American Institute of Mining, Metallurgical, and Petroleum Engineers, Inc.
This paper was prepared for the 46th Annual Fall Meeting of the Society of Petroleum Engineers of AIME, to be held in New Orleans, La., Oct. 3–6, 1971. Permission to copy is restricted to an abstract of not more than 300 words. Illustrations may not be copied. The abstract should contain conspicuous acknowledgment of where and by whom the paper is presented. Publication elsewhere after publication in the JOURNAL OF PETROLEUM TECHNOLOGY or the SOCIETY OF PETROLEUM ENGINEERS JOURNAL is usually granted upon request to the Editor of the appropriate journal provided agreement to give proper credit is made.
Discussion of this paper is invited. Three copies of any discussion should be sent to the Society of Petroleum Engineers office. Such discussion may be presented at the above meeting and, with the paper, may be considered for publication in one of the two SPE magazines.
This paper presents new network simulation algorithms that:
drastically affect the formulation of network problems,
permit the simulation of very large networks,
afford large savings in computing cost. These algorithms may be used as computational aids to the design, evaluation, and operation of natural gas gathering, transmission, and distribution systems.
The first algorithm applies to networks without flow circuits. Its designation "CINS - I", is an acronym for Converging Information Network Simulator. The second algorithm is a modified version of CINS - I, designed to simulate networks with few flow circuits. Its acronym is "CINS - II". The third algorithm is a combination of CINS -I and the Newton-Raphson Method, which is used for very large multi-circuit networks. It is called "GINS", which is the acronym for General Information Network Simulator. The power of the CINS algorithms stem from the circumvention of matrix manipulations normally encountered in network simulation. GINS is designed to greatly reduce the size of the matrices required in the Newton-Raphson Method and to exploit the sparseness of the reduced matrices. Several applications of the algorithms to typical gas networks are also given.
The gratification of a modern society is deeply imbedded in a maze of networks which, among other things, collect and disseminate information, transport people, and distribute goods and energy. The enormous investment in and dependence on these networks demand that existing ones be rationally used and the new ones intelligently planned.
"A typical approach to a current decision making problem (i.e. a network design and/or operating decision) is to allow intuition, experience and current knowledge to dictate the selection of factors to be considered. There are some indications that good intuition is a manifestation of the correct mix of factors".