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Advanced Techniques for Realtime Well Surveillance
Figure 3: Example of an Overview Display Map
information to calculate the desired or theoretical parameter. Example
KPIs include:
• gas–liquid ratio (GLR), with an ideal value of 1,000 standard cubic
feet (scf)/stock tank barrels (stb);
• injected gas–oil ratio (IGOR);
• oil capacity/gas-lift ratio, to compare a well’s effective gas-lifting
efficiencies; and
• model confidence, a measure of the deviation between different
well rate estimation methods.
Presentation of Aggregate Results – Visualisation
All of the information gathered by WPM is summarised in a 2D map
showing all of the wells in each facility, area or field. Each well is
represented by a block whose size and colour can be mapped to
different well-based variables or indices. The default map of the system
displays the size as proportional to the well’s oil capacity and the colour
Figure 4: Schematic of the Well Showing Latest Realtime Measurements
as the well performance KPI explained above. The bigger blocks
(automatically grouped in the top-left corner) are the most important
P1 schematic
wells, and the ones tending towards red are those producing
0.00%
considerably below capacity, as shown in Figure 3. The map is easily
Gas-lift rate:
customisable to suit specific user requirements. Clicking on each well
Annulus: 0.00MMscf/day
block allows the user to drill down to well-specific schematics displays
0.00 BARa
Gas lift
and trends that can be used to perform more in-depth analyses on the
Upstream of choke:
behaviour of each well, as illustrated in Figures 4 and 5.
94.05 BARa
132.31ºC
73.00%
Downstream of choke: Conclusions
13.67 BARa
132.31ºC
The system is highly configurable and scalable to increasing demands
Facility
for the higher-level analyses expected by more sophisticated users;
for example:
Down-hole:
Production rate:
4.59 KPSI
Est. oil rate: 4,346.1STB/day
248.86ºF
Mode: unstable
• intelligent alarming to warn of failure modes characterised by
changes in realtime operating conditions;
Figure 5: Typical Surveillance Trend, in this Case to Monitor the
• realtime performance maps, where the operational point is seen
Behaviour of the Gas Lift System
historically and dynamically in the well performance curve plane; and
• extensions into production operations workflows such as executing
and analysing well tests and requesting well work-overs.
The system combines information from multiple sub-systems,
including the realtime database, relational databases and the well
model files, to produce a single vision of the field in which deviations
from either expected or planned behaviour can be rapidly identified
and analysed.
Field operations have access to realtime well measurements on their
desktop, enabling realtime well surveillance. Problematic wells (i.e.
wells that are not performing as calculated well performance curves
predict) can be quickly identified and analysed, either determining the
necessary action to correct the well’s performance or focusing
attention on the underlying models used for calibration and validation.
an invalid well model, production conditions varying significantly from
expected conditions or an unexpected change in WC. In any case, the Asset management teams can monitor cumulative performance (i.e.
KPI serves as a surveillance index for all wells. WPM allows any number summations of the realtime data) versus production plans, allowing
of such KPIs to be computed, limited only by the availability of the for rapid identification of potential shortfalls and corrective action to
necessary realtime data and the availability of the necessary be taken. ■
1. Halmøy R-H, Verhelst F, Dueñas Díez M, et al., Use of Watering Out on Troll, SPE 112131, presented at the 2008 Amsterdam, 25–27 February 2008.
Agent Structures for Event Detection: Identification of Wells SPE Intelligent Energy Conference and Exhibition in
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