Rock physics modelling of the carbonate reservoirs: A log-based algorithm to determine the pore aspect ratio
Rock physics models play an important role in understanding the elastic behavior of saturated rocks, and in the quantitative interpretation of seismic data in the areas between well controls. Most of the rock physics models were developed for clastic reservoirs. However, estimation of elastic proper...
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| Published in | Journal of applied geophysics Vol. 173; p. 103930 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.02.2020
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| ISSN | 0926-9851 1879-1859 |
| DOI | 10.1016/j.jappgeo.2019.103930 |
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| Abstract | Rock physics models play an important role in understanding the elastic behavior of saturated rocks, and in the quantitative interpretation of seismic data in the areas between well controls. Most of the rock physics models were developed for clastic reservoirs. However, estimation of elastic properties in the carbonate reservoirs have been criticized recently. The major challenge on these reservoirs are primarily due to the pore type variation and the presence of fractures across the rock matrix. To overcome this issue, an aspect ratio (the ratio between the minor and major axes of an ellipsoidal pore) of the pore space was defined to consider the geometry of pores. Aspect ratio has a significant impact on the velocity of the saturated rock, however its quantification on the reservoir scale remains a challenging subject. Aspect ratio is commonly estimated from thin section analysis, however, thin sections are not commonly available for the entire logged reservoir interval. Hence, a constant aspect ratio is typically allocated for each pore type within the target layer. Considering the variation of depositional setting with depth, as well as including the role of diagenetic processes on the carbonate rocks, allocating a single constant aspect ratio across the reservoir interval could introduce uncertainties. In this paper, we introduce a log-based algorithm to estimate a variable aspect ratio that can be applied over the entire length of the logged interval. This method is based on the diverse influence of different pore types on the velocity and density logs. In addition, we include the impact of pressure variation on Xu and Payne (2009) model. Utilizing our methodology, the velocity log is estimated in a carbonate reservoir. The estimated velocity log shows better match with the measured velocity log compared with Lee (2005) (improved Gassmann) and Xu and Payne (2009) models. There are however some disparities left in the reconstruction of the velocity profile that encourages to understand the carbonate reservoirs further.
•A technique is introduced to calculate the aspect ratio of the reservoir rocks utilizing well logs.•Rock physics models of the carbonate reservoirs are critically reviewed.•The pressure impact is included on the carbonate rock physics modelling.•Variable aspect ratio by depth would significantly increase the accuracy of a rock physics model. |
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| AbstractList | Rock physics models play an important role in understanding the elastic behavior of saturated rocks, and in the quantitative interpretation of seismic data in the areas between well controls. Most of the rock physics models were developed for clastic reservoirs. However, estimation of elastic properties in the carbonate reservoirs have been criticized recently. The major challenge on these reservoirs are primarily due to the pore type variation and the presence of fractures across the rock matrix. To overcome this issue, an aspect ratio (the ratio between the minor and major axes of an ellipsoidal pore) of the pore space was defined to consider the geometry of pores. Aspect ratio has a significant impact on the velocity of the saturated rock, however its quantification on the reservoir scale remains a challenging subject. Aspect ratio is commonly estimated from thin section analysis, however, thin sections are not commonly available for the entire logged reservoir interval. Hence, a constant aspect ratio is typically allocated for each pore type within the target layer. Considering the variation of depositional setting with depth, as well as including the role of diagenetic processes on the carbonate rocks, allocating a single constant aspect ratio across the reservoir interval could introduce uncertainties. In this paper, we introduce a log-based algorithm to estimate a variable aspect ratio that can be applied over the entire length of the logged interval. This method is based on the diverse influence of different pore types on the velocity and density logs. In addition, we include the impact of pressure variation on Xu and Payne (2009) model. Utilizing our methodology, the velocity log is estimated in a carbonate reservoir. The estimated velocity log shows better match with the measured velocity log compared with Lee (2005) (improved Gassmann) and Xu and Payne (2009) models. There are however some disparities left in the reconstruction of the velocity profile that encourages to understand the carbonate reservoirs further.
•A technique is introduced to calculate the aspect ratio of the reservoir rocks utilizing well logs.•Rock physics models of the carbonate reservoirs are critically reviewed.•The pressure impact is included on the carbonate rock physics modelling.•Variable aspect ratio by depth would significantly increase the accuracy of a rock physics model. |
| ArticleNumber | 103930 |
| Author | Falahat, Reza Farrokhnia, Foroogh |
| Author_xml | – sequence: 1 givenname: Reza surname: Falahat fullname: Falahat, Reza email: rezafalahat@sut.ac.ir organization: Sahand University of Technology, Tabriz, Iran – sequence: 2 givenname: Foroogh surname: Farrokhnia fullname: Farrokhnia, Foroogh organization: Nargan Amitis Energy Development (NAED), Tehran, Iran |
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| CitedBy_id | crossref_primary_10_1007_s11600_023_01258_3 crossref_primary_10_1144_petgeo2023_028 crossref_primary_10_1016_j_gsf_2022_101405 crossref_primary_10_1190_INT_2022_0088_1 crossref_primary_10_1016_j_geoen_2024_212915 crossref_primary_10_1016_j_geoen_2023_211640 crossref_primary_10_1007_s11600_024_01493_2 crossref_primary_10_1016_j_jappgeo_2020_104253 crossref_primary_10_2118_209582_PA crossref_primary_10_3389_feart_2021_641705 crossref_primary_10_1016_j_petrol_2020_107697 |
| Cites_doi | 10.1190/1.1599691 10.3133/sir20055119 10.1190/1.1707070 10.1190/1.1440450 10.1111/j.1365-2478.1995.tb00126.x 10.3133/sir20085196 10.1190/1.3064148 10.1190/1.1443207 10.1190/geo2014-0366.1 10.1111/1365-2478.12005 10.1144/petgeo2014-008 |
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| Keywords | Carbonate reservoirs Rock physics modelling Velocity estimation Elastic properties Aspect ratio |
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| References | Gassmann (bb0050) 1951; 96 Avseth, Mukerji, Mavko (bb0015) 2010 Batzle, Wang (bb0020) 1992; 57 MacBeth (bb0075) 2004; 69 Lee (bb0070) 2008 Mastellone, Borromeo, Mastellone, Duca, Ortenzi (bb0080) 2017 Eberli, Baechle, Anselmetti, Incze (bb0030) 2003; 22 Kumar, Han (bb0055) 2005 Lee (bb0065) 2005 Amini, MacBeth, Shams (bb0005) 2011 Doyen (bb0025) 2007 El-Husseinya, Vegab, Nizamuddin (bb0035) 2019; S0920-4105 Pride (bb0090) 2005; 50 Xu, Payne (bb0105) 2009; 28 Xu, White (bb0110) 1995; 43 Falahat, Shams, MacBeth (bb0040) 2013; 61 Nurmi, Frisinger (bb0085) 1983 Wang, Wang, Wang, Li (bb0100) 2015; 80 Anselmetti, Eberli (bb0010) 1999; 83 Falahat, Obidegwu, Shams, MacBeth (bb0045) 2014; 20 Shiri, Falahat (bb0095) 2019 Kuster, Toksoz (bb0060) 1974; 39 Pride (10.1016/j.jappgeo.2019.103930_bb0090) 2005; 50 Gassmann (10.1016/j.jappgeo.2019.103930_bb0050) 1951; 96 Wang (10.1016/j.jappgeo.2019.103930_bb0100) 2015; 80 Falahat (10.1016/j.jappgeo.2019.103930_bb0045) 2014; 20 Nurmi (10.1016/j.jappgeo.2019.103930_bb0085) 1983 Avseth (10.1016/j.jappgeo.2019.103930_bb0015) 2010 Anselmetti (10.1016/j.jappgeo.2019.103930_bb0010) 1999; 83 Mastellone (10.1016/j.jappgeo.2019.103930_bb0080) 2017 Shiri (10.1016/j.jappgeo.2019.103930_bb0095) 2019 Lee (10.1016/j.jappgeo.2019.103930_bb0065) 2005 Lee (10.1016/j.jappgeo.2019.103930_bb0070) 2008 Kumar (10.1016/j.jappgeo.2019.103930_bb0055) 2005 Xu (10.1016/j.jappgeo.2019.103930_bb0110) 1995; 43 Eberli (10.1016/j.jappgeo.2019.103930_bb0030) 2003; 22 MacBeth (10.1016/j.jappgeo.2019.103930_bb0075) 2004; 69 Xu (10.1016/j.jappgeo.2019.103930_bb0105) 2009; 28 Doyen (10.1016/j.jappgeo.2019.103930_bb0025) 2007 Falahat (10.1016/j.jappgeo.2019.103930_bb0040) 2013; 61 El-Husseinya (10.1016/j.jappgeo.2019.103930_bb0035) 2019; S0920-4105 Amini (10.1016/j.jappgeo.2019.103930_bb0005) 2011 Batzle (10.1016/j.jappgeo.2019.103930_bb0020) 1992; 57 Kuster (10.1016/j.jappgeo.2019.103930_bb0060) 1974; 39 |
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| Title | Rock physics modelling of the carbonate reservoirs: A log-based algorithm to determine the pore aspect ratio |
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