Best Real Time Model Development of an Oil Well Drilling System

A drilling system consists of a rotating drill string, which is placed into the well. The drill fluid is pumped through the drill string and exits through the choke valve. During drilling, the pore pressure (minimum limit) and the fracture pressure (maximum limit) define mud density range and pressu...

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Main Authors: M. Vega, M. Freitas, L. Fernandes, C. Scheid, A. Martins
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2012-05-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/7479
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spelling doaj-0f2bc6172ca54479a3d106e3b7e75d612021-02-22T21:08:58ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162012-05-012610.3303/CET1226094Best Real Time Model Development of an Oil Well Drilling SystemM. VegaM. FreitasL. FernandesC. ScheidA. MartinsA drilling system consists of a rotating drill string, which is placed into the well. The drill fluid is pumped through the drill string and exits through the choke valve. During drilling, the pore pressure (minimum limit) and the fracture pressure (maximum limit) define mud density range and pressure operational window. Several disturbances affect bottom hole pressure; for example, as the length of the well increases, the bottom hole pressure varies for growing hydrostatic pressure levels. In addition, the pipe connection procedure causes severe fluctuations in well fluids flow, changing well pressure. Permeability and porous reservoir pressure governs native reservoir fluid well influx, affecting flow patterns inside the well and well pressure. The objective being tracked is operating under desired pressure levels, which assures process safety, also reducing costs. In this scenario, modelling techniques are important tools for narrow operational windows, commonly observed at deepwater and pre-salt layer environments. The major objective of this paper is real time building and comparing model performance for predicting annulus bottom hole pressure, using real time flow, choke index and ROP (rate of penetration) data, available from a drilling site. Neural Network (NN) based models were used successfully for on-line identification purposes, using an adaptive methodology. The proposed methodology can be employed at drilling sites, through the use of PWD (Pressure While Drilling) and mud-logging tools, providing real time data and helping operators to make important decisions concerning safety of the drilling process.https://www.cetjournal.it/index.php/cet/article/view/7479
collection DOAJ
language English
format Article
sources DOAJ
author M. Vega
M. Freitas
L. Fernandes
C. Scheid
A. Martins
spellingShingle M. Vega
M. Freitas
L. Fernandes
C. Scheid
A. Martins
Best Real Time Model Development of an Oil Well Drilling System
Chemical Engineering Transactions
author_facet M. Vega
M. Freitas
L. Fernandes
C. Scheid
A. Martins
author_sort M. Vega
title Best Real Time Model Development of an Oil Well Drilling System
title_short Best Real Time Model Development of an Oil Well Drilling System
title_full Best Real Time Model Development of an Oil Well Drilling System
title_fullStr Best Real Time Model Development of an Oil Well Drilling System
title_full_unstemmed Best Real Time Model Development of an Oil Well Drilling System
title_sort best real time model development of an oil well drilling system
publisher AIDIC Servizi S.r.l.
series Chemical Engineering Transactions
issn 2283-9216
publishDate 2012-05-01
description A drilling system consists of a rotating drill string, which is placed into the well. The drill fluid is pumped through the drill string and exits through the choke valve. During drilling, the pore pressure (minimum limit) and the fracture pressure (maximum limit) define mud density range and pressure operational window. Several disturbances affect bottom hole pressure; for example, as the length of the well increases, the bottom hole pressure varies for growing hydrostatic pressure levels. In addition, the pipe connection procedure causes severe fluctuations in well fluids flow, changing well pressure. Permeability and porous reservoir pressure governs native reservoir fluid well influx, affecting flow patterns inside the well and well pressure. The objective being tracked is operating under desired pressure levels, which assures process safety, also reducing costs. In this scenario, modelling techniques are important tools for narrow operational windows, commonly observed at deepwater and pre-salt layer environments. The major objective of this paper is real time building and comparing model performance for predicting annulus bottom hole pressure, using real time flow, choke index and ROP (rate of penetration) data, available from a drilling site. Neural Network (NN) based models were used successfully for on-line identification purposes, using an adaptive methodology. The proposed methodology can be employed at drilling sites, through the use of PWD (Pressure While Drilling) and mud-logging tools, providing real time data and helping operators to make important decisions concerning safety of the drilling process.
url https://www.cetjournal.it/index.php/cet/article/view/7479
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