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物探与化探, 2023, 47(3): 681-689 doi: 10.11720/wtyht.2023.1273

地质调查·资源勘查

分频AVO技术在安岳气田须二段储层含气性分析中的应用

宋晨,1, 金吉能,1, 潘仁芳1, 朱博远1, 喻志骅2, 唐小玲3

1.长江大学 地球科学学院,湖北 武汉 430100

2.中国石油勘探开发研究院,北京 100007

3.华北油田勘探开发研究院,河北 任丘 062552

Application of frequency division AVO in the gas-bearing analysis of reservoir in the Xu-2 Member of the Anyue gas field

SONG Chen,1, JIN Ji-Neng,1, PAN Ren-Fang1, ZHU Bo-Yuan1, YU Zhi-Hua2, TANG Xiao-Ling3

1. School of Earth Sciences,Yangtze University,Wuhan 430100,China

2. Research Institute of Petroleum Exploration and Development,Beijing 100007,China

3. Exploration and Development Research Institute of Huabei Oilfield,Renqiu 062552,China

通讯作者: 金吉能(1986-),男,副教授,主要从事储层地球物理表征和非常规油气资源评价方面的研究工作。Email:Jinjineng@yangtzeu.edu.cn

第一作者: 宋晨(1997-),女,现正攻读矿物学、岩石学、矿床学专业硕士学位,主要从事地球物理研究工作。Email:390172641@qq.com

责任编辑: 叶佩

收稿日期: 2022-06-4   修回日期: 2023-03-21  

基金资助: 国家科技重大专项课题“致密气有效储层预测技术”(2016ZX05047-002)

Received: 2022-06-4   Revised: 2023-03-21  

摘要

四川盆地安岳气田须二段致密气储量丰富,地质特征相对复杂,常规 AVO分析方法预测储层含气性分布的精度较低,需要研究采用更加精细的地震预测方法。基于单井岩石物理和正演模型特征分析,采用基于小波变换下的分频AVO反演,优选出优势频段的AVO属性进行融合构建含气性因子,进而对安岳气田须二段有利含气富集区带进行分布预测。结果表明,须二段气层主要表现为Ⅳ类AVO响应异常。优势频段35~45 Hz的气、水层AVO响应比全频段的AVO响应的差异特征较明显,差异性更大,更易突出含气响应特征;AVO含气性敏感属性为相对横波速度差异、相对泊松比差和流体因子,经融合得到含气指示因子的负异常区域指示含气有利区;井震对比可知优势频段AVO属性的含气性预测效果较好。该方法以期为非常规油气勘探提供技术支撑。

关键词: 分频AVO; 小波变换; 优势频率; 致密气砂岩; 储层预测

Abstract

The second member of the Xujiahe Formation (the Xu-2 Member) in the Anyue area of the Sichuan Basin enjoys abundant tight gas reserves.However,this member has complex geological characteristics,and conventional amplitude versus offset (AVO) analysis has relatively low precision in predicting the gas-bearing property of the reservoir in this member.Therefore,it is necessary to develop a more fine-scale seismic prediction method. Based on the analysis of single-well petrophysical characteristics and forward models,the AVO attributes of the dominant frequency range were selected through the frequency division AVO inversion based on wavelet transform.Then,these AVO attributes were fused to form the gas-bearing indicator,using which the distribution of favorable gas-enrichment zones in the Xu-2 Member of the Anyue area was predicted.The results are as follows:The gas zones in the Xu-2 Member primarily present class IV AVO anomalies;For the gas and water zones,their AVO responses in the dominant frequency range (35~45 Hz) differed significantly from those in the full frequency band,and their gas-bearing response characteristics were more pronounced in the dominant frequency range;The AVO attributes sensitive to the gas-bearing property included the difference in the S-wave velocity,the difference in Poisson's ratio, and the fluid factor.The gas-bearing indicator was obtained through the fusion of these AVO attributes,and the negative anomalies of the gas-bearing indicator were indicative of favorable gas-bearing zones;The seismic-log correlation shows that the AVO attributes in the dominant frequency range yielded positive gas-bearing prediction effects.The method proposed in this study is expected to provide technical support for unconventional oil and gas exploration.

Keywords: frequency division AVO; wavelet transform; dominant frequency; tight gas sandstone; reservoir prediction

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本文引用格式

宋晨, 金吉能, 潘仁芳, 朱博远, 喻志骅, 唐小玲. 分频AVO技术在安岳气田须二段储层含气性分析中的应用[J]. 物探与化探, 2023, 47(3): 681-689 doi:10.11720/wtyht.2023.1273

SONG Chen, JIN Ji-Neng, PAN Ren-Fang, ZHU Bo-Yuan, YU Zhi-Hua, TANG Xiao-Ling. Application of frequency division AVO in the gas-bearing analysis of reservoir in the Xu-2 Member of the Anyue gas field[J]. Geophysical and Geochemical Exploration, 2023, 47(3): 681-689 doi:10.11720/wtyht.2023.1273

0 引言

四川中部须家河组油气储量广泛分布,其中安岳气田区域其构造位于上三叠统须家河组,地层受造山运动影响,受到了长期的挤压与压实作用,其构造格局介于挤压构造与挤压走滑构造之间,少数逆断层发育,变形较弱,存在众多小型圈闭,是典型的丘陵地貌。该构造带中的低缓短轴背斜非常有利于油气成藏。

本文研究目的层段为川中须家河组二段,其分布较为广泛,为一套砂泥岩互层完整的生储盖组合[1-2]。须二段为以灰色中—细粒砂岩为主的大规模辫状河三角洲沉积,是须家河组含油气层的主要储集层系,表现为典型的“厚砂薄储”的特点[3]。储层强烈的压实作用和广泛的胶结作用使须二段储层受到很强压实作用,具有非均质性特征[4-5],导致使用一种参数模型无法评价所有探井。同时,储层孔隙度平均8.36%,主要分布在4%~12%;渗透率平均为0.25×10-3μm2,主要为(0.05~0.55)×10-3μm2,属于典型的低孔、低渗致密砂岩储层。因此,须二段储集层在沉积作用、成岩作用和构造作用等多种因素控制下,具有非均质性显著、埋藏深、成岩改造强烈的特点[6]。储层的强非均质性使得利用常规测井、地震等手段对含气性参数的计算变得更为复杂,给储层预测带来了新的挑战。

为进一步提升须家河组的储层含气性预测精度,关旭等[8]采用近道、远道反射特征对比与AVO主振幅主频率技术相结合的方法,对须二段含气有利区分布进行预测。Lu等[9]则利用气藏中“低频阴影”和“高频衰减”的特征,将气藏与水藏区分开。以上基于地震信号的时频分析已被用来区分徐家河组的气藏和含水层。来自地下的地震反射波信息通常是多层介质的综合响应,每一个薄层产生的地震信号在频率域都有一个与之对应的特定频率,在有效地震频率范围内(10~60 Hz),通常这种频率成分在频率域是唯一的[10-12]。由于受地层厚度、地震波反射频率耦合等不确定因素的影响,导致在实际应用中AVO反演的效果存在较大差异,增加了预测结果的不确定性。地震分频AVO技术作为一种基于频谱分析的地震成像解释新方法,更为全面的涵盖到了地层分界面两侧的弹性参数和频率因素[10]。许多学者在叠前AVO分析及地震属性计算中采用了时频分析工具进行分频研究。路慎强[13]和宁媛丽等[14]利用叠前分频AVO方法消除薄层调谐效应对AVO的影响,以解决薄互层储层AVO识别问题。孔栓栓等[15]研究分频振幅检测浅层“亮点”型气层的方法。然而致密气储盖组合空间差异大,层间物性差异小等特点决定了其预测技术要求更加精细,因此分频AVO技术应用于致密气储层预测还需进一步研究。

本文以安岳气田须家河二段储层地质特征为指导,引入分频AVO分析方法来对气层和水层进行区分,并对该地区须二段的含气储层进行综合预测。通过分频AVO分析技术在须家河组储层中的实际应用,较好地解决了气水分异难题,提高了须二段的气藏预测精度。

1 AVO正演模拟分析

在油气勘探阶段,地震相关特性由于受到岩石流体的影响而发生改变,因此可以将岩石物理作为地震与油藏的转换纽带。AVO属性参数对储层的岩性、物性和含气性具有一定的指示作用,存在较为明确的地质意义。而对于含气储层来说,不同的AVO属性的敏感程度存在一定的差异,因而需要对不同的属性参数进行敏感性分析,从中选取最优的敏感属性组合。AVO模型正演有助于确定预测目标区含气砂岩的AVO异常类型,进而为分频处理提供有效的地震道集[16]。此外,还需要以正演模型的AVO异常响应特征为指导对属性参数进行储层含气性解释[17]

1.1 不同流体地震频谱特征

对研究区中10口井的气层及水层分别提取井旁道振幅频率谱(图1)。基于地震频谱特征分析还可认识气层、水层的频谱关系(图2)。从图2中可看出:川中地区气层主频在32 Hz左右,有效频带在32~46 Hz;水层地震反射主频在46 Hz左右,有效频带在46~62 Hz。据此分析认为,气层比水层的主频较低,且气层、水层的有主频存在明显差异,主要是由于气层段受吸收衰减作用的影响相对较大所致[18]

图1

图1   不同流体类型储层井旁道频谱差异

Fig.1   Spectrum difference diagram of sidetrack in reservoir with different fluid types


图2

图2   典型气、水层地震频谱特征

Fig.2   Seismic spectrum characteristics of typical gas and water layers


1.2 气层AVO响应特征

研究中基于实际井资料对其须二段气层及水层进行分频AVO正演模拟,从中选取了2口直井进行展示说明。以A井为气层的典型井,B井为水层的典型井。从测井曲线上可知,气层相对于上覆盖层,其密度、纵横波速度都减小,储盖界面处于波谷。由图3可知,对A井气层反射振幅变化趋势分析认为,随着入射角度的增大,须二段气层顶界面反射振幅呈现增大的趋势(图3c)。B井水层其顶界面反射振幅随入射角的增加而减小,但减小趋势较为不明显(图3d)。其研究气层与水层的P-G响应特征具有较明显的区分性(图4)。

图3

图3   A井及B井正演模拟

a—A井测井曲线与正演道集;b—B井测井曲线与正演道集;c—A井AVO曲线;d—B井AVO曲线

Fig.3   Forward modeling of well A and well B

a—logging curve and forward trace gather of well A;b—logging curve and forward trace gather of well B;c—AVO curve of well A;d—AVO curve of well B


图4

图4   研究区多井气、水层P-G交会

Fig.4   P-G cross plot of multi well gas and water layer in the study area


为进一步明确研究区气层与水层的分频AVO异常响应特征,对A、B两口井选择6个不同的频率(10、20、30、40、50、60 Hz)进行显示(图5),利用P-G交汇图的特征,分析其气层及水层的AVO响应特征,确定其是否为有利的油气储层[19]。由图6可知,在频率35~45 Hz范围内,气层与水层响应差异最大,并且随着频率的增大,气层AVO响应由从Ⅳ类向Ⅲ类进行逆时针偏转;水层则从Ⅲ类向第一象限偏转。经上述分析认为,频率35~45 Hz频段范围内响应差异性最为明显,因此选取为优势频段。

图5

图5   A井及B井分频AVO曲线

a—A井气层;b—B井水层

Fig.5   Frequency division AVO curve of well A and well B

a—gas layer of well A;b—water layer of well B


图6

图6   A井气层及B井水层分频P-G交会

Fig.6   Frequency division P-G cross plot of gas layer of well a and water layer of well B


2 分频处理分析

2.1 基于小波变换的分频处理技术

时频分析技术的根基是于18世纪提出的傅里叶变换(FT)。时频分析技术是一种利用时间与频率的联合函数来分析信号的方法[20-23]

1984年Morlet等[24]提出了连续小波变换,其核函数是Morlet小波。小波变换是一种利用偏移缩放的模式获取有效信息的时频分析方法,其出现时间较早,发展时间较长,研究体系已相对成熟。地震信号往往是以非平稳信号的形式表现的,在已知非平稳信号xτ,依据小波变换的定义,则其变化式可表示如式(1):

CWTa,b=1a xτψ*τ-badτ

其中:CWTa,b为小波系数谱;ψ*τ为母小波ψτ的复共轭小波;ab均为描述小波性质的参数,a为尺度系数,b为平移系数。通过拉伸平移的变化则得到一系列小波,这些小波被称为小波族,其表达式如式(2):

ψa,bτ=1a ψτ-ba

较于傅里叶变换而言,由于其时窗可以自适应调节,被誉为“数学显微镜”,因此在一定程度上使得时间与频率在分辨率方面的矛盾有所缓解,其局部特征描述也较细致。基于以上特点,利用在应用范围上相对广泛的小波变换分频技术进行分频AVO分析。

2.2 叠前道集分频处理

为了进一步增加分频结果的准确性,在AVO分析的基础上,需对CPR道集进行加工处理,如剩余时差微校正、超道集、角道集等。在叠前反演之前先进行AVO目标处理,相较于共中心点道集,叠前地震角道集(图7)可以通过对比振幅在不同地层界面上相同角度内的变化趋势,进而对地层流体和岩性的特征进行识别[25-27]。从提取的A井和B井的实际井旁原始道集的振幅响应曲线可以看出,A井气层的原始叠前道集的AVO响应曲线与B井水层的响应特征一致(图8),其井旁道集振幅响应均随角度的增大而减小。上述结论与两口井的正演模型结果不同,并且A井的模型正演响应特征与地震响应特征明显相反(图3c图8a)。由于测井资料真实可信,而常规地震处理方法在低频保护、分辨率提高、AVO 特征的道集保护等方面针对性不强,地震道集资料较差,AVO 响应特征分析受到影响较大[28],因此需对叠前道集进行分频处理。

图7

图7   A井气层(a)及B井水层(b)的叠前地震道集

Fig.7   Prestack seismic gathers passing through gas layer of well A(a) and water layer of well B(b)


图8

图8   A井气层(a)及B井水层(b)的原始叠前道集振幅响应特征

Fig.8   Amplitude response characteristics of original prestack gathers of gas layer in well A(a) and water layer in well B(b)


通过前期对频谱的统计及一系列的频率试验,研究区目的层段气层在35~45 Hz范围内AVO 响应特征更好。因此采用小波变换进行叠前资料的分频处理,结合优势频段,采用35~45 Hz的分频数据体作为AVO属性分析的道集数据(图9),提取A井及B井井旁的振幅响应曲线(图10)。从图中可以看出,A井的井旁道集振幅响应随角度的增大而增大;B井井旁道集振幅响应随角度的增大而减小。此结论与正演模型结论一致。由此可见,分频叠前地震数据可以有效区分储层特性。特定频率段的分频道集更能清晰反映相应储层的岩性组合和岩石物理性质,而分频处理是保证AVO正演模拟准确性的必要手段。

图9

图9   A井气层(a)及B井水层(b)的35~45 Hz角道集

Fig.9   35~45 Hz angle gathering through gas layer of well A(a) and water layer of well B(b)


图10

图10   35~45 Hz分频数据体在A井气层(a)及B井水层(b)的井旁的振幅响应曲线

Fig.10   Amplitude response curve of 35~45 Hz frequency divided data volume at the well side of gas layer of well A(a) and water layer of well B(b)


3 分频AVO属性分析

3.1 分频AVO敏感属性优选

Zoeppritz方程主要表达入射波、反射波及折射波的振幅与角度的关系。由于该方程的变量复杂,因此前人对其进行简化。而AVO 反演方法的理论基础是由 Zoeppritz 方程简化后的 shuey 近似方程[29],其三参数近似方程可表示为

R(θ)  A + Bsin2θ + C(tan2θ-sin2θ) ,

而常用于AVO属性提取是通过Aki-Richards近似式、Shuey近似式提取得到[30-33]

Rpp=P+G×sin2θ ,

式(3)中:R(θ)为界面反射系数; θ为入射角; ABC分别为AVO截距、斜率和曲率,是 AVO 的3个基本属性参数。式(4)中:Rpp为垂直入射P波反射系数;G为反射振幅随偏移距变化率。PG为方程截距和梯度,是AVO双属性参数。对于不同的角度道集,通过角度道反射系数与角度的拟合关系可求取得到以上的基本属性,再依据属性之间的关系就能得到其他属性参数[17]

基于角度道集资料进行AVO属性反演,提取相对密度(DDN)、相对横波速度(DVS)、流体因子(FF)、相对泊松比(PR)、相对泊松比差(PRR)、相对横波反射率(RVS)和相对横波速度差异(VSR)等常见的AVO属性。常见的AVO属性的物理意义及计算公式见表1

表1   AVO属性物理意义及公式

Table 1  Physical meaning and formula of AVO attribute

AVO属性物理意义计算公式
差异横波速度反映出横波速度的
变化率特征
DVS=1+0.25k×C-0.25k×B-A
差异密度反映密度的变化
率特征
DDN=2A-C
差异纵波速度反映出纵波速度的
变化率特征
DVP=2C
流体因子显示与Castagna方
程不符的含油气区
FF=Rp-0.58Rs
泊松比反映岩层泊松比
的变化特征
PR=a×A+b×B
横波反射系数反映横波阻抗
的特征
RVS=a×A-b×B

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通过对工区10口井气层及水层的AVO属性剖面观察,相同位置剖面上,气层显示为负异常,水层显示为正异常。测井响应与属性图中负异常指示区域一致。对多井AVO属性与含气性响应吻合度对比(图11)可知,相对横波速度差异VSR、相对泊松比差PRR和流体因子FF的井震油气显示吻合度最高,可将其优选为含气性敏感属性,用于研究区的含气性预测。

图11

图11   多井AVO属性与含气性响应吻合度对比

Fig.11   Comparison of coincidence between AVO attribute and gas bearing response of multiple wells


3.2 含气性预测

从分频叠前道集中提取优势频段的流体因子(FF)、相对横波速度差异(VSR)、相对泊松比差(PRR)3个含气性敏感属性,构建优势频段流体指示因子,进行含气性分布预测。对上述3种相关性较高的属性赋予不同的权值,权值的计算为

Ci=Rij=13Rj,i,j=1,2,3

最后将含气敏感参数组合叠加求得到烃类指示因子DHI,即

DHI=i=13CiRi

式中:Ci分别为流体因子(FF)、相对横波速度差异(VSR)、相对泊松比差(PRR)的权重,单位%;Ri分别为流体因子(FF)、相对横波速度差异(VSR)、相对泊松比差(PRR)的定量化贡献度。主要是将流体因子属性、相对泊松比差及相对横波速度差异的值置于同一个数量级上,DHI的累计负异常可指示含气性分布情况。

本次研究对应地选取了过Yue111—Yue118—Yue145井属性连井预测剖面和须二段上亚段含气性预测平面来展示基于优势频段资料的AVO含气性预测结果(图1213)。色棒表示流体指示因子的正负,剖面和平面图中的黄色及绿色区域说明此处流体因子呈现为负异常,一般指示含气性分布区域。通过对比,整体负异常分布特征较为明显,说明流体指示因子对于含气性的敏感度较高,且预测异常区域与实际试气结果是一致的。

图12

图12   Yue111—Yue118—Yue145井连线的35~45 Hz优势频段属性预测剖面

Fig.12   Prediction profile of dominant frequency band with 35~45 Hz attribute of well Yue111—Yue118—Yue145 well


图13

图13   须二段上亚段DHI含气性预测平面对比

Fig.13   Plane comparison of DHI gas content prediction of upper sub member of Xujiahe formation 2


从含气性预测平面(图13)中可知,须二段上亚段含气区域主要分布工区东南部、中部一线,井震吻合度较高。此外,通过表2 AVO含气性异常响应对比可知,全频共有7口井井震对比吻合,分频有9口井吻合。因此,基于优势频段的相对横波速度差异VSR、相对泊松比差PRR和流体因子FF构建DHI,其含气性分布预测效果较于全频段的预测效果更好,与AVO属性响应最为一致。综上所述,分频AVO技术是目前进行储层预测最为有效的方法之一。

表2   AVO含气性异常响应对比

Table 2  Comparison of abnormal response of AVO gas bearing property

井名气测
结果
AVO
响应
全频井震对比分频井震对比
含气
响应
吻合
情况
含气
响应
吻合
情况
Yue103气井负异常吻合吻合
Yue111气井负异常较吻合吻合
Yue113气井负异常吻合吻合
Yue114气井正异常不吻合不吻合
Yue118气井负异常不吻合较吻合
Yue122水井负异常吻合吻合
Yue145气井负异常不吻合吻合
Yue101-3水井正异常吻合吻合
Yue112水井正异常吻合吻合
Yue125水井正异常吻合吻合

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4 结论

1)川中地区须二段气层和水层的主频存在差异,气层地震反射主频在32 Hz左右,有效频带在32~46 Hz;水层地震反射主频在46 Hz左右,有效频带在46~62 Hz。在优势频段35~45 Hz范围内,气层AVO响应从Ⅳ类向Ⅲ类进行逆时针偏转;水层则从Ⅲ类向第一象限偏转。

2)通过对川中地区须二段气层及水层的研究,在优势频段35~45 Hz范围内,AVO 响应特征更好,差异性更大,更易突出含气响应特征,且分频道集的叠前数据响应特征与原始地震是一致的。

3)优选相对横波速度差、相对泊松比差PRR和流体因子为含气性敏感属性,将其叠加后得到的烃类指示因子DHI的负异常指示含气有利分布区。基于分频AVO的预测比全频段的预测效果较好,能有效提高了川中地区须二段气藏富集区地震预测的精确度。

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The compressional wave reflection coefficient R(θ) given by the Zoeppritz equations is simplified to the following: [Formula: see text] The first term gives the amplitude at normal incidence (θ = 0), the second term characterizes R(θ) at intermediate angles, and the third term describes the approach to critical angle. The coefficient of the second term is that combination of elastic properties which can be determined by analyzing the offset dependence of event amplitude in conventional multichannel reflection data. If the event amplitude is normalized to its value for normal incidence, then the quantity determined is [Formula: see text] [Formula: see text] specifies the normal, gradual decrease of amplitude with offset; its value is constrained well enough that the main information conveyed is [Formula: see text] where [Formula: see text] is the contrast in Poisson’s ratio at the reflecting interface and [Formula: see text] is the amplitude at normal incidence. This simplified formula for R(θ) accounts for all of the relations between R(θ) and elastic properties first described by Koefoed in 1955.

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