Abstract
In this work, we propose a methodology for monitoring well productivity index (PI), forecasting production, and estimating reserves using pressure and flow rate data. Within this context, we also provide a system identification technique by computing constant-pressure rate (deconvolved rate) behavior based on deconvolution of pressure and rate measurements. These measurements can be subsurface, surface, or a combination of both. As downhole permanent monitoring systems become more widely used, data quality, frequency, accuracy, and resolution will improve.
For system identification, deconvolved rate is compared with the exponential decline of the system under depletion as a base. Any deviation from the exponential decline may indicate nonlinearities about the system. With this step's input, a geologically based well/reservoir model is constructed for parameter estimation (e.g., reservoir size, pore volume, etc.) using pressure and/or flow-rate measurements. Any available pressure-transient-test data will also be considered.
The methodology proposed in this work can be integrated into data-acquisition softwares for permanent sensors, to provide a real-time monitoring/diagnosis tool for well performance and prediction. Furthermore, deconvolution results and estimated parameters can be verified continuously through a convolution of pressure and rate data, without interrupting production. It is, therefore, well suited for a single well or group of wells under extended testing, equipped with downhole gauges, and flowing through surface separation and metering systems. Wells completed with permanent downhole rate and pressure instrumentation are also ideal candidates for this type of analysis. Two field examples are presented to demonstrate the application of the methodology.