石油与天然气地质 ›› 2024, Vol. 45 ›› Issue (3): 801-815.doi: 10.11743/ogg20240316

• 油气地质 • 上一篇    下一篇

松辽盆地深层中-基性火山岩有利相带及储层“甜点”逐级识别

李宁1,2(), 李瑞磊2, 苗贺2, 曹开芳2, 田军2   

  1. 1.吉林大学 地球科学学院,吉林 长春 130061
    2.中国石化 东北油气分公司 勘探开发研究院,吉林 长春 130062
  • 收稿日期:2024-01-12 修回日期:2024-05-20 出版日期:2024-07-01 发布日期:2024-07-01
  • 第一作者简介:李宁(1985—),女,副研究员,油气勘探地震地质综合研究。E‑mail: 214260630@qq.com
  • 基金项目:
    中国石化集团公司科技部项目(P21104)

Stepwise identification of favorable facies belts and reservoir sweet spots of deep intermediate-basic volcanic rocks in the Songliao Basin

Ning LI1,2(), Ruilei LI2, He MIAO2, Kaifang CAO2, Jun TIAN2   

  1. 1.College of Earth Sciences,Jilin University,Changchun,Jilin 130061,China
    2.Exploration and Development Research Institute,Northeast Oil & Gas Branch,SINOPEC,Changchun,Jilin 130062,China
  • Received:2024-01-12 Revised:2024-05-20 Online:2024-07-01 Published:2024-07-01

摘要:

松辽盆地深层下白垩统火石岭组中-基性火山岩广泛发育,岩性-岩相复杂,储层横向非均质性强,储层“甜点”识别难,制约了油气勘探和开发。以查干花地区为例,研究了松辽盆地深层中-基性火山岩岩相及储层特征,提出了火山通道、有利岩相、有利岩性及储层甜点识别方法。研究表明:①火山岩岩相主要为3相6亚相,优质储层岩性主要为粗粒、细粒凝灰岩和凝灰质砂岩,在近-中源相带中火山爆发相储层最为发育,相带控制了有利岩性凝灰岩的分布区域,物性和含气性是火山岩“甜点”的主要控制因素。②通过分析每个喷发期次的裂缝密度,结合蚂蚁体与地震数据的叠合剖面,识别出了不同喷发期次的火山通道,以判断火山近源相带,再结合火山机构厚度和能量半衰时属性划分中源与远源相带的边界,实现储层“甜点”发育区的定性刻画。③为降低地震反演定量预测中-基性火山岩储层的多解性,优选出低波阻抗表征沉凝灰岩,低密度表征高核磁孔隙度储层,低拉梅常数表征气层,基于此,在叠前反演密度预测孔隙度数据体的基础上,逐级剔除干扰沉凝灰岩、低孔隙度层及非气层,得到较为可靠的火山岩储层“甜点”空间分布预测结果。经验证,预测结果符合有利相带分布规律,且与已钻井气层解释结论吻合。应用有利相带定性认识及逐级定量刻画“甜点”空间分布,部署井取得较好效果,该方法可在深层火山岩“甜点”分布地震预测中广泛推广。

关键词: 逐级识别, 火山通道, 有利相带, 储层“甜点”, 中-基性火山岩, 松辽盆地

Abstract:

Intermediate-basic volcanic rocks are extensively distributed in the deep Lower Cretaceous Huoshiling Formation of the Songliao Basin. However, their intricate lithologies and lithofacies, as well as the strong lateral heterogeneity of their reservoirs, complicate the prediction of reservoir sweet spots, restricting the exploration and exploitation of hydrocarbon resources. Focusing on the Chaganhua area, we investigate the lithofacies and reservoir characteristics of deep intermediate-basic volcanic rocks in the Songliao Basin and develop a methodology for identifying volcanic conduits, favorable lithofacies and lithologies, and reservoir sweet spots within the volcanic rocks. The key findings are as follows. (1) Three facies with six subfacies are primarily identified in the volcanic rocks. High-quality reservoirs predominantly comprise coarse- and fine-grained tuffs and tuffaceous sandstones. Reservoirs of the volcanic explosive facies are the most extensive in the proximal-middle facies belts. The distribution of tuffs with favorable lithologies is governed by the facies belts. Furthermore, the reservoir sweet spots of the volcanic rocks are primarily governed by their physical and gas-bearing properties. (2) For various volcanic eruptive phases, volcanic conduits are identified based on fracture density, along with the superimposed profiles of ant tracking and seismic data. This helps determine the proximal volcanic facies belts. Then, in combination with the thickness of volcanic edifices and the energy half-time attribute, the boundaries between middle-distance and distal volcanic facies belts are identified, facilitating the qualitative characterization of areas containing reservoir sweet spots. (3) To minimize the multiplicity of solutions in the quantitative prediction of intermediate-basic volcanic reservoirs using seismic data inversion, we preferentially employ low wave impedance, low density, and low Lame constant to characterize tuffs, reservoirs with high porosity as indicated by nuclear magnetic resonance (NMR), and gas layers, respectively. Accordingly, based on the porosity data volumes derived from pre-stack density inversion, we eliminate the interference from the sedimentary tuffs, low-porosity layers, and non-gas layers sequentially, obtaining reliable predictions of the spatial distribution of reservoir sweet spots. It is verified that the predicted results align with the distribution pattern of favorable facies belts and agree with interpretations of drilled gas layers. The qualitative identification and stepwise quantitative characterization of the spatial distribution of reservoir sweet spots based on favorable facies belts, have been successfully applied to well emplacement, yielding encouraging outcomes. Therefore, this methodology is highly applicable in the seismic prediction of sweet spot distribution in deep volcanic rocks.

Key words: stepwise identification, volcanic conduit, favorable facies belt, reservoir sweet spot, intermediate-basic volcanic rock, Songliao Basin

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