Real-Time Pore Pressure Detection: Indicators and Improved Methods
High uncertainties may exist in the predrill pore pressure prediction in new prospects and deepwater subsalt wells; therefore, real-time pore pressure detection is highly needed to reduce drilling risks. The methods for pore pressure detection (the resistivity, sonic, and corrected d-exponent method...
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Series: | Geofluids |
Online Access: | http://dx.doi.org/10.1155/2017/3179617 |
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doaj-ac3cffd0daf94bb08b35d86bb2045be72020-11-25T00:27:26ZengHindawi-WileyGeofluids1468-81151468-81232017-01-01201710.1155/2017/31796173179617Real-Time Pore Pressure Detection: Indicators and Improved MethodsJincai Zhang0Shangxian Yin1Geomech Energy, Houston, TX, USANorth China Institute of Science and Technology, Yanjiao, Beijing, ChinaHigh uncertainties may exist in the predrill pore pressure prediction in new prospects and deepwater subsalt wells; therefore, real-time pore pressure detection is highly needed to reduce drilling risks. The methods for pore pressure detection (the resistivity, sonic, and corrected d-exponent methods) are improved using the depth-dependent normal compaction equations to adapt to the requirements of the real-time monitoring. A new method is proposed to calculate pore pressure from the connection gas or elevated background gas, which can be used for real-time pore pressure detection. The pore pressure detection using the logging-while-drilling, measurement-while-drilling, and mud logging data is also implemented and evaluated. Abnormal pore pressure indicators from the well logs, mud logs, and wellbore instability events are identified and analyzed to interpret abnormal pore pressures for guiding real-time drilling decisions. The principles for identifying abnormal pressure indicators are proposed to improve real-time pore pressure monitoring.http://dx.doi.org/10.1155/2017/3179617 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jincai Zhang Shangxian Yin |
spellingShingle |
Jincai Zhang Shangxian Yin Real-Time Pore Pressure Detection: Indicators and Improved Methods Geofluids |
author_facet |
Jincai Zhang Shangxian Yin |
author_sort |
Jincai Zhang |
title |
Real-Time Pore Pressure Detection: Indicators and Improved Methods |
title_short |
Real-Time Pore Pressure Detection: Indicators and Improved Methods |
title_full |
Real-Time Pore Pressure Detection: Indicators and Improved Methods |
title_fullStr |
Real-Time Pore Pressure Detection: Indicators and Improved Methods |
title_full_unstemmed |
Real-Time Pore Pressure Detection: Indicators and Improved Methods |
title_sort |
real-time pore pressure detection: indicators and improved methods |
publisher |
Hindawi-Wiley |
series |
Geofluids |
issn |
1468-8115 1468-8123 |
publishDate |
2017-01-01 |
description |
High uncertainties may exist in the predrill pore pressure prediction in new prospects and deepwater subsalt wells; therefore, real-time pore pressure detection is highly needed to reduce drilling risks. The methods for pore pressure detection (the resistivity, sonic, and corrected d-exponent methods) are improved using the depth-dependent normal compaction equations to adapt to the requirements of the real-time monitoring. A new method is proposed to calculate pore pressure from the connection gas or elevated background gas, which can be used for real-time pore pressure detection. The pore pressure detection using the logging-while-drilling, measurement-while-drilling, and mud logging data is also implemented and evaluated. Abnormal pore pressure indicators from the well logs, mud logs, and wellbore instability events are identified and analyzed to interpret abnormal pore pressures for guiding real-time drilling decisions. The principles for identifying abnormal pressure indicators are proposed to improve real-time pore pressure monitoring. |
url |
http://dx.doi.org/10.1155/2017/3179617 |
work_keys_str_mv |
AT jincaizhang realtimeporepressuredetectionindicatorsandimprovedmethods AT shangxianyin realtimeporepressuredetectionindicatorsandimprovedmethods |
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1725339800197660672 |