岩性油气藏 ›› 2026, Vol. 38 ›› Issue (5): 83–93.doi: 10.12108/yxyqc.20260508

• 地质勘探 • 上一篇    下一篇

川西南三叠系嘉陵江组四段白云岩薄互层储层地震识别及勘探有利区

李素华1,2(), 肖斌3   

  1. 1 中国石化西南油气分公司 勘探开发研究院， 成都 610041
    2 中国石化油气藏地球物理重点实验室， 南京 211103
    3 中国石油吉林油田公司 乾安采油厂， 吉林 松原 131400
  • 收稿日期:2026-06-28 修回日期:2026-07-12 出版日期:2026-09-01 发布日期:2026-09-04
  • 第一作者:李素华（1980—），女，硕士，副研究员，主要从事海相油气勘探和目标评价工作。地址：（610041）四川省成都市高新区吉泰路688号中石化科研办公基地。Email:lish1121@163.com。
  • 基金资助:
    中国石化科技攻关项目“川南海相上组合天然气主控因素及潜力评价”(P24007)

Seismic identification and favorable exploration zones of thin interbedded dolomite reservoirs in the fourth member of Triassic Jialingjiang Formation, southwestern Sichuan Basin

LI Suhua1,2(), XIAO Bin3   

  1. 1 Research Institute of Exploration and Development, South-west Oil & Gas Branch, Sinopec, Chengdu 610041, China
    2 Key Laboratory of Oil & Gas Reservoir Geophysics, Sinopec, Nanjing 211103, China
    3 Qian’an Oil Production Plant, PetroChina Jilin Oilfield Company, Songyuan 131400, Jilin, China
  • Received:2026-06-28 Revised:2026-07-12 Online:2026-09-01 Published:2026-09-04

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摘要：

为解决川西南井研地区三叠系嘉陵江组四段（嘉四段）白云岩薄储层识别难点，提出了一套薄储层地震识别方法，明确了嘉四段白云岩储层和膏岩非储层的分布特征；综合构造位置、储层厚度、断裂演化及油气成藏配置关系，对勘探有利区进行了预测。研究结果表明：①该方法通过井-震标定确定白云岩储层和膏岩发育特征；基于正演模拟确定识别薄储层的最佳主频为60 Hz；对地震资料进行保幅去噪，并借助压缩小波变换谐波分解、补偿高频分量拓宽频带，提高分辨率；融合分频地震信息，开展高分辨率非线性神经网络孔隙度反演，提高薄储层预测精度。②经保幅去噪、提高分辨率处理后的地震资料与60 Hz雷克子波标定结果匹配良好，能够清晰识别嘉四段各亚段界面，可进行精细层位追踪；高分辨率孔隙度反演结果与测井孔隙度曲线吻合度高，验证井绝对误差为0.02%，相对误差为0.20%。③研究区优质厚层（16~22 m）白云岩储层主要发育在嘉四下亚段，平面上主要分布于工区南部；嘉四中、上亚段膏岩、云质膏岩等非储层厚度为50~80 m可作为有效盖层。④研究区经历多期构造运动，北西—南东向和北东—南西向2组断层多数已断至嘉陵江组，断裂演化与寒武系、二叠系烃源岩生排烃时期匹配；工区南部构造位置高、白云岩储层厚度大、烃源断裂和裂缝发育，且气藏保存条件较好，成藏条件最优，为勘探有利区。

关键词: 薄层白云岩储层, 保幅去噪, 高分辨率, 非线性神经网络反演, 勘探有利区, 嘉陵江组四段, 三叠系, 井研地区, 四川盆地

Abstract:

To address the identification difficulty of thin dolomite reservoirs of the fourth member of Triassic Jia-lingjiang Formation in Jingyan area of southwestern Sichuan Basin, a set of seismic identification methods for thin reservoirs was proposed to clarify the distribution characteristics of dolomite reservoirs and gypsum non-reservoirs in the fourth member of Jialingjiang Formation. Based on the structural location, reservoir thickness, fault evolution, and hydrocarbon accumulation configuration relationship, favorable exploration areas were predicted. The results show that: （1） The proposed method identifies the development characteristics of dolomite reservoirs and gypsum rocks through well-seismic calibration. Based on forward modeling, the optimal dominant frequency for identifying thin reservoirs is determined to be 60 Hz. The seismic data is processed by amplitude-preserved denoising. With the help of compressed wavelet transform harmonic decomposition and compensating high-frequency components, the bandwidth is broadened to improve the resolution. Frequency-division seismic information is integrated to carry out high resolution nonlinear neural network porosity inversion, so as to improve the prediction accuracy of thin reservoirs. （2） After amplitude-preserved denoising and improving resolution, the seismic data matches well with the 60 Hz Ricker wavelet calibration results, allowing clear identification of the interfaces of each submember in the fourth member of Jialingjiang Formation and enabling detailed stratigraphic tracking. The high resolution porosity inversion results match well with logging porosity curves, with an absolute error of 0.02% and a relative error of 0.20% in the verification well. （3） The high-quality thick-layer (16-22 m) dolomite reservoirs in the study area are mainly developed in the lower submember of the fourth member of Jia-lingjiang Formation, and are mainly distributed in the south part of the study area on the plane. The non-reservoir layers such as gypsum and dolomite gypsum in the middle and upper submember of the fourth member of Jia-lingjiang Formation, with thickness of 50-80 m, can serve as effective cap rocks. （4） The study area has experienced multi-stage tectonic movements, with two sets of faults trending NW-SE and NE-SW mostly extending into Jialingjiang Formation. The fault evolution matches the periods when Cambrian and Permian source rocks generated and expelled hydrocarbons. The south part of the study area has high structural positions, thick dolomite reservoirs, developed hydrocarbon-source faults and fractures, well-preserved gas reservoirs condition, and optimal hydrocarbon accumulation conditions, making it the favorable exploration area.

Key words: thin dolomite reservoirs, amplitude-preserved denoising, high resolution, nonlinear neural network inversion, favorable exploration areas, the fourth member of Jialingjiang Formation, Triassic, Jingyan area, Sichuan Basin

中图分类号: 

  • TE122.2

图1

川西南井研地区三叠系嘉陵江组区域构造、沉积特征（a）及岩性地层综合柱状图(b)"

图2

川西南A井三叠系嘉陵江组四段常规地震数据合成记录标定"

图3

川西南A井三叠系嘉陵江组四段常规地震数据反射特征"

图4

川西南井研地区三叠系嘉陵江组正演模型及不同频率雷克子波正演模拟结果"

图5

川西南井研地区三叠系嘉陵江组高分辨率地震数据处理结果"

图6

川西南井研地区三叠系嘉陵江组四段保幅去噪、提高分辨率数据合成记录标定结果对比"

图7

川西南井研地区三叠系嘉陵江组四段高分辨率反演结果"

图8

川西南井研地区三叠系嘉陵江组四段白云岩及膏岩预测分布图"

图9

川西南井研地区三叠系嘉陵江组断裂演化及成藏配置关系（剖面位置见图1a）"

图10

川西南井研地区三叠系嘉陵江组四段断裂裂缝(a)、勘探目标有利区(b)分布图"

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