Pseudo-adsorption isotherm matching for oil field scale squeeze treatments using a Simple Genetic Algorithm

The most common method for preventing downhole scale formation in oil fields is by injecting a scale inhibitor (SI) “squeeze” treatment. For modelling purposes, the interaction of the SI with the rock is often described by a retention function or adsorption isotherm. Generally, field SI return profiles are not matched exactly in the models simply by using an isotherm derived from corefloods. The process of matching the SI return profiles is currently performed manually, by trial and error, which can be very labour intensive. Once a match has been achieved, subsequent treatments can generally be predicted and optimized with a high degree of accuracy.

The main aim of this paper is to implement a Simple Genetic Algorithm (SGA) to automate the adsorption isotherm matching process and turn it into a history matching exercise. In addition, we assess the performance of the SGA on synthetic and field cases. The results from the synthetic cases demonstrated the existence of more than one possible isotherm match (i.e. local minima exist in the misfit between observations and predictions). Moreover, a sensitivity study showed that they might be equivalent, in the sense that both isotherms show similar predictions in different squeeze treatment scenarios (where SI concentrations, flow rates and volume stages were changed). The SGA was tested against two real field cases (smooth and scattered) showing satisfactory results. The match for the smooth profile was very good, while for the scattered case, it seemed to follow the trend of the observed data.