Oilfield Power: Technology and Cost Control
- V.L. Pellegrino (Amoco Production Co.) | G.T. Scott (Amoco Production Co.)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- April 1989
- Document Type
- Journal Paper
- 389 - 393
- 1989. Society of Petroleum Engineers
- 4.1.6 Compressors, Engines and Turbines, 7.4.4 Energy Policy and Regulation, 4.3.4 Scale, 4.1.4 Gas Processing, 4.6 Natural Gas, 4.1.7 Electrical Systems
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The oil producers of today consume significant quantities of electricity to maintain oil production. Production companies now find that high electricity costs are not supported by relatively low product prices, thus leaving operators scrambling to control costs that have not been aggressively controlled in the past. Producing companies have been ineffective in implementing oilfield power technology and cost control because of the widespread nature of oilfield operations.
This paper deals with a very successful power-technology-enhancement and cost-control program that has allowed producing operations to control and to reduce electric-power costs. The power technology available to producing operators and examined in this paper includes cogeneration, electric substations, computer modeling of electricity distribution systems, computer automation of power consumption, and regulatory intervention.
The program was created to reduce and to control the cost of electric power on a per-unit basis rather than to reduce the actual quantity of electric power. With existing energy-conservation programs in place, the program's goal is to reduce electricity costs by securing electricity at the lowest cost through purchases or power generation.
Amoco Production Co. began emphasizing the program strongly in 1984. Fig. 1 shows the total annual cost of electricity for operations in Texas and eastern New Mexico and the annual savings as a result of the cost-reduction program. The lower portion of the bar chart shows the actual cost of electricity as paid to various public utilities, which increased 50% from 1984 to 1988. The top portion of each bar is the savings generated by the cost-reduction program or, if viewed differently, the amount that would have been paid for electricity if the cost-reduction program had not been in effect. The electricity demand increased from 130 MW in 1984 to 207 MW in 1988, a 60% increase. The power-cost-reduction program provided an 8.5 % reduction in costs in 1984, and the reduction increased steadily to approximately 15% in 1988. Although electricity usage has increased significantly, the power-cost-reduction program has helped minimize cost increases by reducing the cost of purchased power on a per-unit basis.
The annual savings are achieved through the many different technologies described in this paper. The contributions of each power technology are divided into four major groups, shown in Fig. 2: cogeneration/power generation, electric substations, system optimization modeling and automation, and regulatory intervention/contract renegotiation.
For 1986, our cogeneration and power-generation projects provided a $3.8-million reduction in electric-power costs and comprised 51% of the total program savings. Electric substations produced 40% of the total program savings--$3.1 million. System optimization and regulatory intervention/contract renegotiation contributed 9% or $0.7 million to the overall impact of the program.
Data Acquisition and Management
The ability to implement new technology to produce electricity cost savings depends largely on the ability to identify the areas of greatest potential savings. The first step involves determining the monthly electricity bill for each field or producing unit. Obviously, the field operations personnel will know the total monthly electricity bill, but often will not know the individual monthly bills for nearby fields or whether electric power is being purchased under the best possible rate schedule. A computer data-storage and -retrieval system should be used to enter the monthly electricity billing data. The data base will then provide immediate access to the billing data for any specific location. The billing data typically include total cost, electricity demand in kilowatts, energy consumed in kilowatt-hours, and power factor, all of which are listed on the monthly electricity bill.
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