基于波形指示模拟的致密砂岩储层预测

杜佳; 刘彦成; 白洁玢; 张迎春; 林利明; 师素珍

doi:10.19509/j.cnki.dzkq.2022.0155

基于波形指示模拟的致密砂岩储层预测

doi: 10.19509/j.cnki.dzkq.2022.0155

1.
中联煤层气有限责任公司, 北京 100015
2a.
中国矿业大学(北京)地球科学与测绘工程学院，北京 100083
2b.
中国矿业大学(北京)煤炭资源与安全开采国家重点实验室，北京 100083

基金项目:

中央高校基本科研业务费专项资金 2022JCCXMT01

煤炭资源与安全国家重点实验室开放基金项目 SKLCRSM19ZZ02

煤炭资源与安全开采国家重点实验室—北京高等学校卓越青年科学家计划项目2020年联合基金项目 BJJWZYJH01201911413037

中海石油(中国)有限公司重大科技专项“中联公司上产60亿方关键技术研究” CNOOC-KJ 135 ZDXM 40

详细信息

作者简介:
杜佳(1983—)，女，工程师，主要从事非常规天然气勘探开发研究工作。E-mail：dujia3@cnooc.com.cn

通讯作者:
师素珍(1983—)，女，副教授，主要从事地震勘探研究工作。E-mail: ssz@cumbt.edu.cn

中图分类号: P631.4
计量
- 文章访问数: 1048
- PDF下载量: 88
- 被引次数: 0
出版历程
- 收稿日期: 2022-03-07
- 网络出版日期: 2022-11-10

Prediction of tight sandstone reservoirs based on waveform indication simulation

1.
China United Coalbed Methane Corporation Ltd., Beijing 100015, China
2a.
School of Geoscience and Surveying Engineering, China University of Mining and Technology(Beijing), Beijing 100083, China
2b.
State Key Laboratory for Coal Resources and Safety Mining, China University of Mining and Technology(Beijing), Beijing 100083, China

摘要

摘要:
随着勘探开发的不断深入，地质目标逐渐由常规储层转向非常规储层。鄂尔多斯盆地东北缘砂岩储层纵向叠置、厚度薄、横向变化快，传统的反演技术无法满足薄储层精细预测的要求。波形指示模拟基于波形相控的思路，利用地震波形代替变差函数分析储层的分布特征，可以实现非阻抗参数模拟，是一种高精度反演技术。综合地质、地震和测井资料，基于自然伽马曲线，对鄂尔多斯盆地东缘MG区块进行了波形指示模拟，刻画出目的层砂岩储层的分布规律。结果表明，波形指示模拟具有较高的横、纵向分辨率，反演结果与钻井吻合度较好，与地震波形相关性强，能够反映储层的空间变化情况，且比较符合研究区的地质沉积规律。因此，波形指示模拟作为一种更高效的反演方法，为薄层、薄互储层的精细研究提供了有力支撑，有助于最大程度地实现对气藏资源的开发和利用。
- 波形指示模拟 /
- 相控 /
- 敏感曲线 /
- 储层预测 /
- 致密砂岩
Abstract:
With the deepening exploratory development, geological targets are gradually shifting from conventional reservoirs to unconventional ones. The sandstone reservoirs in the northeast margin of the Ordos Basin are stacked vertically and change quickly horizontally with thin thicknesses. Therefore, traditional inversion technology cannot satisfy the requirements of precise prediction of thin reservoirs. To solve this problem, this paper integrated geological, seismic and logging data based on the GR curve. A wave form simulation of the MG block in the eastern margin of Ordos Basin was conducted, and the distribution of sandstone reservoirs in the target bed was depicted. The results showed that the waveform indication simulation profiles had a high resolution both horizontally and vertically. They were also in line with the drilling well and strongly correlated with the seismic waveform, which could reflect the spatial variation in the reservoir and accord with the law of geological deposition in the study area. Therefore, as a more efficient inversion method, waveform indication simulation provided a strong support for the refined study of thin inter-bedded reservoirs and helped to maximize the development and utilization of gas resources.
- waveform indication simulation /
- waveform facies-control /
- sensitive curve /
- reservoir prediction /
- tight sandstone

HTML全文

图 1 波形特征分析示意图

Figure 1. Schematic diagram of waveform character analysis

下载: 全尺寸图片幻灯片

图 2 波形指示反演频率成分分析

Figure 2. Frequency component analysis of waveform indication inversion

下载: 全尺寸图片幻灯片

图 3 波形指示反演流程图

Figure 3. Flow chart of waveform indication inversion

下载: 全尺寸图片幻灯片

图 4 研究区位置图

Figure 4. Location map of the study area

下载: 全尺寸图片幻灯片

图 5 M2井地球物理响应特征

Figure 5. Geophysical characteristics of Well M2

下载: 全尺寸图片幻灯片

图 6 波阻抗曲线直方图

Figure 6. Histogram of wave impedance curve

下载: 全尺寸图片幻灯片

图 7 自然伽马曲线直方图

Figure 7. Histogram of the gamma ray curve

下载: 全尺寸图片幻灯片

图 8 波形指示模拟剖面

Figure 8. Profile of waveform indication simulation

下载: 全尺寸图片幻灯片

图 9 波形指示模拟叠合地震波形充填剖面

Figure 9. Profile of waveform indication simulating superimposed seismic waveform filling profile

下载: 全尺寸图片幻灯片

图 10 太1段(a)、太2段(b)反演平面图

Figure 10. Inversion slice of the first (a) and second (b) Member of Taiyuan Formation

下载: 全尺寸图片幻灯片

图 11 砂岩厚度统计图

Figure 11. Statistical map of sandstone thickness

下载: 全尺寸图片幻灯片

表 1 地震波形指示反演和模拟的区别

Table 1. Difference between inversion and simulation of seismic waveform indication

	波形指示反演	波形指示模拟
输入曲线	波阻抗曲线	敏感曲线
地震数据作用	波形指示储层结构、提供中频段相对阻抗	波形指示储层结构
输出结果	波阻抗体	敏感曲线数据体
适用性	波阻抗曲线可以区分砂泥岩	波阻抗无法区分砂泥岩，敏感曲线能够区分砂泥岩
主要用途	反映沉积特征、砂岩分布	预测储层敏感参数分布

下载: 导出CSV

表 2 太原组砂岩预测符合情况

Table 2. Sandstone prediction consistency of the Taiyuan Formation

井名	太1段符合情况	太2段符合情况
M1	√	√
M2	√	×
M3	×	√
M4	√	×
M5	√	√
M6	√	√
M7	√	√
M8	×	√
M9	√	√
M10	√	√
M11	×	√
M12	√	√
M13	√	√
M14	×	√
M15	√	×
M16	√	√
M17	×	√
M18	√	√

下载: 导出CSV

参考文献(28)

[1]	沈洪涛, 郭乃川, 秦童, 等. 地质统计学反演技术在超薄储层预测中的应用[J]. 地球物理学进展, 2017, 32(1): 248-253. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201701035.htm Shen H T, Guo N C, Qin T, et al. Application of geostatistical inversion for super thin reservoir prediction[J]. Progress in Geophysics, 2017, 32(1): 248-253(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201701035.htm
[2]	Helgesen J, Magnus I, Prosser S, et al. Comparison of constrained sparse spike and stochastic inversion for porosity prediction at Kristin field[J]. The Leading Edge, 2000, 19(4): 400-407. doi: 10.1190/1.1438620
[3]	杨亚华, 高刚, 魏红梅, 等. 叠前同时反演在灰质发育区识别储层及流体的应用研究[J]. 地球物理学进展, 2017, 32(1): 332-338. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201701047.htm Yang Y H, Gao G, Wei H M, et al. Application of pre-stack simultaneous inversion in reservoir and fluid identification of the calcareous development zone[J]. Progress in Geophysics, 2017, 32(1): 332-338(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201701047.htm
[4]	Du X, Li G F, Zhang M, et al. Multichannel band-controlled deconvolution based on a data-driven structural regularization[J]. Geophysics, 2018, 83(5): 401-411. doi: 10.1190/geo2017-0516.1
[5]	Velis D R. Stochastic sparse-spike deconvolution[J]. Geophysics, 2008, 73(1): 1-9.
[6]	Tarantola A. A strategy for nonlinear elastic inversion of seismic reflection data[J]. Geophysics, 1986, 51(10): 1893-1903. doi: 10.1190/1.1442046
[7]	Zong Z, Yin X, Wu G. Elastic impedance parmneterization and inversion with Young's modulus and Poisson's ratio[J]. Geophysics, 2013, 78(6): 35-42. doi: 10.1190/geo2012-0529.1
[8]	Fu J H, Wei X S, Luo S S, et al. Discovery and geological knowledge of the large deep coal-formed Qingyang Gas Field, Ordos Basin, NW China[J]. Petroleum Exploration and Development, 2019, 46(6): 1111-1126. doi: 10.1016/S1876-3804(19)60267-3
[9]	Francis A. Limitations of deterministic and advantages of stochastic seismic inversion[J]. CSEG Recorder, 2005, 30(2): 5-11.
[10]	赵继龙, 王俊鹏, 张先龙, 等. 基于地震多属性融合与地质统计学反演的薄层砂岩预测[J]. 地质科技情报, 2014, 33(5): 93-99. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201405013.htm Zhao J L, Wang J P, Zhang X L, et al. Thin sandstone prediction based on multi-seismic attribute information fusion and geostatistical inversion[J]. Geological Science and Technology Information, 2014, 33(5): 93-99(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201405013.htm
[11]	曲志鹏, 王芳芳, 张云银, 等. 基于关联规则与随机森林的地震多属性砂体厚度预测[J]. 地质科技通报, 2021, 40(3): 211-218. doi: 10.19509/j.cnki.dzkq.2021.0314 Qu Z P, Wang F F, Zhang Y Y, et al. Thickness prediction of seismic multi-attributes sand based on association rules and random forests[J]. Bulletin of Geological Science and Technology, 2021, 40(3): 211-218(in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2021.0314
[12]	印兴耀, 崔维, 宗兆云, 等. 基于弹性阻抗的储层物性参数预测方法[J]. 地球物理学报, 2014, 57(12): 4132-4140. doi: 10.6038/cjg20141224 Yin X Y, Cui W, Zong Z Y, et al. Petrophysical property inversion of reservoirs based on elastic imped[J]. Chinese Journal of Geophysics, 2014, 57(12): 4132-4140(in Chinese with English abstract). doi: 10.6038/cjg20141224
[13]	姚逢昌, 甘利灯. 地震反演的应用与限制[J]. 石油勘探与开发, 2000, 27(2): 53-56. doi: 10.3321/j.issn:1000-0747.2000.02.014 Yao F C, Gan L D. Application and restriction of seismic inversion[J]. Petroleum Exploration and Development, 2000, 27(2): 53-56(in Chinese with English abstract). doi: 10.3321/j.issn:1000-0747.2000.02.014
[14]	撒利明, 杨午阳, 姚逢昌, 等. 地震反演技术回顾与展望[J]. 石油地球物理勘探, 2015, 50(1): 184-202. https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ201501034.htm Sa L M, Yang W Y, Yao F C, et al. Past, present, and future of geophysical inversion[J]. Oil Geophysical Prospecting, 2015, 50(1): 184-202(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ201501034.htm
[15]	Ma M, Wang S X, Yuan S Y, et al. Multichannel spatially correlated reflectivity inversion using block sparse Bayesian learning[J]. Geophysics, 2017, 82(4): 191-199.
[16]	谢春临, 李永义, 陈志德, 等. 波形指示模拟在致密油水平井钻探中的应用[J]. 石油地球物理勘探, 2021, 56(3): 564-573. https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ202103015.htm Xie C L, Li Y Y, Chen Z D, et al. Seismic motion simulation for horizontal well drilling in Fuyu reservoirs[J]. Oil Geophysical Prospecting, 2021, 56(3): 564-573(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ202103015.htm
[17]	胡玮, 齐鹏, 杨江峰. 波形指示反演在超深层致密砂岩薄储层中的应用[J]. 地球物理学进展, 2018, 33(2): 620-624. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201802022.htm Hu W, Qi P, Yang J F. Application of seismic motion inversion in identification of tight thin super deep reservoirs[J]. Progress in Geophysics, 2018, 33(2): 620-624(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201802022.htm
[18]	杨涛, 乐友喜, 吴勇. 波形指示反演在储层预测中的应用[J]. 地球物理学进展, 2018, 33(2): 769-776. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201802042.htm Yang T, Le Y X, Wu Y. Application of the waveform inversion in reservoir prediction[J]. Progress in Geophysics, 2018, 33(2): 769-776(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201802042.htm
[19]	Ahmad M N, Rowell P. Application of spectral decomposition and seismic attributes to understand the structure and distribution of sand reservoirs within Tertiary rift basins of the Gulf of Thailand[J]. The Leading Edge, 2012, 31(6): 630-634.
[20]	高君, 毕建军, 赵海山, 等. 地震波形指示反演薄储层预测技术及其应用[J]. 地球物理学进展, 2017, 32(1): 142-145. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201701019.htm Gao J, Bi J J, Zhao H S, et al. Seismic waveform inversion technology and application of thinner reservoir prediction[J]. Progress in Geophysics, 2017, 32(1): 142-145(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201701019.htm
[21]	González E F, Mukerji T, Mavko G. Seismic inversion combining rock physics and multiple-point geostatistics[J]. Geophysics, 2007, 73(1): 11-21.
[22]	Zhu H H, Zhang T S, Zhong D K, et al. Binary pore structure characteristics of tight sandstone reservoirs[J]. Petroleum Exploration and Development, 2019, 46(6): 1297-1306.
[23]	Xu F H, Xu G S, Liu Y, et al. Factors controlling the development of tight sandstone reservoirs in the Huagang Formation of the central inverted structural belt in Xihu Sag, East China Sea Basin[J]. Petroleum Exploration and Development, 2020, 47(1): 101-113.
[24]	杨文采, 于常青. 深层油气地球物理勘探基础研究[J]. 地球物理学进展, 2007, 22(4): 1238-1242. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ200704032.htm Yang W C, Yu C Q. On basic research problems in applied geophysics for deep oil and gas fields[J]. Progress in Geophysics, 2007, 22(4): 1238-1242(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ200704032.htm
[25]	Holditch S A. Tight gas sands[J]. Journal of Petroleum Technology, 2006, 58(6): 86-93.
[26]	周爽爽, 印兴耀, 裴松, 等. 地震波形约束的蒙特卡洛-马尔科夫链随机反演方法[J]. 石油地球物理勘探, 2021, 56(3): 543-554. https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ202103013.htm Zhou S S, Yin X Y, Pei S, et al. Monte Carlo-Markov Chain stochastic inversion constrained by seismic waveform[J]. Oil Geophysical Prospecting, 2021, 56(3): 543-554(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ202103013.htm
[27]	Tan Z, Wang W, Li W, et al. Controlling factors and physical property cutoffs of the tight reservoir in the Liuhe Basin[J]. Advances in Geo-Energy Research, 2017, 1(3): 190-202.
[28]	尹相东, 蒋恕, 吴鹏, 等. 致密砂岩酸性和碱性成岩环境特征及对储层物性的控制: 以鄂尔多斯盆地临兴和神府地区为例[J]. 地质科技通报, 2021, 40(1): 142-151. doi: 10.19509/j.cnki.dzkq.2021.0109 Yin X D, Jiang S, Wu P, et al. Features of the acid and alkaline diagenetic environment of tight sandstones and the control of the reservoir physical properties: A case study of the Linxing and Shenfu district, eastern Ordos Basin[J]. Bulletin of Geological Science and Technology, 2021, 40(1): 142-151(in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2021.0109