Petrophysical characteristics of deep intermediate-basic volcanic gas reservoir

ChengCheng LI, KeFei ZHANG, XiaoYi MA, Huan WANG, Jun BAI

Prog Geophy ›› 2025, Vol. 40 ›› Issue (2) : 580-591.

PDF(7670 KB)
Home Journals Progress in Geophysics
Progress in Geophysics

Abbreviation (ISO4): Prog Geophy      Editor in chief:

About  /  Aim & scope  /  Editorial board  /  Indexed  /  Contact  / 
PDF(7670 KB)
Prog Geophy ›› 2025, Vol. 40 ›› Issue (2) : 580-591. DOI: 10.6038/pg2025HH0567

Petrophysical characteristics of deep intermediate-basic volcanic gas reservoir

Author information +
History +

Abstract

In recent years, the exploration of deep volcanic rocks in Songliao Basin has achieved a breakthrough in the new formation series (Huoshiling Formation) and new rock type (intermediate-basic volcanic rocks). The physical response of deep volcanic rocks is complex and multi-solution because of the variety of mineral composition, no obvious boundary and relatively compact rocks. In order to quantitative analysis the physical responses and differences of deep intermediate-basic volcanic rocks and improve the accuracy of volcanic rock lithology identification and reservoir prediction, 40 typical samples of volcanic rocks from Huoshiling Formation in the southern Songliao Basin are selected, the rock mineral composition and microstructure are quantitatively analyzed, the eight types of rocks are classified into three types by introducing lithofacies and rock structure information, that is effusive andesite, explosive tuff and volcanic breccia, the petrological characteristics and petrophysical parameters under formation pressure and fluid conditions are tested, and the relationships between petrophysical parameters and lithofacies, lithology, physical properties and fluid are clarified. The results show that the petrophysical properties of deep volcanic rocks are controlled by the combination of lithofacies and lithology, the rock physical properties of explosive tuff are the best, density and p-wave impedance can be used as the sensitive parameters for the optimization of high quality reservoirs, the identification threshold and quantitative relationship are different with the types of volcanic rocks, that is density is small than 2.582 g/cm3 for the effusive andesite, 2.509 g/cm3 for the explosive tuff and 2.555 g/cm3 for the volcanic breccia. There are obvious differences in fluid identification ability of rock physical parameters under different rock types, the combination parameters λ-0.28 μ、Ip2-2.15 Is2、λ/μ can be used to identify the fluid properties in the effusive andesite, the explosive tuff and volcanic breccia rocks respectively based on the tested petrophysical parameters and sensitivity analysis results of the fluid saturated rock samples, and the identification effect is good when the sensitive parameters are used in the actual study area.

Key words

Huoshiling Formation / Intermediate-basic volcanic rocks / Rock type / Physical parameters / Elastic parameters / Fluid identification

Cite this article

Download Citations
ChengCheng LI , KeFei ZHANG , XiaoYi MA , et al . Petrophysical characteristics of deep intermediate-basic volcanic gas reservoir[J]. Progress in Geophysics. 2025, 40(2): 580-591 https://doi.org/10.6038/pg2025HH0567

References

Avseth P , Mukerji T , Mavko G . Quantitative Seismic Interpretation: Applying Rock Physics Tools to Reduce Interpretation Risk. Cambridge: Cambridge University Press, 2005 1- 359.
Castagna J P, Batzle M L, Kan T K. 1993. Rock physics—the link between rock properties and AVO response. //Castagna J P, Backus M M eds. Offset-Dependent Reflectivity-Theory and Practice of AVO Analysis. Tulsa: Society of Exploration Geophysicists, 135-171.
Chen S M , Jiang C J . Basin Volcanic Reservoir Seismic Prediction Theory and Method. Beijing: Science Press, 2015
Dai S L . Volcanic lithology and reservoir identification based elastic wave characteristics analysis in Yingcheng Formation, Xujiaweizi depression. Oil Geophysical Prospecting, 2018, 53 (1): 122- 128.
Dai S L , Wang L J , Xin Z K . Testing and characteristic analysis of elastic parameters of basement rock in the paleo-central uplift belt in the northern Songliao Basin. Oil Geophysical Prospecting, 2023, 58 (2): 443- 453.
Gao S S , Hu Z M , Liu H X , et al. Microscopic pore characteristics of different lithological reservoirs. Acta Petrolei Sinica, 2016, 37 (2): 248- 256.
Gardner G H F , Gardner L W , Gregory A R . Formation velocity and density—The diagnostic basics for stratigraphic traps. Geophysics, 1974, 39 (6): 770- 780.
Goodway B, Chen T W, Downton J. 1997. Improved AVO fluid detection and lithology discrimination using Lame petrophysical parameters; "λρ", "μρ", &"λ/μ fluid stack", from P and S inversions. //67th Ann. Internat Mtg., Soc. Expi. Geophys. . Expanded Abstracts, 183-186, doi: 10.1190/1.1885795.
Guo H Y , Yun M H , Ai Y S , et al. Study on petrophysical properties of volcanic reservoir in the third member of Yingcheng Formation in Songliao Basin. Oil Geophysical Prospecting, 2012, 47 (1): 74- 81.
He D F , Ma Y S , Liu B , et al. Main advances and key issues for deep-seated exploration in petroliferous basins in China. Earth Science Frontiers, 2019, 26 (1): 1- 12.
Huang Y L , Wang P J , Shu P , et al. Characteristics and formation mechanism of the Cretaceous intermediate and mafic volcanic reservoirs in Songliao Basin, NE China. Acta Petrologica Sinica, 2010, 26 (1): 82- 92.
Jiang C J , Dai S L , Wu J , et al. Elastic parameter tests and characteristics analysis of volcanic rocks in Yingcheng formation, Northern Songliao Basin. Oil Geophysical Prospecting, 2014, 49 (5): 916- 924.
Li J , She Y Q , Gao Y , et al. Onshore deep and ultra-deep natural gas exploration fields and potentials in China. China Petroleum Exploration, 2019, 24 (4): 403- 417.
Li S H , Yu Y , Li R , et al. Application of neural network inversion in prediction of volcanic rock reservoir. Oil Geophysical Prospecting, 2023, 58 (2): 392- 402.
Lin J J , Ruan B T , Hu M Y , et al. Seismic facies and sedimentary facies of Huoshiling Formation-Yingcheng Formation in Sujiatun Region, Lishu Fault Depression, Songliao Basin. Journal of Northeast Petroleum University, 2019, 43 (1): 87- 98.
Lin S G , Zhao Z H , Xu S J , et al. Enrichment and exploration prospects in deep volcanic gas reservoirs in Songliao Basin. Xinjiang Petroleum Geology, 2013, 34 (2): 174- 178.
Liu J , Liu J , Cao J , et al. Characteristics of reservoir and pore fluid sensitivity parameters based on rock physical experiment: a case study of the middle-deep clastic rock reservoirs in the eastern Pearl River Mouth Basin. Acta Petrolei Sinica, 2019, 40 (S1): 197- 205.
Liu W F . Petrophysical study on volcanic reservoir rocks. Xinjiang Petroleum Geology, 2003, 24 (5): 389- 391.
Lou R X. 2019. Petroleum accumulation rules of the lower cretaceous Huoshiling-Yingcheng formations in fault depressions, southeastern Songliao Basin[Ph. D. thesis](in Chinese). Changchun: Jilin University.
Ma Z G . Experimental investigation into Biot's coefficient and rock elastic moduli. Oil & Gas Geology, 2008, 29 (1): 135- 140.
Ma Z G , Zhu L H , Zhang W H , et al. Petrophysical characteristics of basalt in the southern Leizhou peninsula. Acta Petrolei Sinica, 2020, 41 (6): 702- 710.
Miao C S , Xu W , Liu Y H , et al. Characteristics of volcanic reservoirs in Southern Songliao Basin. Journal of Jilin University (Earth Science Edition), 2020, 50 (2): 635- 643.
National Energy Administration . SY/T 6385-2016 Porosity and permeability measurement under overburden pressure. Beijing: Petroleum Industry Press, 2017
Ning Z H , He Z H , Huang D J , et al. High sensitive fluid identification based on seismic data. Geophysical Prospecting for Petroleum, 2006, 45 (3): 239- 241.
Qiao H Q , Zhang B , Liu C . Research on prediction method of volcanic rock shear wave velocity based on improved Xu-white model. Energies, 2022, 15 (10): 3611
Qiao H Q , Liu C , Fang H , et al. S-wave velocity prediction method of volcanic rock based on statistical rock-physics model. Earth Science, 2023, 48 (8): 2993- 3006.
Wang D , He Z H , Huang D J . Construction of a new fluid identification factor and analysis on its application. Geophysical Prospecting for Petroleum, 2009, 48 (2): 141- 145.
Wu J . Identification of volcanic lithology and reservoir with petrophsical elastic parameters: an example of Yingcheng Formation in Xujiaweizi fault depression, north of Songliao Basin. Bulletin of Geological Science and Technology, 2015, 34 (4): 15- 19.
Yan W L , Li H J , Yang X F , et al. Logging Evaluation Technology and Application of Volcanic Gas Reservoir in Northern Songliao Basin. Beijing: Science Press, 2015
Yang P J , Dong Z L , Liu C Y , et al. Sensitive fluid factor extraction and analysis. Oil Geophysical Prospecting, 2016, 51 (1): 158- 164.
Yang S L , Liu W Z , Yu S Q , et al. Pore textures and its causes of volcanic reservoir in Songliao Basin. Journal of Jilin University (Earth Science Edition), 2007, 37 (3): 506- 512.
Yang X L , Wang F L , Zhang M . Facies-controlled inversion in the prediction of volcanic rock and surrounding reservoir with near offset stack seismic: a case study in No.2 structure of Nanpu sag. Progress in Geophysics, 2022, 37 (4): 1640- 1649.
Zhang D , Guo Y H , Yang Q L , et al. Multiscale petrophysical modeling and reservoir prediction of intermediate-basic volcanic reservoirs based on logging and seismic combination. Acta Geophysica, 2024, 72 (5): 3077- 3089.
Zhang L H , Pan B Z , Shan G Y , et al. Identification of fluid properties of volcanic rocks based on acoustic data of rock samples. Progress in Geophysics, 2020, 35 (6): 2284- 2289.
Zhang W H , Ma Z G , Zhou F , et al. Study on the relationship between the physical properties of basalt rocks and the properties of excited seismic waves in the southern Leizhou Peninsula. Progress in Geophysics, 2021, 36 (2): 706- 715.
Zhang Y Y. 2010. The logging response characteristics and identification of volcanic rocks phase and gas Zone in Changling sag, Songliao Basin[Master's thesis](in Chinese). Changchun: Jilin University.
Zhao H B, Cheng D A, Li L L. 2009. Rock physics analysis of deep volcanic rocks in Daqing Oilfield. //Liu Z W, Sun Y H eds. Beijing 2009 International Geophysical Conference and Exposition. Beijing: Society of Exploration Geophysicists, 1028.
Zhao W Z , Zou C N , Feng Z Q , et al. Geological features and evaluation techniques of deep-seated volcanic gas reservoirs, Songliao Basin. Petroleum Exploration and Development, 2008, 35 (2): 129- 142.
树民 , 传金 . 盆地火山岩储层地震预测理论与方法. 北京: 科学出版社, 2015
世立 . 徐家围子断陷营城组火山岩岩性、储层岩石物理弹性参数特征分析. 石油地球物理勘探, 2018, 53 (1): 122- 128.
世立 , 力娟 , 朝坤 . 松辽盆地北部古中央隆起带基底岩石弹性参数测试及特征分析. 石油地球物理勘探, 2023, 58 (2): 443- 453.
树生 , 志明 , 华勋 , 等. 不同岩性储层的微观孔隙特征. 石油学报, 2016, 37 (2): 248- 256.
洪岩 , 美厚 , 印双 , 等. 松辽盆地营城组三段火山岩储层的岩石物理特性. 石油地球物理勘探, 2012, 47 (1): 74- 81.
国家能源局 . SY/T 6385-2016覆压下岩石孔隙度和渗透率测定方法. 北京: 石油工业出版社, 2017
登发 , 永生 , , 等. 中国含油气盆地深层勘探的主要进展与科学问题. 地学前缘, 2019, 26 (1): 1- 12.
玉龙 , 璞珺 , , 等. 松辽盆地营城组中基性火山岩储层特征及成储机理. 岩石学报, 2010, 26 (1): 82- 92.
传金 , 世立 , , 等. 松辽盆地北部营城组火山岩岩石弹性参数测试及特征分析. 石油地球物理勘探, 2014, 49 (5): 916- 924.
, 源琦 , , 等. 中国陆上深层—超深层天然气勘探领域及潜力. 中国石油勘探, 2019, 24 (4): 403- 417.
素华 , , , 等. 神经网络反演在火山岩储层预测中的应用. 石油地球物理勘探, 2023, 58 (2): 392- 402.
佳佳 , 宝涛 , 明毅 , 等. 松辽盆地梨树断陷苏家屯地区火石岭组—营城组地震相与沉积相. 东北石油大学学报, 2019, 43 (1): 87- 98.
世国 , 泽辉 , 淑娟 , 等. 松辽盆地深层火山岩气藏富集规律与勘探前景. 新疆石油地质, 2013, 34 (2): 174- 178.
, , , 等. 基于岩石物理实验的储层与孔隙流体敏感参数特征——以珠江口盆地东部中-深层碎屑岩储层为例. 石油学报, 2019, 40 (S1): 197- 205.
为付 . 火山岩储集层常规岩石物理学研究方法. 新疆石油地质, 2003, 24 (5): 389- 391.
楼仁兴. 2019. 松辽盆地东南部下白垩统火石岭组-营城组断陷群油气成藏规律[博士论文]. 长春: 吉林大学.
中高 . Biot系数和岩石弹性模量的实验研究. 石油与天然气地质, 2008, 29 (1): 135- 140.
中高 , 立华 , 卫华 , 等. 雷州半岛南部玄武岩岩石物理特征. 石油学报, 2020, 41 (6): 702- 710.
长盛 , , 玉虎 , 等. 松辽盆地南部火山岩储层特征. 吉林大学学报(地球科学版), 2020, 50 (2): 635- 643.
忠华 , 振华 , 德济 , 等. 基于地震资料的高灵敏度流体识别因子. 石油物探, 2006, 45 (3): 239- 241.
汉青 , , , 等. 基于统计学岩石物理模型的火山岩横波速度预测方法. 地球科学, 2023, 48 (8): 2993- 3006.
, 振华 , 德济 . 新流体识别因子的构建与应用分析. 石油物探, 2009, 48 (2): 141- 145.
. 火山岩岩性、储层的岩石物理弹性参数判别: 以松辽盆地北部徐家围子断陷营城组为例. 地质科技情报, 2015, 34 (4): 15- 19.
伟林 , 红娟 , 学峰 , 等. 松辽盆地北部火山岩气藏测井评价技术及应用. 北京: 科学出版社, 2015
培杰 , 兆丽 , 昌毅 , 等. 敏感流体因子定量分析与直接提取. 石油地球物理勘探, 2016, 51 (1): 158- 164.
双玲 , 万洙 , 世泉 , 等. 松辽盆地火山岩储层储集空间特征及其成因. 吉林大学学报(地球科学版), 2007, 37 (3): 506- 512.
晓利 , 方鲁 , . 两步相控反演火山岩及围岩储层预测——以南堡2号构造为例. 地球物理学进展, 2022, 37 (4): 1640- 1649.
丽华 , 保芝 , 刚义 , 等. 基于岩样声波实验数据的火山岩流体性质识别. 地球物理学进展, 2020, 35 (6): 2284- 2289.
卫华 , 中高 , , 等. 雷州半岛南部玄武岩岩石物性与激发地震波属性关系研究. 地球物理学进展, 2021, 36 (2): 706- 715.
张洋洋. 2010. 松辽盆地长岭断陷火山岩相与气层的测井响应特征及识别[硕士论文]. 长春: 吉林大学.
文智 , 才能 , 志强 , 等. 松辽盆地深层火山岩气藏地质特征及评价技术. 石油勘探与开发, 2008, 35 (2): 129- 142.

感谢审稿专家提出的修改意见和编辑部的大力支持!

RIGHTS & PERMISSIONS

Copyright ©2025 Progress in Geophysics. All rights reserved.
PDF(7670 KB)

Accesses

Citation

Detail

Sections
Recommended

/