Chacon_subbed.qxp 30/3/09 10:04 Page 138
Advanced Techniques for Realtime Well Surveillance
Communications
a report by
&
Joel Chacon-Fonseca
1
and David Parsons
2
1. Well Performance Monitor Solutions Manager; 2. Solutions Business Manager, Matrikon Europe Ltd
IT
Accelerating production from oil- and gas-producing fields and intimate knowledge of data historians, supervisory control and data
minimising operating costs is of renewed interest in the current economic acquisition (SCADA) systems and distributed control systems (DCS)
climate: anything that improves cash flow is likely to be welcomed by and is vendor-independent with regard to connecting to these
engineers and managers alike. Well performance monitoring enables systems. This means for a complex asset or assets with different DCS
production engineers to optimise average well production rates by being and/or SCADA systems, Matrikon’s solutions represent a unifying view
able to quickly pinpoint issues and initiate corresponding actions in less on asset performance.
time than previously required, thus minimising deferred production and
at the same time gaining valuable insight into field issues. Process Data Cleansing and Filtering
Realtime data are pre-processed with a proprietary set of algorithms
Based on ‘cleansed’ realtime measurements and updated well (known collectively as data cleansing) in which all non-natural realtime
performance curves, Matrikon™ Well Performance Monitor (WPM) signal values are removed. Realtime process data often contain
calculates a well’s operational parameters and presents results for an inherent quality problems, either because of faults within the different
entire field using a visualisation technique that allows for rapid systems and system interfaces (e.g. from the signal transmitters up to
identification of production losses or well instability. Users intuitively drill the process historians) or due to noise introduced by measurement
down to access process variable trends and schematic displays that are methods and the nature of the process. These data quality problems
presented in the context of the well as part of a field-wide hierarchy. manifest either as flat-lines or missing data (e.g. caused by poor system
interconnectivity or signal drop-out) or as noise (e.g. caused by the
This article presents the steps and approaches undertaken by WPM that movement of offshore structures introducing noise into otherwise
allow users to optimise well performance. These include: stable level measurements).
• process data cleansing and filtering; The conventional approach to noise reduction has been traditional
• identification of well ‘mode’; filtering techniques, but it is well known that these introduce delays
• estimation of realtime well rates; and distortions in the behaviour of the process signal, masking one of
• identification and computation of well capacity and key the most important features of realtime data: the pattern of behaviour
performance indicators (KPIs); and of the realtime trend. The simplest traditional filtering technique –
• presentation of aggregate results (well group, field, asset) – averaging – works on the assumption that an average calculation will
visualisation. cancel any disturbances or unwanted noise (which will effectively be
true when dealing with zero-mean noise). However, averaging process
WPM is rapid to deploy, easily scaleable to many hundreds of wells data can mask features that can be quite important: the dynamic
and delivers a rapid return on investment for field operators. It process characteristics.
provides a web-based view of all wells, whose visualisation can be
customised to reflect the user’s interest, e.g. well rate and/or well KPI. In this context, the ideal process data cleansing ‘filter’ would remove
As the world’s largest supplier of OPC connectors, Matrikon has any non-natural process signal values without affecting the normal
pattern and dynamics of any legitimate process data variation. This
data cleansing methodology is used by WPM to provide the most
Joel Chacon-Fonseca is Well Performance Monitor
Solutions Manager at Matrikon Europe Ltd.
accurate picture of well performance. Cleansed data are written back
Previously, he worked in the Automation Department
to the process historian so they can be accessed by all realtime data
of Lagoven, later PDVSA, in Maracaibo, Venezuela.
consumers and data visualisation users. Using the cleansed data,
He holds a BSc in electrical engineering and an MSc
in electrical engineering–systems from the University certain calculations and behaviour estimates are performed by the
of Southern California.
system to aid in the detection of changes that could be considered
E: wpm@matrikon.com potential production losses or well problems. All well analyses are
based on cleansed data. When realtime process signals are used for
David Parson is Solutions Business Manager at
Matrikon Europe Ltd, with particular research interests
online calculations, it is essential to ‘cleanse’ the data in order to
in process modelling and optimisation. He is a achieve trustworthy realtime calculations and intelligent alarming.
member of the Society of Petroleum Engineers (SPE).
A Chartered Chemical Engineer, he has a BSc in
chemical engineering from the University of Bradford.
Identification of Well Mode
A well’s mode is identified as stable, unstable or shut-in based on
pre-configured rules. For example, if the well’s choke valve is open, the
well may be in either stable or unstable mode: it will be identified as
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