Recent volatility in natural gas liquid (NGL) frac spreads and NGL pricing has only underlined long-recognized challenges for gas processors. To stay competitive, operators need agility to respond swiftly to market demands and pricing. They have to achieve the right product mix between NGL and natural gas—and often the best NGL mix (between C2 and C3, for example) as well.

It is a trick some pull off more successfully than others. Arguably, however, most make it more difficult than necessary. While it is widely used and well-proven in the hydrocarbon- processing industries, multivariable predictive control (MPC) has seen poor uptake among gas processors. That’s despite the fact that it has a good return on investment (ROI) and is perfectly suited to the challenges involved in enabling owners and operators to respond quickly to market demands. The payback on MPC investments is proven to be attractive—some provide an ROI of less than a month.

MPC creates the tools to design, implement and maintain multiple-input/multiple-output applications that drive processes to maximum economic benefit.

A more agile operation

Gas processors’ operating objectives depend on the type of contract under which they operate. Fee-based contracts seek to maximize throughput volumes. Percentage of proceeds (POP) contracts incentivize processors to cut operational costs, and keep-whole contracts promote NGL yields optimization. Contracts may be a mix of different types, and here the operating objectives will change in response to market demands. It is important to optimize the operations to not only maximize the throughput volumes but also the most valuable products.

The task is made more difficult by volatility in frac spreads and NGL pricing, which are both likely to be here to stay: Shale gas production activities and overall global supply and demand dynamics essentially guarantee it. MPC, however, potentially offers an answer. It allows operators to optimize the process in response to changing economics by improving management of the multiple process constraints they operate under.

For gas plants, there are both tangible and intangible benefits.

The MPC technology results in quantifiable increases in production of valuable products, energy savings, better product quality and reduced process variability, especially in the face of significant feed disturbances, rates or composition. Based on reference MPC installations in the gas processing industry, users can expect throughput increases of 3% to 5%, recovery improvements of highermargin products exceeding 2% in both fractionators and splitters and utility consumption cut by up to 10%.

The less tangible benefits are mainly found in an improved ability to respond to market changes and a shift from chasing alarms to unit optimization.

In practice, actual benefits and value from the MPC applications depends on the plant and type of operation. The biggest impact is usually in increased production, and gas plants operate in two distinctly different operating modes— maximizing liquids and propane production from the liquids; and maximizing sales-gas production rates, subject to the quality specifications. Each mode faces a different set of constraints.

However, MPC does allow the operator to make the switch between the two operating modes more easily and quickly, with minimal loss of production or quality.

Overall, the payback period for an MPC application is usually about six months, but varies widely depending on the type of contract and market dynamics. It may be as much as a year, but it can be as little as a few weeks.

MPC deployment

Deployment typically includes a project kick-off meeting, controller design, step testing to develop controller models and implementation of the controller. During the kick-off meeting, the teams collect the data and have detailed discussions with operations personnel and other key stakeholders regarding the expected goals of the final application.

Two, most-critical steps in the deployment are controller design and developing the controller models for the MPC. The controller design is meant to capture the key operating relationships, including constraints, and should be in line with the operating objectives of the plant. The controller design is the basis for the configuration of the MPC application and sets the manipulated variables (handles to change) and controlled variables.

Controller models are the relationships (steady-state gains, process dynamics) used by the MPC application to control and optimize the operations. Traditional MPC technologies require invasive step testing of the unit. But there are technologies available in the market, such as Honeywell Profit Controller Express, that can allow a bypass of these step tests to develop the required model. In such cases, necessary information to develop the controller models can be obtained using a combination of any available steady-state process simulation model, historical data and use of “bump test.” Bump testing includes making enough process change to validate the steady-state gains derived from any of the sources mentioned above.

The MPC deployment typically takes three months from the project kick-off to completion of controller commissioning. Duration will drop with experience and subsequent projects. For example, in a recent roll-out program for a customer involving multiple sites, the initial application took approximately three months to implement, and after four projects, this duration was down to two to four weeks.

Getting it right

Several factors heavily impact the effectiveness of MPC and help determine that payback period. Plant characteristics, such as age, have a significant impact where the infrastructure such as valves and instrumentation need to be working well and regulatory control needs to be well-tuned.

Operator input is essential at the controller-design stage to ensure the design accurately reflects the operating objectives of the plant and captures the key constraints. Similarly, close engagement is required after deployment—on-the-job training will be needed for in-house engineers and support functions and for board operators. There should also be ongoing communication with operators, as well as a commitment to review data performance regularly, throughout the life of the application—focus on monitoring!

Finally, control should be focused on what makes the most money. Only install what’s needed to control the key variables to achieve that objective. This is the purpose of being able to set the objective within the controller: If there is a change in the process or market, the plant is able to adjust the priority of the controller based on the most economical outcome, or even tie the controller directly to the pricing of the components (if the component prices are available), to adjust automatically to changes.

Nevertheless, plants should be sure not to ignore energy savings or the point that operating parameters and requirements change. If gas operators should know anything, it is that they operate in a dynamic environment.

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