Managed Pressure Drilling; Overview, Modeling, and Case Study

Бурение с контролируемым давлением: обзор, моделирование и пример из практики
A. Alizadeh, C.. Peña, M. Brzezinski, M. Arnone, W. Al-Hashmy, E. Dietrich
2026-04-22

MPDManaged Pressure DrillingPressure While Drillingconstant bottom hole pressurehydraulic modelingnon-productive timerate of penetrationrheological models
Abstract Managed Pressure Drilling (MPD) is defined by IADC as "an adaptive drilling process used to precisely control the annular pressure profile throughout the wellbore". It aims to facilitate safer and more efficient drilling of hydrocarbon wells by employing automated chokes to manage the wellbore pressure profile and maintain a constant bottom hole pressure (CBHP) at a specified anchor point. Since its development, MPD has gained significant popularity due to its numerous advantages. While MPD is particularly designed for drilling wells with a narrow pressure window, it helps to mitigate various drilling hazards and reduces wellbore-related problems, especially those caused by pressure deviations, such as kicks, lost circulation, stuck pipe, wellbore instability, and twist-offs. MPD is also proven to enhance drilling performance and increase rate of penetration (ROP) by reducing fluid pressure at the bottom of the well. MPD can improve well economics by reducing non-productive time (NPT) for any well. At the heart of MPD operations is hydraulic modeling, which gathers well operational parameters and calculates the pressure profile along the wellbore. Numerous rheological models are available in literature, each with their own assumptions, simplifications, and advantages. This article aims to review MPD technology, showcase a variety of successful MPD case studies, and discuss the economic and safety benefits MPD brings to the drilling industry. Then, in the main section of the paper, two MPD wells drilled with PWD tool are used to compare downhole measurements of Pressure While Drilling tools against predictions from different hydraulics rheology models. After evaluating each models' accuracy, the most reliable model is used to run a parametric analysis to assess the impact of various drilling parameters (RPM, ROP, flow rate, and mud properties) on the well's pressure profile. The case study results indicate that hydraulic modeling can serve as a reasonably accurate alternative to expensive PWD tools for predicting downhole pressure. It is also discussed that, while ROP significantly influences pressure due to increased cuttings content in the mud, RPM is another critical parameter that must not be overlooked.
1
Comparison of downhole PWD measurements from two MPD wells against different rheology model predictions identified the most reliable model for parametric analysis.
2
Hydraulic modeling using various rheological models can predict the pressure profile along the wellbore and serves as a reasonably accurate alternative to expensive Pressure While Drilling (PWD) tools.
3
MPD enhances drilling performance and increases rate of penetration (ROP) by reducing bottomhole fluid pressure, improving well economics via reduced non-productive time (NPT).
4
MPD mitigates drilling hazards (kicks, lost circulation, stuck pipe, wellbore instability, twist-offs) and reduces wellbore-related problems caused by pressure deviations.
5
Managed Pressure Drilling (MPD) precisely controls annular pressure to maintain constant bottom hole pressure (CBHP) using automated chokes.
6
Parametric analysis shows ROP significantly influences downhole pressure through increased cuttings content, and RPM is also a critical parameter affecting pressure.

Managed Pressure Drilling (MPD) operations and hydraulic modeling of the wellbore pressure profile

Accuracy and applicability of hydraulic/rheological models (and parametric effects of RPM, ROP, flow rate, and mud properties) for predicting and controlling annular/downhole pressure profiles during MPD compared to Pressure While Drilling (PWD) measurements, and resulting safety/economic impacts

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2026-04-22
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Authors
A. Alizadeh
C.. Peña
M. Brzezinski
M. Arnone
W. Al-Hashmy
E. Dietrich
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