Transient Diagnosis Of Fines Migration Integrating Core Testing And Numerical Reservoir Modeling

To manage well productivity, an effort was undertaken to identify fines migration by means of transient diagnosis, quantify its effect on productivity, model the production history, and forecast well performance. Because of its distinguishable transient behavior, mechanical fines migration can be identified among other factors that contribute to productivity decline. Pressure transient analysis (PTA), production data analysis (PDA), laboratory experiments, and numerical-flow-simulation techniques were used to understand the physics of fines migration, quantify its characteristic parameters, validate the model with production history, and verify its efficacy in a field application. Results are consistent with laboratory observations, synthetic studies leveraging a geomechanics reservoir simulator, and field data for moderate to severe fines migration.A new integrated approach was developed to accurately identify and depict declining productivity caused by fines migration through PTA, core testing, and reservoir flow modeling. Previous research has proposed a permeability-reduction flow function that correlates with extended coreflood data to predict the key parameters that characterize the fines-migration effects: critical velocity, permeability-reduction rate, and ultimate residual permeability. From the transient-behavior observations on wells experiencing fines migration, the obvious damage is represented by a positive skin as a function of time in the near-wellbore region. This concurs with the realization that interstitial velocity decreases with the distance from the wellbore. For severe fines migration observed in both synthetic cases and field data, two permeability regions could be identified and described by a radial composite model allowing the damage radius and the average permeabilities of each zone be estimated. Incorporation of a new technique, which correlates the skin-time function with the fines-migration flow relation, enables the calculation of key parameter ranges. These can be integrated with coreflood data for use as initial values in numerical reservoir modeling, potentially simplifying history-matching efforts before performance forecast.The novelty of this workflow is in the ability to identify and quantify the potential influence of mechanical fines migration with PTA and PDA techniques, and incorporation of the fines-migration flow relation to estimate the ranges of the characteristic parameters used in numerical modeling. Understanding the impact of fines migration on well productivity allows engineers to more accurately predict production decline, identify the benefit of remediation, and select optimal development strategies.