASTAGNA J P, MEZA R. Case study: seismic resolution and reservoir characterization of thin sands using multiattribute analysis and bandwidth extension in the Daqing field, China[J]. Interpretation, 2020, 8(1): 89-102.
[14]	段友祥, 曹婧, 孙岐峰. 自适应倾角导向技术在断层识别中的应用[J]. 岩性油气藏, 2017, 29(4): 101-107.
[15]	田涛, 夏同星, 闫涛, 等. 地层倾角信息在断层精细刻画中的应用:以渤海湾盆地A油田为例[J]. 地球物理学进展, 2017, 32(5): 2236-2240.
[16]	徐德奎, 王玉英, 郑江峰. 倾角导向的相干加强技术在改善复杂断块地震资料中的应用[J]. 地球物理学进展, 2016, 31(3): 1124-1228.
[17]	尹川, 杜向东, 赵汝敏, 等. 基于倾角控制的构造导向滤波及其应用[J]. 地球物理学进展, 2014, 29(6): 2818-2822.
[18]	印兴耀, 高京华, 宗兆云. 基于离心窗倾角扫描的曲率属性提取[J]. 地球物理学报, 2014, 57(10): 3411-3412.
[19]	汪杰, 汪锐. 基于方差相干体的断层识别方法[J]. 工程地球物理学报, 2016, 13(1): 46-51.
[20]	李婷婷, 侯思宇, 马世忠, 等. 断层识别方法综述及研究进展[J]. 地球物理学进展, 2018(4): 1507-1514.
[21]	黄诚, 李鹏飞, 王腾宇, 等. 地震属性分析技术在小断层识别中的应用[J]. 工程地球物理学报, 2016, 13(1): 41-45.
[22]	甄宗玉, 郑江峰, 孙佳林, 等. 基于最大似然属性的断层识别方法及应用[J]. 地球物理学进展, 2020, 35(1): 374-378.
[23]	QI J, CASTAGNA J P. Application of PCA fault-attribute and spectral decomposition in Barnett Shale fault detection[J]. 83rd Annual International Meeting, SEG, Expanded Abstracts, 2013: 1421-1425.
[24]	韩磊, 张宏, 王劲松. 分频相干技术在复杂断裂解释中的应用[J]. 复杂油气藏, 2016, 9(4): 16-21.
[25]	BARBATO U, CASTAGNA J P, PORTNIAGUINE O. Composite attribute from spectral decomposition for fault detection[C]//SEG technical program expanded abstracts 2014. Tulsa: Society of Exploration Geophysicists, 2014: 2542-2546.
[26]	陈国飞, 吕双兵. RGB分频技术在断块油藏断层识别中的应用[J]. 复杂油气藏, 2015(2): 29-32.
[27]	陈波, 魏小东, 任敦占, 等. 基于谱分解技术的小断层识别[J]. 石油地球物理勘探, 2010(6): 890-894.
[28]	马承杰. 多尺度边缘检测技术在断层识别及裂缝发育带预测中的应用[J]. 油气地质与采收率, 2021(2): 85-90.