With current trends towards intelligent wells and fields, continuous bottomhole well pressure monitoring is becoming the norm in new field developments. Theoretically, this should allow operators to better control well performance and address problems before they become irreversible. In practice, the need to interpret the raw information provided by permanent gauges, and the lack of manpower or expertise for doing so prevents real time intervention. Therefore, some sort of automatic interpretation and alarm system is required to benefit from the full potential of downhole permanent gauges.

A new deconvolution algorithm developed at Imperial College by von Schroeter, Hollaender and Gringarten, makes the development of such tools possible. Deconvolution converts pressures at variable rates into pressures at constant rates, thus making more data analysable. Contrary to deconvolution algorithms previously published in the literature, our algorithm provides stable results. Extensive usage at Imperial and, independently, at BP, has confirmed its huge potential for well test analysis of permanent pressure gauges: deconvolution provides information over a radius of investigation that corresponds to the total duration of the production period, which can be orders of magnitude greater than that available from individual flow periods used for conventional well test analysis. Alternatively, deconvolution can reduce considerably the required duration of an extended well test, by revealing boundaries not visible in individual flow periods.

Experience with our algorithm has identified a number of areas for improvement, most notably the need to handle interference effects in highly permeable formations. The objective of this proposal is to address these issues in order to obtain a robust deconvolution algorithm that can be used with confidence by practicing engineers in a wide variety of field conditions to control and optimise well performance.