Using well-log data to modeling factors influencing the amount o adsorbed gas in transitional shale reservoirs

被引:0
|
作者
Liu, Rui [1 ]
Guo, Shaobin [1 ]
Ji, Kun [2 ]
机构
[1] China Univ Geosci, Sch Energy Resources, Beijing 10008, Peoples R China
[2] CNCP LOGGING, Tech Ctr, Xian, Peoples R China
关键词
ADSORPTION; STRATA; BASIN;
D O I
10.1190/INT-2019-0049.1
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Traditional isothermal adsorption experiments often fail to accurately estimate the adsorption capacity of reservoirs with rapidly changing lithology. Temperature, pressure, and mineral composition can influence the adsorption capacity of shale reservoirs. We have examined the influence of these factors on the amount of gas adsorbed in samples from well Yu-88. Samples consist of marine-continental transitional coal-bearing strata from the Upper Paleozoic Shanxi-Taiyuan Formation of the Ordos Basin of China. Shales occur as frequently interbedded, thin, and single layers that exhibit large cumulative thickness and rapid changes in mineral composition. Our experiments on samples B1 and B2 indicated that Langmuir constant V-L varied inversely with temperature, but Langmuir pressure P-L, did not. The P-L exhibits good correlation with illite as well as illite/smectite content but did not clearly correlate with the total organic carbon (TOC). The V-L correlated positively with TOC and negatively with illite/smectite content These relationships enabled modeling of V-L, P-L, and mineral composition. Novel step-by-step modeling methods of well logs generated optimized estimates for well-log parameters including mineral composition. According to the actual temperature of the reservoir, we corrected the Langmuir constant V-L. We calculated a profile for the amount of gas adsorbed in shale intervals of well Yu-88. Comparisons with experimental values indicate relatively high reference values.
引用
收藏
页码:T249 / T258
页数:10
相关论文
共 18 条
  • [1] Novel Method for Evaluating Shale-Gas and Shale-Tight-Oil Reservoirs Using Advanced Well-Log Data
    Freedman, Robert
    Rose, David
    Sun, Boqin
    Brown, Ronald L.
    Malizia, Thomas
    SPE RESERVOIR EVALUATION & ENGINEERING, 2019, 22 (01) : 282 - 301
  • [2] Computer modeling of porosity and lithology for complex reservoirs using well-log measurements
    Salem, HS
    ENERGY SOURCES, 2000, 22 (06): : 515 - 524
  • [3] Improved prediction of shale gas productivity in the Marcellus shale using geostatistically generated well-log data and ensemble machine learning
    Kim, Sungil
    Hong, Yongjun
    Lim, Jung-Tek
    Kim, Kwang Hyun
    COMPUTERS & GEOSCIENCES, 2023, 181
  • [4] A review of permeability-prediction methods for carbonate reservoirs using well-log data
    Babadagli, T
    Al-Salmi, S
    SPE RESERVOIR EVALUATION & ENGINEERING, 2004, 7 (02) : 75 - 88
  • [5] Using the pair-correlation function as a tool to identify the location for shale gas/oil reservoir based on well-log data
    Gassiyev, Aslan
    Huang, Feifei
    Chesnokov, Evgeni M.
    GEOPHYSICS, 2016, 81 (02) : D91 - D109
  • [6] Identification of overpressures resulting from undercompaction and hydrocarbon generation in shale-dominated settings using well-log data
    Tang, Longxiang
    Lu, Jungang
    Yang, Mingyi
    Zhang, Huaqin
    Xiao, Zhenglu
    Yao, Jingli
    Lu, Zixing
    Han, Meimei
    INTERPRETATION-A JOURNAL OF SUBSURFACE CHARACTERIZATION, 2022, 10 (01): : T141 - T150
  • [7] Rock Physics Modeling of Gas Hydrate Reservoirs Through Integrated Core and Well-Log Data in NGHP-02 Area in KG Offshore Basin, India
    Kumar, Sunaj
    Mishra, Debarati
    Chatterjee, Soma
    Tiwari, R. R.
    Avadhani, V. L. N.
    PETROPHYSICS, 2022, 63 (02): : 237 - 255
  • [8] Desorbed gas volume estimation using conventional well-log data for the Montney Formation, Deep Basin, Canada
    Yang, Il Ho
    Lee, Hyun Suk
    JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2018, 162 : 633 - 651
  • [9] Customized interpretation workflow for simultaneous assessment of unconventional shale-gas reservoirs and conventional reservoirs using seismic and log data
    Harilal
    Leading Edge, 2016, 35 (08): : 689 - 694
  • [10] Predictive pore pressure modeling using well-log data in the West Baram Delta, offshore Sarawak Basin, Malaysia
    Asfha, Dejen Teklu
    Gebretsadik, Haylay Tsegab
    Latiff, Abdul Halim Abdul
    Rahmani, Omeid
    GEOMECHANICS AND GEOPHYSICS FOR GEO-ENERGY AND GEO-RESOURCES, 2024, 10 (01)