Page 278 - Petroleum Production Engineering, A Computer-Assisted Approach

Guo, Boyun / Computer Assited Petroleum Production Engg 0750682701_chap18 Final Proof page 278 4.1.2007 10:04pm Compositor Name: SJoearun

18/278 PRODUCTION ENHANCEMENT
Table 18.3 Gas Lift Performance Data for Well A and Well B
Oil production rate (stb/day) Slope of performance curve (stb/MMscf)
Lift gas injection rate (MMscf/day) Well A Well B Well A Well B
0.6 0 740 242 850
1.2 145 1,250 150 775
1.8 180 1,670 54 483
2.4 210 1,830 46 142
3 235 1,840 33 13
3.6 250 1,845 17 6
4.2 255 1,847 8 0
4.8 259 1,845 4 56
5.4 260 1,780 3 146
6 255 1,670

Table 18.4 Assignments of Different Available Lift Gas Injection Rates to Well A and Well B
Gas injection rate Slope of performance Lift gas Gas injection rate
before assignment curve assignment after assignment
(stb/day) (stb/MMscf) (MMscf/day) (stb/day)
Total lift gas
(MMscf/day) Well A Well B Well A Well B Well A Well B Well A Well B

1.2 0 0 242 850 0 1.2 0 1.2
1.8 0 1.2 242 775 0 0.6 0 1.8
2.4 0 1.8 242 483 0 0.6 0 2.4
3 0 2.4 242 142 0.6 0 0.6 2.4
3.6 0.6 2.4 242 142 0.6 0 1.2 2.4
4.2 1.2 2.4 150 142 0.6 0 1.8 2.4
4.8 1.8 2.4 54 142 0 0.6 1.8 3
5.4 1.8 3 54 13 0.6 0 2.4 3
6 2.4 3 46 13 0.6 0 3 3

7. Construct a computer model for the flow network. A key feature of ReO is that it is both a production
8. Validate equipment models for each well/equipment in simulation and an optimization tool. Simulation deter-
the network by simulating and matching the current mines the pressures, temperatures, and fluid flow rates
operating point of the well/equipment. within the production system, whereas optimization deter-
9. Validate the computer model at facility level by simu- mines the most economical production strategy subject to
lating and matching the current operating point of the engineering or economic constraints. The economic mod-
facility. eling capability inherent within ReO takes account of the
10. Validate the computer model at field level by simulat- revenues from hydrocarbon sales in conjunction with the
ing and matching the current operating point of the production costs, to optimize the net revenue from the
field. field. The ReO Simulation option generates distributions
11. Run simulations for scenario investigations with the of pressure, temperature, and flow rates of water, oil, and
computer model if a simulation-type program is used. gas in a well-defined network. The ReO Optimization
12. Run optimizations with the computer model if an option determines optimum parameter values that will
optimization-type program is used. lead to the maximum hydrocarbon production rate or
13. Implement the result of optimization with an open- the minimum operating cost under given technical and
loop or closed-loop method. economical constraints. ReO addresses the need to opti-
mize production operations, that is, between reservoir and
facilities, in three main areas:
18.8.4 Production Optimization Software
Commercial software packages are available for petroleum . To aid in the design of new production capacity, both
production optimization at all levels. Field-level optimiza- conceptual and in detail
tion can be performed with ReO, GAP, HYSYS, FAST . To optimize production systems either off-line or in real
Piper, among others. This section makes a brief introduc- time
tion to these packages. . To forecast performance and create production profiles
for alternative development scenarios
18.8.4.1 ReO ReO integrates complex engineering calculations, practical
The software ReO (EPS, 2004) is a compositional produc- constraints, and economic parameters to determine the
tion simulator that can simulate and optimize highly non- optimal configuration of production network. It can be
hierarchical networks of multiphase flow. Its optimizer employed in all phases of field life, from planning through
technology is based on sequential linear programming development and operations, and to enable petroleum,
techniques. Because the network is solved simultaneously production, facility, and other engineers to share the
rather than sequentially, as is the case for nodal analysis same integrated model of the field and perform critical
techniques, the system can optimize and simulate account- analysis and design activities such as the following:
ing for targets, objectives, and constraints anywhere in the
network. . Conceptual design in new developments