OPTIMIZATION OF NATURAL GAS GATHERING SYSTEMS AND 

GAS PLANTS 

Keith A. Bullin, P.E. 

Bryan Research and Engineering, Inc. 

Bryan, Texas, U.S.A. 

Jason Chipps 

Bryan Research and Engineering, Inc. 

Bryan, Texas, U.S.A. 

ABSTRACT

Due to the increase in natural gas prices in the past few years, the benefits of 

optimizing natural gas gathering and processing systems have become substantially 

greater. These benefits can be observed from an analysis of the operating conditions, 

updating gas contracts, and adding gas to existing systems when excellent opportunities 

exist. 

A new technique has been developed to accurately model gas processing systems 

to incorporate an economic simulation with the process simulation. This new technique 

utilizes an Excel interface with process simulation software to include economic factors 

with the simulation results. As a result, an extended analysis of the operating conditions 

of the facility as well as the economic conditions can be simultaneously combined to 

provide a complete model of the system. This methodology can be extended to include a 

parametric study of the available process and economic variables. Excel solvers may also 

be used to generate the economic optimum set operating conditions. 
INTRODUCTION 

Process simulation has been traditionally used to troubleshoot and maximize the 

performance of gas processing facilities. Economic considerations are often performed in 

spreadsheets disconnected from the process simulation model. As a result, economic 

models cannot be easily combined with the process model. In many instances, one 

person handles the day to day plant operations and uses the process model while the 

person who negotiates gas contracts uses the economic model. A new technique has been 

developed to combine the process and economic models in a seamless format which 

gives economic insight to general process simulation problems. 

Once the two models are connected, process changes will be automatically 

reflected in the economics. Parametric studies or solvers may be utilized to determine the 

overall economic picture, but it is helpful to review the important drivers for the process 

and economics. 

IMPORTANT FACTORS FOR GAS GATHERING AND PROCESSING 

SYSTEMS 

 Natural gas gathering systems are a unique product of continual changes from the 

addition and depletion of wells. Some gathering systems contain spare capacity from 

fields which never developed. Other gathering systems are pushing capacity constraints 

from fields which exceed expectations. As a result, modeling gas gathering systems is an 

art which can have many forms. Some of the major factors for consideration from both a 

process and economic perspective are shown below: 

Pressure Drop / Compressor Fuel - Increased gas density at higher pipeline operating 

pressures allows for more gas to travel through a given line size. Higher pressure drops 

directly contribute to increased compression fuel costs. 

Liquids in Pipelines - Produced gas generally enters the pipeline near its dew point. As a 

result, cooling of the gas through the gathering system can create liquids in the pipeline. 

These liquids can collect in low spots and increase the pressure drop through the pipeline. 

The value of the pipeline liquids may be significant. 

 A second source of potential liquids occurs when the gas is compressed and 

cooled. These liquids present challenges because they may not be stable at atmospheric 

pressure, but they need to be removed prior to a second stage of compression. 

Wellhead Pressure - Many gas gathering systems require a low pressure at the wellhead 

to facilitate production. This can become a constraint for the operation of gathering 

systems. 

Gas Contracts - The gas gathering contracts may have many forms including fees for 

compression, treating, or gathering. Many gas contracts operate on a percent of proceeds 

after processing. Gas collected by gathering systems may also have a mixture of 

ownership and contract terms. 
Product Prices - The sales price of gas and liquid products is one of the most important 

factors in optimizing gas gathering and processing facilities. Historic price information is 

compiled on the Barnes and Click website1

. 

GENERAL APPROACH FOR OPTIMIZATION 

Traditional methods for optimizing gas process facilities are quite complex2. 

These methods incorporate simplified process calculations in order to combine 

economics and process simulation techniques. An example simplification is the use of 

the Underwood3

 method for separation of the light and heavy key components. All other 

components are not considered in the distillation. Sophisticated numerical techniques are 

required to complete the process model such as the method proposed by Box4

. 

Significant improvements in optimization evolved with the additional capability 

of process simulation programs to imbed an Excel workbook or other spreadsheet type 

application. With the addition of spreadsheets in process simulation models, the general 

approach is quite easy; link an Excel workbook to a process simulation program and 

transmit values back and forth. A process or pipeline facility can be modeled rigorously 

with the process simulation portion while the economic model can be set up in Excel. 

ProMax® was selected as an example for the application of this technique due to its ease 

of integration with Excel. An example of the importing and exporting feature is shown 

below in Figure 1. The following example illustrates this concept. 

Figure 1: Importing and Exporting Values to an Imbedded Excel Workbook 
OPTIMIZATION OF A NATURAL GAS GATHERING SYSTEM WITH A 

PROCESSING PLANT 

In many instances, the operator may include the gas gathering and processing 

under one contractual arrangement. As a result, the gas processing facility must be 

included in the overall analysis. In this example, 50 MMSCFD of 10.8 GPM gas enters 

an existing 20 mile pipeline at 35 psig. The gas is field compressed to achieve 100 psig 

at the plant gate as shown in Figure 2. Up to 25 MMSCFD of additional 7.2 GPM gas is 

available. The pipeline transports and processes the gas under a fixed fee arrangement 

($0.25 per MCF) and the gas owner pays for the fuel. 

The plant inlet compression system compresses the gas to an operating pressure of 

between 800-900 psig and separates the methane from the heavier hydrocarbon products 

as shown in Figure 3. This figure also identifies several key parameters which 

significantly affect the operational efficiency and economics of the plant. These 

parameters are the inlet pressure, amount of inlet split for reflux to the column, the 

demethanizer pressure, the reboiler duty, and the chiller duty. The residue gas from the 

plant is recompressed to 700 psig for pipeline injection. The demethanized liquid is sold 

as a Y-grade product at $0.55 per gallon. The residue gas value is $ 5.50 per MMBTU. 

The plant charges small pipeline and marketing fees. 

Figure 2: Gas Gathering and inlet Compression System 
Figure 3: Expander Plant with Key Operating Parameters Identified 

An Excel economic model was used to represent the economics for the gathering and 

processing facility. This spreadsheet was linked to a process simulation of both the 

gathering a processing facility simultaneously. Table 1 lists the parameters residing in 

Excel and shared with the process simulation. These parameters significantly affect the 

plant operation. Table 2 identifies the parameters calculated by the process simulation 

and shared with the Excel model. 

Table 1: Parameters which reside in Excel and Shared with the Process Simulation

• Plant Inlet Pressure 

• Percent Split for Reflux to the Top of the Column 

• Chiller Outlet Temperature 

• Demethanizer Pressure 

• Reboiler Duty 

Table 2: Parameters Calculated by the Process Simulation and Shared with Excel

• Residue Composition and Flow 

• Liquid Product Composition and Flow 

• Compressor Energy Requirements 

• Reboiler and Chiller Energy Requirements 

Upon completion of the linkages, various process and economic factors were investigated 

as shown graphically in Figures 4-9. 

The gross plant profit is shown in Figure 4 with variations in the reflux split. 

Splits from 22.5-30% yield the best results. There is a small benefit to operating at an 

optimal value of 25%. 
23,500

23,750

24,000

24,250

24,500

0 5 10 15 20 25 30 35

Split for Reflux to Column (%)

Gross Plant Profit ($/Day)

No New Gas

Figure 4: Plant Profit without New Gas for Variations in Reflux Split 

The new gas stream is leaner containing 7.2 GPM compared to the 10.8 GPM 

existing gas stream. Figure 5 shows ethane recovery fluctuations with reflux splits from 

10-35%. The plant will operate at better recoveries with the addition of the new gas. 

75

80

85

90

0 10 20 30 40

Split for Reflux to Column (%)

C2 Recovery (%)

With 25MMSCF

New Gas

Without New Gas

Figure 5: Plant C2 Recovery with/without New Gas 

Figure 6 shows the demethanizer pressure effects on plant profitability with 

demethanizer pressures from 180-220 psig. The optimum for the percentage of liquids 

scenario is the lowest demethanizer pressure. The lowest demethanizer pressure yields 

the greatest change in pressure through the expander and generates the coldest 
temperatures and best recovery. Since the plant does not have to pay for fuel in this case, 

the additional fuel required for recompression does not affect the economics. If the plant 

is processing the new gas under a keep whole arrangement, recompression costs are 

important and favor operating the demethanizer at higher pressures. 

30,000

35,000

40,000

45,000

50,000

150 175 200 225 250

Demethanizer Pressure (psig)

Gross Plant Profit ($/Day)

Plant Keeps 15%

Liquids

Plant Processes

Keep Whole

Figure 6: Demethanizer Pressure Influence on Plant Profitability 

The economic response to changes in the inlet pressure is shown in Figure 7. 

Higher inlet pressures are optimal for keep whole processing despite the added fuel costs 

32,750

33,000

33,250

33,500

780 800 820 840 860 880 900 920

Inlet Pressure (psig)

Gross Plant Profit ($/Day)

Plant Processes

Keep Whole

Figure 7: Inlet Pressure Influence on Plant Profitability with Keep Whole 

Processing 
The inlet pressure effect on the plant profitability with a percentage of liquids 

contract shows a similar response to that of the keep whole contract as shown in Figure 8. 

Higher inlet pressures contribute to increased liquids recovery. 

44,000

44,250

44,500

44,750

45,000

780 800 820 840 860 880 900 920

Inlet Pressure (psig)

Gross Plant Profit ($/Day)

Plant Keeps 15%

Liquids

Figure 8: Inlet Pressure Influence on Plant Profitability with Percent of Liquids 

Processing 

The amount of new gas was varied with different contract scenarios as shown in 

Figure 9. The plant receives the smallest amount for processing the gas at the same $0.25 

per MCF gathering and processing fee. At current price levels, the keep whole 

processing arrangement is only marginally better. The best scenario is to process the gas 

while retaining 15% of the liquids without charges for fuel. 
25,000

35,000

45,000

0 5 10 15 20 25 30

Amout New Gas (MMSCFD)

Gross Plant Profit ($/Day)

Plant Keeps 15% Liquids

Plant Processes Keep Whole

Fixed Gathering and

Processing $0.25/MCF

Figure 9: Plant Profitability with Different Contracts for the New Gas 

In summary, the technique of combining a process simulation with an Excel 

representation of the economics can be very helpful in predicting plant economic 

performance. This technique must be reapplied periodically for changes in the gas, 

product prices, and contracts. 

Literature Cited 

1.) www.engineers1.com (Barnes and Click Website) 

2.) Bullin, Keith A. “Economic Optimization of Natural Gas Processing Plants 

Including Business Aspects.” Ph.D. Dissertation. Texas A&M University. 1999. 

3.) Underwood, A. J. V. “Fractional Distillation of Multicomponent Mixtures.” 

Chem. Eng. Prog., 1948, 44, 603. 

4.) Box, G. E. P., Hunter, W. G., and Hunter J. S. Statistics for Experimenters. New 

York: Wiley Series in Probability and Mathematical Statistics, John Wiley & 

Sons, Inc., 1978.