Log-based evaluation of intralayer heterogeneity of glutenite reservoirs in the Niudong area
ZHOU Jun1(), BIAN Hui-Yuan1(), CHEN Wen-An2, ZHANG Di2, LIU Guo-Liang2, WANG Fei3
1. College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China 2. Research Institute of Exploration and Development, Qinghai Oilfield Company, PetroChina, Dunhuang 736202, China 3. College of Geology Engineering and Geomatics, Chang'an University, Xi'an 710064, China
Glutenite reservoirs in the Niudong area exhibit low porosity and permeability, intricate reservoir structures, and pronounced heterogeneity, making it difficult to classify the reservoirs using conventional logs and further impairing reservoir evaluation accuracy. As indicated by the data from core porosity and permeability tests, thin-section analysis, and X-ray diffraction tests, the glutenite reservoirs in the Niudong area feature high heterogeneity and can be classified into three types based on capillary pressure morphologies. This study evaluated the intralayer heterogeneity of the reservoirs using electrical imaging logs. First, reservoir porosity spectra were derived from the electrical imaging logs. Then, the averages, variances, Lorenz coefficients, and concentration functions of the porosity spectra of different depths were calculated by analyzing these depth-varying porosity spectra. Based on the integrated probability model, the weights of evaluation indices were determined through hierarchical analysis, obtaining the composite index of reservoir heterogeneity. Accordingly, the reservoirs were classified, and the evaluation criteria for reservoir heterogeneity were established. The results of this study were consistent with the results of mercury injection experiments. The method used in this study proves effective in reservoir heterogeneity evaluation, enriching current methods for reservoir heterogeneity evaluation and providing theoretical support for fine-scale reservoir evaluation.
Wu H G, Kang X, Qin M Y, et al. Pore structure characteristics and genesis of heterogeneous conglomerate reservoir of Baikouquan Formation in Mahu Sag,Junggar Basin[J]. Journal of Central South University:Science and Technology, 2022, 53(9):3337-3353.
Chen X J, Liu Z D, Liu Y X, et al. Research into the pore structure of tight reservoirs:A review[J]. Geophysical and Geochemical Exploration, 2022, 46(1):22-31.
[3]
吴元燕, 陈碧珏. 油矿地质学[M]. 2版. 北京: 石油工业出版社,1996.
[3]
Wu Y Y, Chen B J. Petroleum geology[M]. 2th ed. Beijing: Petroleum Industry Press,1996.
[4]
裘怿楠. 油气储层评价技术[M]. 北京: 石油工业出版社,1993.
[4]
Qiu Y N. Evaluation technology of oil and gas reservoir[M]. Beijing: Petroleum Industry Press,1993.
[5]
Yang S S, Huang X R, Yin C, et al. Intra-layer heterogeneity of sandstone with different origins in deep-water environment and its causes[J]. Sustainable Computing:Informatics and Systems, 2019, 21:10-18.
doi: 10.1016/j.suscom.2018.11.003
Cao J J, Luo J L, Madina M, et al. Influence mechanism of micro-heterogeneity on conglomerate reservoir densification:A case study of upper Permian Wutonggou formation in DN8 area of dongdaohaizi sag,Junggar Basin[J]. Earth Science, 2021, 46(10):3435-3452.
Yan K, Yang S C, Ren H Q. Research on quantitative characterization of macroscopic heterogeneity of reservoir[J]. Acta Petrolei Sinica, 2008, 29(6):870-874,879.
doi: 10.7623/syxb200806015
Bian H Y, Han B H, Wang F, et al. Characteristics and classification of glutenite reservoirs in Niudong area,north margin of Qaidam Basin[J]. Journal of Xi’an University of Science and Technology, 2020, 40(5):894-901.
Li H Y, Yue D L, Zhang X J. Characteristics of pore structure and reservoir evaluation of low permeability reservoir in Sulige gas field[J]. Earth Science Frontiers, 2012, 19(2):133-140.
Yuan H Q, Deng X Y, Du H Y, et al. Characterizing the heterogeneity of tight sandstone in outcropped Permian Shanxi Formation,Liujiang Basin[J]. Oil & Gas Geology, 2023, 44(2):468-479.
Tian H, Yang M. The logging evaluation methods for fractured-vuggy carbonate reservoirs[J]. Geophysical and Geochemical Exploration, 2015, 39(3):545-552.
Cui Y T, Wang Z W, Xu F H, et al. Analysis of fracture formation characteristics of igneous rock based on stoneley wave and electrical imaging logging[J]. Journal of Jilin University:Earth Science Edition, 2022, 52(2):624-632.
[14]
Aghli G, Moussavi-Harami R, Mohammadian R. Reservoir heterogeneity and fracture parameter determination using electrical image logs and petrophysical data:A case study,carbonate Asmari Formation,Zagros Basin,SW Iran[J]. Petroleum Science, 2020, 17(1):51-69.
doi: 10.1007/s12182-019-00413-0
Hou Z X, Yu X X, Li D X, et al. Application of new processing technology of electrical imaging logging in reservoir evaluation[J]. Progress in Geophysics, 2020, 35(2):573-578.
Li C, Sima L Q, Shen A J, et al. The application of the reservoir heterogeneity evaluate method with microresistivity image log in FC formation of G region in northeastern Sichuan[J]. Progress in Geophysics, 2015, 30(2):725-732.
Lin J Q, Meng X, Li Q Q, et al. Characterization method and application of electrical imaging logging in conglomerate reservoir:A case study in Mahu Sag of Junggar Basin[J]. Petroleum Drilling Techniques, 2022, 50(2):126-131.
Zuo C J, Wang Z W, Xiang M, et al. The radial pore heterogeneity of volcanic reservoir based on the porosity analysis of micro-electric imaging logging[J]. Geophysical Prospecting for Petroleum, 2016, 55(3):449-454.
doi: 10.3969/j.issn.1000-1441.2016.03.016
Wang Y Z, Pan B Z, Guo Y H. Relationship between relative permeability and electrical parameters of tight sandstone reservoirs[J]. Global Geology, 2017, 36(4):1277-1283.
Zhang F, Gao M, Chen G J, et al. Application of electrical imaging logging porosity spectrum in identification of effective reservoir in sandy conglomeratic reservoirs[J]. Science Technology and Engineering, 2022, 22(2):488-495.
Yue C W, Yang X M, Zhong X Q, et al. Evaluation of formation heterogeneity using Lorentz coefficient of logging curves[J]. Journal of Jilin University:Earth Science Edition, 2015, 45(5):1539-1546.
Huang H D, Liu X M, Cai Y J, et al. Igneous rock fracture prediction with well logging and seismic data[J]. Oil Geophysical Prospecting, 2015, 50(5):942-950,805-806.