Tight sandstone gas is a significant unconventional natural gas resource, and has been exploited economically mostly through the application of hydraulic fracturing technology in recent decades. However, formation damage occurs when fracturing fluid percolates into the pores inside sandstones through imbibition driven by capillary pressure during fracturing operations. In this work, the formation damage resulting from the whole operation process composed of fracturing, well shut-in and flowback, and the degree of damage at different moments were investigated through core flow experiments and the low-field Nuclear Magnetic Resonance (NMR) technique. The results show that imbibition damage occurs starting from the contact surface between the formation and the fracturing fluid, which penetrates into an increasingly deep position with time down to a certain depth. The T2 spectra of NMR at different moments indicates that fracturing fluid initially enters the small pores, followed by the large pores due to the larger capillary pressure in the former. Thus, the sandstone cores with low permeability incur a higher degree of damage due to their stronger capability of retaining fracturing fluid compared to high-permeability cores. The front position of the fracturing fluid imbibition at different moments, along with the degree of damage, were characterized through the one-dimensional encoding processing of the NMR signal. These results underlie the effective strategy to relieve formation damage resulting from imbibition during hydraulic fracturing operations.
For series continuous stirred tank reactor system (CSTR), it is a complex problem to finetune the fractional order proportional-integral-derivative controller (FOPID). To solve the problem, this paper presents a parameter tuning method based on intelligent optimization genetic algorithm (GA) and integral time absolute error (ITAE). Firstly, the series CSTR system was mathematically modelled by vectorized modules, and an FOPID control system was established. Meanwhile, the intelligent optimization GA was introduced under the ITAE rule, and the empirical PID control parameters were taken as the initial values for iteration, aiming to enhance the effect of the search for optimal solution. To verify its superiority, the FOPID controller optimized by GA was compared with intelligent optimization GA and empirical PID controller through simulation. The results show that the optimized FOPID system achieved much better control effect and stronger anti-interference performance than the contrastive methods.
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