Tese: Reservoir characterization based on pressure and temperature transient data, using an ensemble-based method
Aluno(a) : Vinicius Mattoso Reis da SilvaOrientador(a): Márcio Carvalho
Área de Concentração: Petróleo e Energia
Data: 26/01/2022
Link para tese/dissertação: https://doi.org/10.17771/PUCRio.acad.58784
Resumo: Reservoir characterization is an important tool for production/reservoir management. Well tests are commonly used in reservoir characterization and are the only source of dynamic data during the exploitation period. These tests typically measure the pressure and temperature responses at a well during controlled production, injection, or static conditions. Generally, only pressure data is post-processed in reservoir characterization. However, considering only pressure data can lead to misinterpretation associated with the neglected thermal effects, causing errors in reservoir properties estimation and consequently inefficient reservoir management. Besides that, pressure data have several noise sources that may compromise the accuracy of test results. Recent results have shown that temperature data can be used to improve reservoir parameter estimation. In this work, the ensemble smoother with multiple data assimilation method (ES-MDA) was applied in synthetic cases created by an in-house non-isothermal reservoir-well flow simulator that considers the Joule-Thomson heating and cooling, adiabatic fluid expansion/compression, conduction, and convection effects in the thermal energy balance equation. The synthetic measured data was obtained by adding gaussian and harmonics noises to the numerical predictions to simulate equipment and tidal effects, respectively. A sensitivity analysis of the effect of the CD matrix used for updating parameters of the ES-MDA method on the parameters estimations was carried out. The results show that adding temperature data to the observed data in the history matching improves the estimates of the reservoir parameters, especially for the skin region and reservoir porosity. For the analyses in which the pressure data had the addition of harmonic noise, the inclusion of temperature data also proved to be of great importance for an accurate characterization of the reservoir.