Title: Smart well zonal allocation
1Smart well zonal allocation
2The Problem
- To run smart wells at its optimum level it must
be possible to determine the zonal reservoir
pressure at any time and compare those with the
theoretical expected pressure calculated from
your well and network models. A comparison of
the theoretical value with the actual calculated
value is a key performance indicator if the
well/reservoir behaved as expected. If not the
system needs to be recalibrated.
3The Team
- IP21 by Aspentech is the data historian
- EnergyComponents by TietoEnator is the
production database - Prosper by Petroleum Experts is a Well modelling
application - DECIDE! By Schlumberger is the orchestrator of
automated workflows and data consolidation - Avocet Production Surveillance by Schlumberger is
the visualization tool - Avocet - Integrated Asset Modeller (IAM) by
Schlumberger is the optimizer and forecaster
4The Workflow
- The integrated asset model will consume
historical production and injection data to
calculate production and injections targets
(forecast). - Those targets will be used to in the consolidator
to compare the targets to the actually achieved
values - The measured temperature and pressure at each
zone (downhole sensor data available via data
historian) will be used to calculate zonal and
total rates and to calculate the reservoir
pressure per zone - The reservoir pressure and rates can be used in
an advanced process controller to calculate the
optimum choke setting on how to operate the well
within the targets and the constraints.
5The interactions
9
13
PETEX Prosper/GAP
APS
8
7a
7b
4
Decide!
10
1
14b
IAM
12a
12b
14a
3b
3a
2b
6b
2a
6a
5b
11b
Advanced Process Control
5a
11a
11
TE EnergyComponents
Aspentech IP21
6Setup the IAM model
7Set PI Targets
8Create new PRODML connection
9Point to TietoEnators web service
10Define the well(s) to query for
11Define the parameter(s) to query for
12View resulting query and response
13View data that is to be acquired
14and acquire it to DECIDE!
15Create new PRODML connection
16Point to Aspentech web service
17Select the well(s) to query for
18Define the parameter(s) to query for
19View query template and results
20View query template and results
21Optionally data cleansing rules to the data
22View resulting data that will be acquired
23Finish initial data acquisition
24This connection can than be automated
25in a DECIDE! workflow
26Advanced Process Control
New IAM data (5 Increase)
Sample
180
185
190
195
200
290
295
300
305
New velocity limit
27The web viewer can visualize the acquired data
28and the calculated pressures
29Calculated KPI for monitoring the performance
30Rerun optimization if performance declines