A New General Optimization Method - Application to Gas Gathering System

Abstract

Discussion of this paper is invited. Three copies of any discussion should be sent to the Society of Petroleum Engineers office. Such discussions may be presented at the above meeting and, with the paper, may be considered for publication in one of the two SPE magazines. Abstract The object of this paper is to present a new optimization method developed for problems concerning operating policy in oil or gas fields. Several mathematical procedures have been used, but none permits the handling of problems that are, at the same time, nonlinear, problems that are, at the same time, nonlinear, discrete and submitted to constraints. The method proposed here is based on probability concepts, and the algorithm probability concepts, and the algorithm described is shown to converge, in probability, to the optimal solution. An example of a gas-gathering system optimization illustrates the method. This example seems appropriate as it is similar to many exploitation problems. Indeed, most of them are nonlinear (friction losses, as an example), discrete (such as connecting point locations and pipe diameters), submitted constraints (pressures at wellheads and fluid speed in flow lines). The computing efficiency of the method is then tested. Introduction While, in every industry, decision problems are important, this is certainly most evident in the oil- or gas field development strategy where almost always, the "best policy" must be at the very beginning, despite the small amount of available information. The various decisions to be made relative to the development or abandonment of a field, on the basis of a very small number of exploration wells, are far from obvious. In practice, all operational aspects are concerned. It is not sufficient to search for a technical-economic optimum by successive trials without taking all variables into account. The following examples require particular accuracy in calculations that is not always reached:well drilling schedules and well locations during field life,design and construction of a gas-gathering system andcompressor positions and required power, if necessary. Several methods have already been developed, but their mathematical limits have forced users to simplify their problems. A general optimization method is presented here. It will be seen that the described algorithm converges to the best technical-economic decision or "optimum decision" in a probability sense. It is applied to the development of a gas-gathering system in the case of a dry gas field.