Liao Dongliang. Interpretation and Application of ECS Logging Data in Shale Formations[J]. Petroleum Drilling Techniques, 2015, 43(4): 102-107. DOI: 10.11911/syztjs.201504018
Citation: Liao Dongliang. Interpretation and Application of ECS Logging Data in Shale Formations[J]. Petroleum Drilling Techniques, 2015, 43(4): 102-107. DOI: 10.11911/syztjs.201504018

Interpretation and Application of ECS Logging Data in Shale Formations

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  • Received Date: December 17, 2014
  • Revised Date: June 03, 2015
  • It is difficult to accurately evaluate clay minerals, including those that contain clasolite and carbonates by using conventional logging methods.The crystal detector of the ECS logger measures gamma rays produced by collision of neutron sources and the strata minerals, so the ECS element log response equation was established according to the corresponding relationship between minerals and gamma rays. The optimized inversion method was used to determine mineral types, and calculate mineral content, grain density and brittleness index. By using this method, the ECS logging data of Well X in shale gas block A was interpreted, the elements including Si, Al, Fe, Ca, Su and K were selected to determine six to eight kinds of minerals and their contents, related to 10 minerals such as quartz, feldspar, limestone, dolomite, illite, chlorite, montmorillonite, pyrite, mica and anhydrite. Eventually, the inversion results coincided well with the core mineral analysis results, the grain density of the shale formation in this well was calculated according to the contents of the minerals, which ranged from 2.65-2.75 g/m3, the brittle index is 40-60. It showed that shale formation minerals and their contents can be evaluated by using ECS logging data, and the grain density and brittleness index of shale formation can be calculated. These results could provide an accurate evaluation for shale formations and guide shale formation fracturing.
  • [1]
    Hertzog R,Colson L,Seeman O,et al.Geochemical logging with spectrometry tools[R].SPE 16792,1989.
    [2]
    Harvey P K,Lofts J C,Lovell M A.Mineralogy logs: element to mineral transforms and compositional colinearity in sediments: SPWLA the 33rd Annual Logging Symposium,Houston,June 14-17,1992[C].
    [3]
    Herron S L,Herron M M.Quantitative lithology: An application for open and cased hole spectroscopy: SPWLA the 37rd Annual Logging Symposium,New Orleans,June16-19,1996[C].
    [4]
    Quirein J,Witkowsky J,Truax J A,et al.Integrating core data and wireline geochemical data for formation evalution and characterization of shale gas reservoirs[R].SPE 134559,2010.
    [5]
    Herron M M,Herron S L,Grau,J A,et al.Real-time petrophysical analysis in siliciclastics form the integration of spectroscopy and triple-combo logging[R].SPE77631,2002.
    [6]
    雍世和,孙建孟.最优化测井解释[M].东营:石油大学出版社,1995:87-119. Yong Shihe,Sun Jianmeng.Optimization logging interpretation[M].Dongying: Petroleum University Press,1995: 87-119.
    [7]
    肖立志.一种改进的数字测井最优化解释方法[J].石油学报,1991,12(2):40-50. Xiao Lizhi.An improved interpretation method for digital log,Acta Petrolei Sinica[J].Acta Petrolei Sinica,1991,12(2): 40-50.
    [8]
    Jarvie D M,Hill R J,Ruble T E,et al.Unconventional shale-gas systems: the Mississippian Barnett Shale of north-central Texas as one model for thermogenic shale-gas assessment[J].AAPG Bulletin,2007,91(4): 475-499.
    [9]
    Buller D,Hughes S N,Market J,et al.Preophysical evaluation for enhancing hydraulic stimulation in horizontal shale gas wells[R].SPE 132990,2010.
    [10]
    廖东良,肖立志,张元春.基于矿物组分与断裂韧度的页岩地层脆性指数评价模型[J].石油钻探技术,2014,42(4):37-41. Liao Dongliang,Xiao Lizhi,Zhang Yuanchun.Evaluation model for shale brittleness index based on mineral content and fracture toughness[J].Petroleum Drilling Techniques,2014,42(4): 37-41.
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