Driving Value Using Closed Loop Optimization Technology At the Williams Ignacio Plant

Presented with Williams Midstream 2007 National GPA Meeting

John Ritter and Davis Begay Williams Midstream Durango, Colorado U.S.A.

James Jones, Steve Hendon, Mark Darby, and Mark Roop eSimulation, Inc. Houston, Texas U.S.A.

ABSTRACT Williams Midstream is one of the largest gatherers and natural gas processors in the San Juan Basin of Colorado and New Mexico. Williams Midstream operates 5 gas plants in the region with the combined capacity to process approximately 750 million cubic feet per day and treat an additional 760 million cubic feet per day. The Ignacio Processing Plant, near Durango, CO is a large, complex facility with a design processing capacity of 450 million cubic feet per day. Operations at Ignacio are closely coordinated with operations at the Milagro Treating Plant, 50 miles away, to maximize efficiency.

In 2005, Williams Midstream selected closed-loop process optimization technology to improve the profitability of the Ignacio Processing Plant. This paper will outline some of the operational challenges associated with managing the Ignacio facility, and with coordinating Milagro volumes and will discuss how closed-loop optimization was identified as a viable option for helping Williams to address these challenges. The methodology employed to justify the project for AFE purposes will be described.

The Ignacio closed-loop optimization system was commissioned in 2006. The system includes two primary technology offerings:

• eSimulation’s eSimOptimizerSM on-line economic / process optimization system applied to a large scope gas processing plant, including a cryogenic gas plant, product fractionation facility, power generation and LNG production

• Multivariable predictive control technology to smooth process upsets and to achieve and maintain the operational targets developed by the eSimOptimizerSM system.

Lessons learned from deploying both of these technology offerings will be discussed. The results of a performance test on the multivariable controller will be presented. Finally, the value methodology used for the benefits assessment will be summarized.

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