An optimization framework for sandstone acidizing using design of experiment (DOE) and mathematical modelling

Abstract

Fluoroboric acid (HBF4) serve as one of the alternatives for conventional mud acid in the application of sandstone wells stimulation. Various parameters such as formation temperature and acid injection velocity would significantly affect the performance of sandstone acidizing and hence determine the success rate of well stimulation. It is therefore undeniable that a deep understanding of the effects of these major parameters are of paramount importance. However, there is a scarcity of data available in the literature regarding the use of HBF4 in sandstone acidizing in comparison to the use of mud acid. In this work, an optimization framework is developed to study the combined effects of formation temperature and acid injection velocity to the change in porosity and pressure drop. Apart from porosity improvement, a pressure drop across the sandstone core would also give an indication to the acidizing performance. The optimization approach is achieved by using design of experiment (DOE) and response surface methodology, coupled with a mechanistic model for sandstone acidizing. The design of experiment used in this work is central composite design (CCD). Meanwhile, the mechanistic model that simulate a flow in porous media is being developed using COMSOL Multi-physics, which is a computational fluid dynamics (CFD) software that uses finite element method (FEM). In this optimization tool, a range of formation temperature was set between 41˚C and 88˚C, whereas the range of acid injection velocity was set between 1.79×10-5 m/s to 3.78×10-5 m/s. According to the results, the optimum condition studied was found out to be 88˚C and 3.78×10-5 m/s. Under such an operating condition, the favourable maximum porosity enhancement and pressure drop profile were obtained. The maximum porosity and pressure drop were up to 17% and 16.6979 kPa respectively. The porosity enhancement and pressure drop in the sandstone core showed an excellent agreement with the data predicted by the model. In general, this optimization study had proven that response surface methodology (RSM) could be applied to determine the acid performance in sandstone acidizing.