Brittleness index estimation in a tight shaly sandstone reservoir using well logs

Abstract Premise evaluation of the ability of fracture network forming using hydraulic fracturing is crucial for the development of tight shaly sandstone reservoirs. X-ray diffraction, petrographic analysis integrated with petrophysical well logs was used to provide insights to the brittleness of Chang 7 shaly sandstone in the Ordos basin. The mineralogical composition of this unit is quartz, clay, carbonates and feldspar with minor quantities of pyrite. Quartz and carbonate are the critical brittle minerals. The brittleness index defined in terms of mineralogy and geomechanical properties was investigated respectively. The geomechanical brittleness derived from dipole acoustic logs has a wide range from 0.98% to 93.21%, averaging 58.07%. In contrast, the mineralogical brittleness index from X-ray diffraction results is in the range of 28.26–78.85%, averaging 59.31%. The geomechanical brittleness index could be easily calculated using the dipole acoustic and bulk density logs. For wells without dipole acoustic logs, predicting the brittleness index using conventional well log suits is of great importance. The mineralogical brittleness index was then correlated with their well-log signatures. Statistical regression analysis was carried out to find the relations between brittleness index and conventional well logs, and it is found that the ratio of gamma ray to photoelectric absorption cross section index (GR/Pe) shows a good correlation with brittleness index. Therefore, the brittleness index could be estimated using conventional logs (GR/Pe). The geomechanical brittleness index and the test oil results confirm the reliability of the brittleness index estimation model. Favorable layers for hydraulic fracturing are mainly associated with the intervals with high values of brittleness index. This work is valuable for the evaluation of hydraulic fracturing effects in unconventional oil and gas reservoirs in the future.

[1]  C. Hecht,et al.  Relations of Rock Structure and Composition to Petrophysical and Geomechanical Rock Properties: Examples from Permocarboniferous Red-Beds , 2005 .

[2]  D. Jarvie,et al.  Unconventional shale-gas systems: The Mississippian Barnett Shale of north-central Texas as one model for thermogenic shale-gas assessment , 2007 .

[3]  Peng Han,et al.  A novel experimental approach for fracability evaluation in tight-gas reservoirs , 2015 .

[4]  K. Chesser,et al.  Seismic reservoir characterization in resource shale plays: Stress analysis and sweet spot discrimination , 2011 .

[5]  Hossein Memarian,et al.  イラン,ガッチサラン蒸発形成層の無水石膏,泥灰土,塩の動的特性 , 2013 .

[6]  A. Boruah,et al.  Microstructure and pore system analysis of Barren Measures shale of Raniganj field, India , 2015 .

[7]  A. Folkestad,et al.  Utilising borehole image logs to interpret delta to estuarine system: A case study of the subsurface Lower Jurassic Cook Formation in the Norwegian northern North Sea , 2012 .

[8]  Carl H. Sondergeld,et al.  Petrophysical Considerations in Evaluating and Producing Shale Gas Resources , 2010 .

[9]  D. Jingen Fracability evaluation of shale-gas reservoirs , 2013 .

[10]  Linye Zhang,et al.  Geochemical and geological characteristics of the Es3L lacustrine shale in the Bonan sag, Bohai Bay Basin, China , 2015 .

[11]  Hui Zhou,et al.  Evaluation Methodology of Brittleness of Rock Based on Post-Peak Stress–Strain Curves , 2015, Rock Mechanics and Rock Engineering.

[12]  Weichao Yan,et al.  Imbibition inducing tensile fractures and its influence on in-situ stress analyses: A case study of shale gas drilling , 2015 .

[13]  O. Bábek,et al.  Spectral gamma-ray logging of the Grès d'Annot, SE France: An outcrop analogue to geophysical facies mapping and well-log correlation of sand-rich turbidite reservoirs , 2015 .

[14]  R. Altindag,et al.  Assessment of some brittleness indexes in rock-drilling efficiency , 2010 .

[15]  C. Liang,et al.  The shale characteristics and shale gas exploration prospects of the Lower Silurian Longmaxi shale, Sichuan Basin, South China , 2014 .

[16]  N. Goktan R.M. Gunes Yilmaz,et al.  A new methodology for the analysis of the relationship between rock brittleness index and drag pick cutting efficiency , 2005 .

[17]  Shicheng Zhang,et al.  A new method for evaluation of fracture network formation capacity of rock , 2015 .

[18]  Xuan Feng,et al.  A shale rock physics model for analysis of brittleness index, mineralogy and porosity in the Barnett Shale , 2013 .

[19]  P. Pedersen,et al.  Reservoir characterization of a tight oil reservoir, the middle Jurassic Upper Shaunavon Member in the Whitemud and Eastbrook pools, SW Saskatchewan , 2013 .

[20]  Saffet Yagiz,et al.  Assessment of brittleness using rock strength and density with punch penetration test , 2009 .

[21]  Kevin J. Smart,et al.  Geomechanical modeling of hydraulic fracturing: Why mechanical stratigraphy, stress state, and pre-existing structure matter , 2014 .

[22]  R. Altindag,et al.  A brittleness index to estimate fracture toughness , 2004 .

[23]  Yan Wei,et al.  Logging identification of the Longmaxi mud shale reservoir in the Jiaoshiba area, Sichuan Basin , 2014 .

[24]  R. Rickman,et al.  A Practical Use of Shale Petrophysics for Stimulation Design Optimization: All Shale Plays Are Not Clones of the Barnett Shale , 2008 .

[25]  Erling Fjær,et al.  Chapter 3 Geological aspects of petroleum related rock mechanics , 2008 .

[26]  Xiao Xianming Mineral composition and brittleness of three sets of Paleozoic organic-rich shales in China South area , 2013 .

[27]  Cheryl A. Mnich,et al.  Mechanical anisotropy in the Woodford Shale, Permian Basin Origin, magnitude, and scale , 2011 .