A data processing workflow for borehole enlargement identification and characterisation using petrophysical logs
Borehole breakouts provide valuable information with respect to the evaluation of the in-situ stress direction and magnitude, and also verification of any geomechanical models built for a specific field. Identifying the locations along a borehole where the breakouts form is therefore very important....
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| Format: | Thesis |
| Language: | English |
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Curtin University
2009
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| Online Access: | http://hdl.handle.net/20.500.11937/771 |
| _version_ | 1848743475664650240 |
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| author | Soroush, Hamed |
| author_facet | Soroush, Hamed |
| author_sort | Soroush, Hamed |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Borehole breakouts provide valuable information with respect to the evaluation of the in-situ stress direction and magnitude, and also verification of any geomechanical models built for a specific field. Identifying the locations along a borehole where the breakouts form is therefore very important. On the other hand, the borehole geometry (defined as width and depth of breakouts), which is a critical factor in completion and production optimisation design, can also be estimated from the back analysis of breakout information. While breakout width has been widely used in obtaining an estimate of the maximum horizontal stress magnitude, few studies have been reported on the estimation of breakout depth and the information it may provide.Caliper and image logs are customarily used to identify and characterise borehole enlargement zones; in particular, the breakouts. However, these methods are limited in their applications in many instances. In addition, good quality image logs are not available in many wells including old wells. This leads to a need for the development of a new approach to identify the location of borehole enlargements along a wellbore.This research aims to understand the mechanisms under which breakouts form with respect to a rock’s physical and mechanical properties. Petrophysical logs, which are often acquired in most of the drilled wells, show correlations with mechanical properties of the rock. Therefore, this research attempts to develop an approach to identify the location of borehole enlargement zones using the information gained from petrophysical logs.This research introduces a new multi-variable approach based on various data processing techniques (including wavelet, classifiers, and neural networks) to extract rock properties from different petrophysical logs. This information was combined using a robust data fusion technique which determined the location of the enlarged borehole. The results demonstrated the accuracy of the location of the borehole enlargement identified along a borehole compared to that observed using calipers and image logs.In addition, there were correlations between breakout width and depth measurements when measurements taken from high quality acoustic image logs were used. Elastic and elastoplastic finite element numerical models also showed how breakout width and depth could change due to a change in different rock properties. The models were verified by comparing results of numerical analysis with real observations from field data. |
| first_indexed | 2025-11-14T05:46:10Z |
| format | Thesis |
| id | curtin-20.500.11937-771 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T05:46:10Z |
| publishDate | 2009 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-7712018-06-12T08:10:23Z A data processing workflow for borehole enlargement identification and characterisation using petrophysical logs Soroush, Hamed classifiers petrophysical logs borehole breakouts neural networks physical and mechanical properties rocks image logs calipers wavelet borehole enlargement zones Borehole breakouts provide valuable information with respect to the evaluation of the in-situ stress direction and magnitude, and also verification of any geomechanical models built for a specific field. Identifying the locations along a borehole where the breakouts form is therefore very important. On the other hand, the borehole geometry (defined as width and depth of breakouts), which is a critical factor in completion and production optimisation design, can also be estimated from the back analysis of breakout information. While breakout width has been widely used in obtaining an estimate of the maximum horizontal stress magnitude, few studies have been reported on the estimation of breakout depth and the information it may provide.Caliper and image logs are customarily used to identify and characterise borehole enlargement zones; in particular, the breakouts. However, these methods are limited in their applications in many instances. In addition, good quality image logs are not available in many wells including old wells. This leads to a need for the development of a new approach to identify the location of borehole enlargements along a wellbore.This research aims to understand the mechanisms under which breakouts form with respect to a rock’s physical and mechanical properties. Petrophysical logs, which are often acquired in most of the drilled wells, show correlations with mechanical properties of the rock. Therefore, this research attempts to develop an approach to identify the location of borehole enlargement zones using the information gained from petrophysical logs.This research introduces a new multi-variable approach based on various data processing techniques (including wavelet, classifiers, and neural networks) to extract rock properties from different petrophysical logs. This information was combined using a robust data fusion technique which determined the location of the enlarged borehole. The results demonstrated the accuracy of the location of the borehole enlargement identified along a borehole compared to that observed using calipers and image logs.In addition, there were correlations between breakout width and depth measurements when measurements taken from high quality acoustic image logs were used. Elastic and elastoplastic finite element numerical models also showed how breakout width and depth could change due to a change in different rock properties. The models were verified by comparing results of numerical analysis with real observations from field data. 2009 Thesis http://hdl.handle.net/20.500.11937/771 en Curtin University restricted |
| spellingShingle | classifiers petrophysical logs borehole breakouts neural networks physical and mechanical properties rocks image logs calipers wavelet borehole enlargement zones Soroush, Hamed A data processing workflow for borehole enlargement identification and characterisation using petrophysical logs |
| title | A data processing workflow for borehole enlargement identification and characterisation using petrophysical logs |
| title_full | A data processing workflow for borehole enlargement identification and characterisation using petrophysical logs |
| title_fullStr | A data processing workflow for borehole enlargement identification and characterisation using petrophysical logs |
| title_full_unstemmed | A data processing workflow for borehole enlargement identification and characterisation using petrophysical logs |
| title_short | A data processing workflow for borehole enlargement identification and characterisation using petrophysical logs |
| title_sort | data processing workflow for borehole enlargement identification and characterisation using petrophysical logs |
| topic | classifiers petrophysical logs borehole breakouts neural networks physical and mechanical properties rocks image logs calipers wavelet borehole enlargement zones |
| url | http://hdl.handle.net/20.500.11937/771 |