CHARACTERIZATION OF GAS/GAS CONDENSATE RESERVOIRS BY DECONVOLUTION OF MULTIRATE WELL TEST DATA

Analyzing multirate well test data may not be achieved using conventional methods. Deconvolution reconstructs a unit step response (USR) over a radius of investigation of the multirate well test data and can provide more information than the conventional method. We propose a workflow for characterizing gas/gas condensate reservoirs from multirate well test data. It comprises five steps: (1) linearization of pressure transient signals of both gas and gas condensate reservoirs using pseudo-pressure; (2) extraction of USR of the linearized signals by deconvolution; (3) calculation of the log-log derivative graph of the extracted USR; (4) detection of wellbore, reservoir, and boundary models from the log-log derivative plot; and (5) estimation of wellbore, reservoir, and boundary parameters using their associated flow regimes. The methodology is validated by synthetic well test signals of a gas reservoir and two different gas condensate reservoirs. Results confirm that this technique can correctly detect wellbore, reservoir, and boundary models of all data. Also, the proposed method presents average relative deviations (ARDs) in the range of 0.18%-1% for wellbore storage, 0.01%-1.3% for permeability, 0.11%-3.78% for skin factor, 1%-10% for non-Darcy skin, and 0.11%-0.26% for boundary distance.