准噶尔盆地玛西地区致密砂砾岩优质薄储层预测

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程志国, 胡婷婷, 瞿建华, 贺陆明. 准噶尔盆地玛西地区致密砂砾岩优质薄储层预测[J]. 物探与化探, 2015,39(5): 891-896.
CHENG Zhi-Guo, HU Ting-Ting, QU Jian-Hua, HE Lu-Ming. High-quality and thin reservoir of tight conglomerate prediction in Maxi area of Junggar Basin[J]. Geophysical and Geochemical Exploration, 2015,39(5): 891-896.
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准噶尔盆地玛西地区致密砂砾岩优质薄储层预测

程志国, 胡婷婷, 瞿建华, 贺陆明

中国石油新疆油田公司勘探开发研究院,新疆乌鲁木齐 830013

作者简介: 程志国(1978-),男,高级工程师,硕士,新疆油田地球物理研究所副总工程师,现从事石油地震勘探工作。E-mail:chengzg@petrochina.com.cn

收稿日期: 2014-12-30

摘要

准噶尔盆地玛湖西斜坡区三叠系百口泉组储层为扇三角洲致密砂砾岩,具有低孔、低渗、储层薄的特征,水下中等孔隙度的灰绿色砂砾岩为优质储层。由于地震资料主频低(25~30 Hz),储层薄(10 m左右),而且优质储层与致密层阻抗叠置,目前常用的叠后波阻抗反演、叠前同时反演等方法都满足不了该地区优质薄储层预测的要求。笔者基于取芯、测井、试油等资料开展岩石物理分析,利用纵波阻抗和纵横波速度比建立岩石物理图版,确定该区的优质储层参数特征。在此基础上,开展叠前地质统计学反演,综合叠前同时反演与地质统计学反演技术的优点,实现砂砾岩优质薄储层的预测。反演结果表明,叠前地质统计学反演结果可以明显提高储层纵向预测的分辨率,较好地解决该地区致密砂砾岩优质薄储层预测的问题,为该区下步勘探开发提供依据。

关键词: 准噶尔盆地; 玛湖西斜坡; 致密砂砾岩; 优质薄储层; 叠前地质统计学反演

中图分类号:P631.4 文献标志码:A 文章编号:1000-8918(2015)05-0891-06 doi: 10.11720/wtyht.2015.5.03

High-quality and thin reservoir of tight conglomerate prediction in Maxi area of Junggar Basin

CHENG Zhi-Guo, HU Ting-Ting, QU Jian-Hua, HE Lu-Ming

Exploration and Production Research Academy,Xinjiang Oilfield Company,PetroChina,Urumqi 830013,China

Abstract

The reservoir of Triassic Baikouquan Formation on Mahu slope in Junggar Basin is characterized by low porosity,low permeability,and thin tight conglomerate,with only the subaqueous grayish green conglomerate with medium porosity being the high-quality reservoir. Because central frequency of seismic data is low (25~30 Hz),the thickness of the thin layer is about 10 m,and the impedances of high-quality reservoir and tight layers are overlapped in these reservoirs,the commonly used post-stack impedance inversion and pre-stack simultaneous inversion are not very effective in prediction of high-quality and thin reservoirs.In this paper,based on core,logging and test data,the authors carried out the petrophysical analysis and established the petrophysical chart by using P-impedance and v_p/ v_s,and then identified the parameter of the effective reservoir of this area.Finally,the authors conducted the pre-stack geo-statistic inversion that combines the advantages of the simultaneous inversion and geo-statistics inversion,and predicted the high-quality and thin conglomerate reservoir.The result of inversion indicates that the pre-stack geo-statistics inversion can effectively identify the high-quality and thin conglomerate reservoir and provide reliable basis for further exploration and development.

Keyword: Junggar basin; Mahu west slope; tight conglomerate; high-quality and thin reservoir; pre-stack geo-statistics inversion

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玛湖西斜坡区北接乌夏断裂带, 南邻玛湖凹陷, 构造格局形成于白垩纪早期, 构造较为简单, 基本表现为向东南倾斜的平缓单斜, 局部发育低幅度平台、背斜或鼻状构造。玛湖凹陷是准噶尔盆地主力生油凹陷之一, 具有充足的油气源供应, 成藏条件十分有利, 油气资源丰富, 在近几年的百口泉组砂砾岩岩性油气藏勘探中获得了亿吨级的储量规模, 取得了重大进展。三叠系百口泉组主要发育扇三角洲平原亚相和前缘亚相水下分流河道砂为主的储集体。储层岩性主要为砂砾岩, 具有低孔、低渗、储层薄的特征, 其中水下分选较好的具有中等孔隙度的灰绿色砂砾岩为优质储层。由于储层薄, 优质储层与致密层纵波阻抗叠置, 目前常用的叠后波阻抗反演、叠前同时反演等方法都满足不了该地区优质薄储层预测的要求。叠前地质统计学反演综合叠前同时反演与地质统计学反演技术的优点^{[1, 2, 3, 4, 5]}, 能得到高分辨率的叠前弹性参数, 不仅可以提高储层纵向预测的分辨率, 还可以解决优质储层与致密层阻抗叠置情况下的优质储层识别问题。

1 研究区概况和储层基本特征

玛湖西斜坡地区三叠系百口泉组主要为扇三角洲沉积环境, 沉积相变化快, 北部为扇三角洲平原亚相, 向南逐渐过渡为扇三角洲前缘亚相。图1为工区百口泉组百二段沉积相。本区岩性结构复杂, 横向变化快; 百口泉组储层含油气性主要受物性控制, 而物性主要受相带控制, 扇三角前缘亚相物性明显好于扇三角平原亚相, 前缘相水下分选较好的具有中等孔隙度的灰绿色砂砾岩、砂岩为优质储层。

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	图1 百口泉组二段沉积相

图2为B75— AH2— AH1连井地层对比, 从图中可以看出, 从工区北部B75井扇三角洲平原相杂色致密砂砾岩地层过渡到中部的AH2井和南部的AH1井扇三角洲前缘相灰色、灰绿色砂砾岩储层, 其中AH2井百二段(T₁b₂)发育两套灰绿色储层, 薄的10 m, 厚的16 m, AH1井百一段(T₁b₁)为薄互层砂砾岩、砂岩, 发育两套油层, 薄的4.1 m, 厚的13.2 m。

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	图2 B75— AH2— AH1连井地层对比

开展岩石物理分析, 首先利用岩屑录井和取芯等资料对所有钻井进行岩性划分, 共划分为三种岩性:泥岩、杂色致密砂砾岩和灰色、灰绿色优质储层。然后对百口泉组储层进行分岩性弹性参数统计分析, 确定敏感弹性参数, 建立岩石物理量板^[6]。从纵波阻抗和纵横波速度比(v_p/v_s)岩石物理量板(图3)上看, 泥岩阻抗范围在8 000~11 500之间, 砂砾岩阻抗范围在9 500~12 500之间, 砂砾岩阻抗总体上大于泥岩, 但是优质砂砾岩储层与致密层阻抗叠置非常严重。对于v_p/v_s属性, 优质砂砾岩储层分布范围在1.6~1.76之间, 致密砂砾岩分布范围在1.76~1.83之间, 而泥岩大于1.83, 因此, 通过纵横波速度比能够很好地识别有效储层和致密层。

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	图3 波阻抗与v_p/v_s交会

2 预测方法及流程

针对砂砾岩优质储层的特点, 通过岩石物理分析可以看出, 单一运用波阻抗很难区分优质储层和致密层, 即常规叠后反演技术对于百口泉组储层预测难以奏效, 因此, 必须开展叠前反演, 利用弹性参数v_p/v_s才能有效地区分优质储层与致密层。同时由于地震资料分辨率(主频25~30 Hz)的限制, 难以对10 m以下的优质储层开展预测, 而叠前地质统计学方法能够将叠前反演技术和随机反演技术相结合, 有效地综合地质、测井、地震资料, 将地震横向分辨率和测井纵向分辨率有机结合, 不仅能够解决储层与围岩阻抗叠置情况下有效储层的识别问题, 而且能够提高纵向分辨率, 解决薄层识别与储层描述问题。因此针对玛西地区致密砂砾岩优质薄储层, 笔者采用叠前地质统计学反演的方法开展高精度储层预测研究。

叠前地质统计学反演采用严格的马尔科夫链蒙特卡洛算法(markov chain monte carlo, MCMC)^{[7, 8, 9]}, 将叠前同时反演和地质统计学反演^{[10, 11, 12, 13]}相结合, 成为全新的同时随机反演技术。叠前地质统计学反演以地质统计学为基础, 主要包括随机模拟过程和反演过程。通过对地震和测井数据进行分析, 得到概率分布函数和变差函数, 其中概率分布函数描述的是特定岩性对应的岩石物理参数分布的可能性, 而变差函数描述的是横向和纵向地质特征的结构和特征尺度。然后从井点出发, 井间变化用地震约束, 根据马尔科夫链蒙特卡洛算法随机模拟, 得到多个可选的、等概率的岩性模型; 再次, 通过反复迭代计算, 保证最终的岩性模拟所对应的合成地震记录必须和实际的各个部分叠加地震数据有很高的相似性; 最后应用多次等概率模拟, 得到多个与井资料、地质信息、地震资料相吻合的模拟结果, 基于多个模拟实现可以求取最大似然岩性体、属性体。通过叠前地质统计学反演得到高分辨率的反演结果, 是目前解决横向非均质性很强的岩性油气藏描述问题, 以及解决优质储层与致密层阻抗叠置条件下优质储层预测的最佳方案。

笔者应用叠前地质统计学方法解决玛西地区致密砂砾岩优质薄储层预测的流程如图4所示。第一步, 分析录井、试油、测井资料, 对参与反演的测井曲线进行环境校正和标准化, 然后进行岩石物理建模、横波预测, 选择敏感弹性参数, 建立岩石物理模板; 第二步, 利用叠后地震资料进行层位精细标定和构造解释, 利用叠前道集处理得到分角度叠加剖面, 分别进行标定和提取子波; 第三步建立初始地质模型, 进行常规地震波阻抗反演和叠前同时反演; 第四步, 根据测井资料、地震资料和反演波阻抗属性进行空间变差分析和概率密度统计分析, 通过无井、抽井等上百次的高斯配置协模拟实验, 与确定性反演成果比对, 并结合地质认识, 综合优化、确定岩性比例、纵向变差函数和横向变差函数等统计学参数; 第五步, 根据优化确定的反演参数开展叠前地质统计学反演, 得到多个与井资料吻合且在空间上符合确定性反演结果规律的岩性实现, 最终通过多次地质统计学的岩性概率实现来综合计算得到最终的极大似然属性体、岩性体。最后对反演结果进行精细解释, 确定优质储层分布范围。

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	图4 致密砂砾岩优质薄储层预测流程

3 结果分析

3.1 叠前同时反演

叠前同时反演是在测井资料的约束下对不同角度或者偏移距部分叠加的多个地震数据进行同时反演, 得到纵波阻抗、横波阻抗、纵横波速度比等多个数据体^{[14, 15, 16]}。

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	图5 过B75— AH2— AH1井叠后阻抗(上)与叠前v_p/v_s反演剖面(下)

通过储层弹性参数分析, 纵横波速度比能够区分致密砂砾岩与优质储层, 致密砂砾岩位于1.76~1.83之间, 优质储层纵横波速度比小于1.76。通过连井的反演剖面(图5)可以看出, 从工区北部B75井扇三角洲平原相杂色致密砂砾岩过渡到工区中部AH2井扇三角洲前缘相砂砾岩, 再到工区南部AH1井扇三角洲前缘相水下灰色、灰绿色砂砾岩储层, 叠前同时反演得到的纵横波速度相比叠后阻抗反演能够更好地区分B75井的致密砂砾岩和AH1井的优质储层, 从而实现优质储层的预测。但由于AH1井的灰色砂砾岩优质储层薄, 受地震分辨率的限制, 未能较好地预测出百一段的两套优质储层。因此, 需要进一步开展叠前地质统计学反演, 实现优质薄储层的预测。

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	图6 过AH1井叠前同时反演v_p/v_s剖面

3.2 叠前地质统计学反演

叠前地质统计学反演主要参数为概率密度函数和差函数。对工区内9口测井曲线质量较好的井进行分析, 纵波阻抗、密度和纵横波速度比的概率密度函数分布服从高斯分布。纵向变差函数的求取来自于测井曲线的拟合, 通过多高斯型和指数型拟合的比较, 本地区指数型拟合较好, 纵向变程为6 m。横向变程的拟合来自于确定性反演提取的储层平面分布特征, 通过拟合, 横向变程为1 800 m。

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	图7 过AH1井叠前地质统计反演v_p/v_s剖面

根据叠前地质统计学反演得到多个与井吻合且在空间上符合确定性反演结果的岩性, 最终通过多次地质统计学的岩性概率实现来综合计算得到最终的极大似然岩性体。比较过AH1井叠前同时反演v_p/v_s(图6)与叠前地质统计学反演(图7)可以看出, 叠前地质统计学反演得到的v_p/v_s保留了叠前同时反演结果的优势, 能够很好地区分优质储层与致密层, 而且叠前地质统计学反演结果分辨率有了明显提高。

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	图8 AH2— AH1井优质储层概率剖面

分析过AH2— AH1井最大似然岩性体剖面(图8)和优质储层概率剖面(图9)后发现, 优质储层、致密层和泥岩边界特征清晰, 纵向上变化关系清楚、横向叠置特征明显。同时针对百口泉组, 能够清楚地识别AH2井发育的两套10 m和16 m的优质储层, 以及AH1井发育的两套13 m和4 m的薄优质储层。从反演的精度上来看, 叠前地质统计学反演至少可以分辨6 m以上的储层, 明显较常规的叠前反演分辨率高。

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	图9 AH2— AH1井最大似然概率体剖面

在对工区反演结果进行精细解释后得到了百口泉组优质储层的平面分布, 主要分布在AH1— MA18井区, 顺物源方向, 沿南北向展开, 东西方向变薄。后续又在MA18和AH1周围部署了多口评价井, 获得高产工业油流, 落实了玛西地区近亿吨级的控制储量规模。因此通过以叠前地质统计学反演方法为核心的致密砂砾岩优质薄储层预测研究, 提高了玛湖斜坡区三叠系百口泉组灰绿色砂砾岩优质薄储层的预测精度, 为井位部署提供依据, 见到明显效果。

4 结论

(1)玛湖斜坡区百口泉组砂砾岩储层薄、优质储层与致密层阻抗叠置, 常规储层预测手段难以解决该区优质薄储层预测的问题。

(2)叠前地质统计学反演能有效地综合地质、测井和地震资料, 实现测井纵向分辨率和地震横向分辨率的有机结合, 不仅能够解决薄储层预测问题, 还能很好地实现优质储层和致密层阻抗叠置情况下优质储层预测的问题。

(3)通过开展致密砂砾岩优质薄储层预测研究, 可以很好地预测玛西地区百口泉组优质储层的分布范围, 为下一步勘探开发提供了可靠的依据。

The authors have declared that no competing interests exist.

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[7]	赵林. 马尔科夫链蒙特卡洛模拟在储层反演中的应用[J]. 石油天然气学报, 2009, 31(2): 249-252. [本文引用:1]
[8]	何火华, 李少华, 杜家远, 等. 利用地质统计学反演进行薄砂体储层预测[J]. 物探与化探, 2011, 35(6): 804-808. [本文引用:1]
[9]	王香文, 刘红, 滕杉杉, 等. 地质统计学反演技术在薄储层预测中的应用[J]. 石油与天然气地质, 2012, 33(5): 730-755. [本文引用:1]
[10]	孙思敏, 彭仕宓. 地质统计学反演及其在吉林扶余油田储层预测中的应用[J]. 物探与化探, 2007, 31(1): 51-53. [本文引用:1]
[11]	韩瓣, 臧殿光, 李建华. 地质统计学反演在四川盆地 L 地区储层预测中的应用[J]. 物探化探计算技术, 2010, 32(3): 310-315. [本文引用:1]
[12]	边树涛, 狄帮让, 董艳蕾, 等. 地质统计反演在东濮凹陷白庙气田沙三段储层预测中的应用[J]. 石油地球物理勘探, 2010, 45(3): 398-405. [本文引用:1]
[13]	黄捍东, 罗群, 付艳, 等. 地震相控非线性随机反演与应用[J]. 石油地球物理勘探, 2007, 42(6): 694-698. [本文引用:1]
[14]	郎晓玲, 彭仕宓, 康洪全, 等. 叠前同时反演方法在流体识别中的应用[J]. 石油物探, 2010, 49(2): 164-169. [本文引用:1]
[15]	程志国, 谭佳, 宋永, 等. 阜东地区河道砂体AVO油气预测研究[J]. 新疆石油地质, 2013, 34(3): 338-342. [本文引用:1]
[16]	宗兆云, 印兴耀, 吴国忱. 基于叠前地震纵横波模量直接反演的流体检测方法[J]. 地球物理学报, 2012, 55(1): 284-292. [本文引用:1]

1994

0.0

... 叠前地质统计学反演综合叠前同时反演与地质统计学反演技术的优点^[1,2,3,4,5],能得到高分辨率的叠前弹性参数,不仅可以提高储层纵向预测的分辨率,还可以解决优质储层与致密层阻抗叠置情况下的优质储层识别问题 ...

1998

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1998

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2013

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姜岩, 徐立恒, 张秀丽, 等. 叠前地质统计学反演方法在长垣油田储层预测中的应用[J]. 地球物理学进展, 2013, 28(5): 2579-2586.

The stratum distribution and porosity, permeability and oil-gas bearing properties can be revealed by prestack geostatistical inversion method and can get more reservoir informations than post-stack, it is the direction of further development on inversion reservoir prediction. Taking reservoir of north Saertu oilfield for example, 3D Geological Objects for sand body distribution of study area are obtained by the quality control on the key technologies of rock physical model、prestack wavelet; lithologic body from the prestack geostatistical inversion method matches the underground geological object, thin reservoir、sand and mud interbed and isolated sand body can be depicted, but it's difficult to efficiently identify the flow of late stage development through elastic characters. The fine description of late-stage oilfield sand body can be provided by the study.

Exploration and Development Research Institute, Daqing Oilfield Company Limited, Daqing 163712, China

叠前地震反演方法相对于叠后反演方法得到的储层信息更多,能可靠地揭示地下储层的展布情况和孔、渗物性及含油气性,己经成为反演储层预测技术进一步发展的方向.文章以萨尔图油田北部区块为研究区,运用叠前地质统计学方法进行储层预测,根据其储层沉积特点和地质需求,对地质统计学反演的岩石物理模型、叠前子波等关键技术环节进行质控,最终得到研究区的砂体展布三维数据体;经平面抽井检验,叠前地质统计学反演方法得到的岩性体与地下客观地质体吻合,能够刻画出薄储层、砂泥岩互层及孤立砂体,但很难通过弹性参数对开发后期流体进行有效识别.该研究成果可为处于开发后期油田砂体精细刻画技术的研究提供借鉴.

2014

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余振, 王彦春, 何静, 等. 基于叠前AVA同步反演和地质统计学反演的高分辨率流体预测方法[J]. 石油地球物理勘探, 2014, 49(3): 551-560.

A high resolution approach for fluid prediction is proposed to accurately predict the fluid in thin layers. The approach carries out prestack AVA simultaneous inversion and the geostatistical inversion for water saturation with lithology masks in the same time. Then through crossing the results of them, the final high resolution result for fluid prediction is produced by selecting the part corresponding to the threshold values of the fluid in crossplots. It could precisely predict the fluid in thin layers. This approach is applied to three multilayer horizontal layered models with shale walls of different width and real data. The results show that prestack AVA simultaneous inversion has high resolution in the lateral direction and low resolution in the vertical direction. Geostatistical inversion with lithology masks has high resolution in the vertical direction and a certain resolution in the lateral direction, but the resolution in the lateral direction is not as good as that of prestack AVA simultaneous inversion. The joint use of these two methods for fluid prediction can obtain high resolution both in the vertical direction and in the lateral direction, and get good prediction results of thin layer fluid.

1. Halliburton Energy Services (China) Limited, Beijing 100020, China; 2. School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing 100083, China; 3. LandOcean Energy Services Co, Ltd, Beijing 100084, China; 4. Research Institute of Exploration and Developent, Qinghai Oil Company, CNPC, Dunhuang, Gansu 736200, China

针对薄层流体的精细预测问题，提出一种高分辨率流体预测方法。该方法在进行叠前AVA同步反演的基础上，同时对含水饱和度进行带岩性遮挡的地质统计学反演，然后将两者的结果进行交会，根据流体的门槛值在交会图中选择相应的部分，生成最终的高分辨率流体预测结果，可精细预测薄层流体。通过不同宽度泥岩墙的多层水平层状模型试算和实际资料的应用，结果表明：叠前AVA同步反演的横向分辨率高、纵向分辨率低；带岩性遮挡的地质统计学反演的纵向分辨率高且有一定的横向分辨率，但横向分辨率不如叠前AVA同步反演高；基于两者的高分辨率流体预测方法的纵、横向分辨率都高，对薄层流体的预测效果较好。

2012

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吕其彪, 孙作兴. 岩石物理模版在储层定量解释中的应用[J]. 地球物理学进展, 2012, 27(2): 610-618.

Rock physics refers to the volume of various minerals made up of the rocks and the relationships among these minerals. Generally, the relationships between minerals are relatively stable and principal. There are several famous rock physics models such as Xu-White model, Self-consistent model, Spherical model et al . Base on these rock physics models, we can forward many kinds of characteristics of the gas rock and pick out the most obvious parameters of gas rock to different gas rock with tight rock and nonereservior. At the same time, we can tell the parameter difference in accord with different gas saturation with the Gassmann equation liquid substitution.The rock physics chart uses well log interpretation values of specific minerals ,selects suitable rock physics model and forward the different reservoir physical parameters with different reservoir lithology combinations, different reservoir porosity and different water saturation, then we can get a series of parameters and different seismic synthetic response characteristics of the reservoir, we can quantitatively establish the relationship between seismic elastic parameters and reservoir geophysical parameter as well. As a result, we predict the advantageous reservoir in the map scale constrained by the rock physics chart and the well log parameters abnormity.In this paper, we set up the rock physics interpretation chart according to the well log interpretation model, then we crossplot the compress wave impedance with the Vp/Vs to different the gas sand with tight sand and nonreservior in great scale. That is the advantage parameters to detect the good reservoir. Base on the gather AVO amplitude information, we carry out the simultaneous pre-stack inversion, interpret the inversion result with the rock physics chart and achieve good prediction result. Compared with the conventional qualitative interpretation such as amplitude and phase attribute interpretation, the rock physics chart interpretation result is more convincing.

1. Deyang Branch Institute ,Exploration & Production Research Institute, Southwest Branch Co., SINOPEC, Deyang 618000,China; 2. Research Institute of Petroleum Exploration & Development,Petrochina,Beijing 100083,China

岩石物理模板采用测井解释的各类岩性矿物骨架点值,选取适合该地区的岩石物理模型,模拟在不同储层组合、不同孔隙及不同饱和度情况下,储层岩石物理参数变化引起的储层测井参数及地球物理响应特征的变化,定量地建立起储层参数同地球物理弹性参数间的解释关系模版.本文根据新场JS 4 2 气藏储层参数分析结果,尝试性地将岩石物理解释模板应用于储层定量解释中,对储层高产气区、含水区域进行定量解释,并预测了该气藏的气水界面,该预测结果与实钻井测试情况吻合,证实了该方法的科学性.

... 然后对百口泉组储层进行分岩性弹性参数统计分析,确定敏感弹性参数,建立岩石物理量板^[6] ...

2009

0.0

... 叠前地质统计学反演采用严格的马尔科夫链蒙特卡洛算法(markov chain monte carlo,MCMC)^[7,8,9],将叠前同时反演和地质统计学反演^{[10,11,12,13]}相结合,成为全新的同时随机反演技术 ...

2011

0.0

何火华, 李少华, 杜家远, 等. 利用地质统计学反演进行薄砂体储层预测[J]. 物探与化探, 2011, 35(6): 804-808.

The delta-front of a certain area is characterized by fast facies change, strong heterogeneity, and small thickness of a single sand body. As the earthquake-band of the conventional deterministic inversion is limited, the vertical resolution of the seismic inversion body is very low, and hence it is often difficult to identify the small sand body. The geostatistic inversion method based on stochastic modeling technique can effectively integrate geological, logging and seismic data, greatly improve the seismic vertical resolution, and more accurately describe the subtle changes in the reservoir, thus well identifying the thin sand. Geostatistic Inversion was used in delta-front of a target area to predict the thin sand layers. The impedance body derived from the high-resolution geostatistic inversion method was compared with the density body, which could effectively identify a thin layer of sand body in the horizontal distribution on the inversion profile. This method provides a basis for identifying favorable oil and gas traps.

1. MOE Key Laboratory of Oil & Gas Resources and Exploration Technique, Yangtze University, Jingzhou 434023,China; 2. The Zhiluo Oil Production Plant of Yanchang Oil Field Co., Ltd.,Yanan 727500,China; 3. The Shenzhen Branch Institute, CNOOC, Guangzhou 510240,China

某地区三角洲前缘砂体相变快,非均质性强,单砂体厚度小,常规的确定性反演由于受到地震频带限制,反演地震体的垂向分辨力低,往往难以识别。基于随机建模技术的地质统计学反演方法,能有效地综合地质、测井和三维地震数据,极大地提高了预测结果的垂向分辨率,能更加精确地描述储层细微的变化,可以更好地识别薄层砂体。利用地质统计学反演方法对某地区三角洲前缘目标层段的薄层砂体进行了预测,通过高分辨率的地质统计学反演波阻抗体和密度反演体剖面对比,可以有效识别出薄层砂体在反演剖面上横向展布。

2012

0.0

王香文, 刘红, 滕杉杉, 等. 地质统计学反演技术在薄储层预测中的应用[J]. 石油与天然气地质, 2012, 33(5): 730-755.

Taking M1 thin reservoir in H-N oilfield,Southern Ecuador,as an example,this paper documents the challenges and problems of thin reservoir prediction and presents relevant techniques and methods to tackle these problems.Based on analysis of geophysical characteristics of reservoirs and surrounding rocks,a geostatistical inversion technique is applied in this case to identify the thin(1-25 ft)reservoirs with rapid lateral changes and strong concealment.Sand distribution is refined through correlation between different data volume including seismic interpretation,CSSI(Constrained Sparse Spike Inversion)and geostatistical inversion,and is further checked by non-well,random-wells and newly drilled wells.The accuracy of thin reservoir prediction is greatly enhanced to a vertical resolution up to 5 ft.This technique is successfully applied in H-N oilfield and the new drilling data show that all the prediceted thin sand layers are encountered and the drilling coincidence rate is 82%.

1. Exploration and Production Research Institute, SINOPEC, Beijing 100083, China; 2. The First Oil Production Factory of Daqing Oilfield Company, PetroChina, Daqing, Heilongjiang 163001, China

以厄瓜多尔南部H-N油田M1层薄储层为例,阐述了研究区M1层储层预测难点和存在问题,提出针对性的储层预测方法技术。经过储层和围岩地球物理特征分析,论证了储层预测条件,确定了运用以地质统计学反演为核心的储层预测技术对该区进行储层预测研究,来解决该区储层薄(1~25 ft)、横向变化大、隐蔽性强的薄储层的识别;通过以地震、稀疏脉冲反演、地质统计学反演不同数据体间砂体进行对比分析,精细解释出该区砂体分布;经过无井、盲井和新钻井校验,实现了薄层的高精度预测,提高了预测精度(垂向分辨率达到5 ft)。该预测结果经过在H-N油田的实际应用和新钻井钻探证实,砂层钻遇率为100%,钻探符合率达82%,实现了该区新井产能的突破。

2007

0.0

孙思敏, 彭仕宓. 地质统计学反演及其在吉林扶余油田储层预测中的应用[J]. 物探与化探, 2007, 31(1): 51-53.

Geostatistical inversion (GI) combines the advantages of stochastic modeling and seismic inversion, integrates geological, logging and seismic data, and delineates the reservoir more preciously. Constrained sparse spike inversion is conducted to predict the general distribution of reservoirs before GI, and the results including wavelet and 3D acoustic impedance (AI) can be used later. The inversion uses both well-log and seismic data. The inter-well AI is created by stochastic simulation, and the subsequent work includes (1) simulating an AI at the interwell point, followed by computing reflectivity series, (2) convolving it with the wavelet selected to simulate a local trace, and (3) implementing iterations to make the simulated and seismic trace reach a desired fit. The results are of multi-equiprobable 3D AI volume realization, which can be used for uncertainty evaluation. The inversion integrates the high resolution of logging and lateral directions of the seismic data. The results fit the geostatistical features of the input data, and are constrained by structural and stratigraphic earth models.

China University of Petroleum, Beijing 102249, China

地质统计学反演方法将随机建模技术与常规地震反演相结合,有效地综合地质、测井和三维地震数据,可以更加精确地描述储层的变化.在执行地质统计学反演前,首先应用稀疏脉冲约束反演,了解储层的大致分布,以求取子波和水平变差函数.地质统计学反演从井点出发,井间以原始地震数据作为硬数据,通过随机模拟的产生井间波阻抗,然后将波阻抗转换成反射系数,并用确定性反演方法求得的子波褶积产生地震道,通过反复迭代直至合成地震道与原始地震数据达到一定程度的匹配,反演结果是多个等概率的波阻抗数据体实现.反演结果符合输入数据的地质统计学特征并受地质模型的约束,它综合了测井的垂向分辨率高和地震的横向分辨率高的优势,结果的多个实现用于不确定性评价.

2010

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2010

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边树涛, 狄帮让, 董艳蕾, 等. 地质统计反演在东濮凹陷白庙气田沙三段储层预测中的应用[J]. 石油地球物理勘探, 2010, 45(3): 398-405.

本文基于约束稀疏脉冲波阻抗反演进行地质统计反演，把标准化后的自然电位曲线作为输入参数，把稀疏脉冲反演得到的波阻抗数据体作为相关控制函数。首先，统计随机变量的直方图分布和变差函数，确定随机变量在不同方向上的变程；然后在每一地震道上，将随机提取的反射系数与求取的地震子波进行褶积，生成合成地震道，将合成地震道与原始地震道进行匹配，计算反演的剩余值，直到匹配程度满足精度要求为止；最后，选择合成地震记录最好的节点值作为反演结果，对下一个随机选取的节点进行反演，直到完成各个随机实现的全部反演，再对相关性大于90%的各个实现进行求均方根运算，并将获得的均方根数据体作为最终的反演结果。文中以白庙气田三维地震工区沙三段水下扇体为研究对象，在分析储层岩性、电性、物理特征的基础上，选取地震空变子波，建立低频模型，通过合理选取反演参数λ,把标准化后的自然电位曲线作为输入参数，利用约束稀疏脉冲反演和地质统计反演技术，得到的反演结果与实钻资料吻合率达到81.3%，取得了较好的效果。

2007

0.0

黄捍东, 罗群, 付艳, 等. 地震相控非线性随机反演与应用[J]. 石油地球物理勘探, 2007, 42(6): 694-698.

在地震相模型控制下，通过原始数据将各个单一反演问题转化为一个联合反演问题，可降低反演在描述参数几何形态时的单个反演问题的自由度，从本质上提高地球物理反演的效果。本文在计算过程中采用了非线性随机反演算法，能有效提高地震资料的分辨率，并充分考虑地质条件的随机特性，使反演结果更符合实际地质情况。在胜利、中原油田等地区的储层预测中，应用本文方法均取得了良好的效果，为岩性油气藏勘探提供了可靠基础数据。

2010

0.0

... 1 叠前同时反演叠前同时反演是在测井资料的约束下对不同角度或者偏移距部分叠加的多个地震数据进行同时反演,得到纵波阻抗、横波阻抗、纵横波速度比等多个数据体^[14,15,16] ...

2013

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2012

0.0

宗兆云, 印兴耀, 吴国忱. 基于叠前地震纵横波模量直接反演的流体检测方法[J]. 地球物理学报, 2012, 55(1): 284-292.

Fluid factor, which can be derived from pre-stack seismic inversion efficiently, is an important method for fluid indication. Firstly, we start from the reconstruction of fluid factor and gain the direct relationship between fluid factor and compressional modulus, shear modulus based on rock physics model for multi-porosity media; in this way we can gain fluid factor directly without knowing the density information which could not be inverted correctly. Then, through derivation of a new elastic impedance equation from Zeoppritz approximation, we study the compressional modulus and shear modulus direct inversion method based on new elastic impedance equation. Finally, the model and practical test shows that this method is more stable and reasonable, which leads to less error brought by accumulating calculation with common elastic impedance inversion method, and the method to gain fluid factor is efficient.

[Zong Zhao-Yun; Yin Xing-Yao; Wu Guo-Chen] China Univ Petr E China, Sch Geosci, Qingdao 266555, Peoples R China.

流体因子是储层流体识别的重要方法,而叠前地震反演是获得流体因子的有效途径之一.本文从流体因子的构建出发,基于多孔弹性介质岩石物理模型,建立了流体因子与纵横波模量之间的直接关系,避免了流体因子计算所需的密度参数无法准确求取的问题,通过推导基于纵横波模量的Zeoppritz近似方程及弹性阻抗方程,探讨了基于弹性阻抗的纵横波模量直接反演方法,模型与实际应用表明,基于弹性阻抗的纵横波模量直接反演方法合理、可靠,减少了常规方法间接计算纵横波模量带来的累积误差,基于纵横波模量的流体因子计算方法有较好的实际应用效果.