Acid stimulation is used in carbonate reservoirs to bypass formation damage. Carbonate reservoirs are highly heterogeneous with layers of large permeability variation. For even distribution of acid between layers, we have developed a new acid diversion system using nanoparticles. Nanoparticles aggregate size distribution evolves with time, and once it spans pore space, gel structure is formed. The objective of this present a new acid diversion system with nanoparticles based acid system along with model that can predict the gelation kinetics. Experimental inversitgation has been conducted to study the gelation kinetics of nanoparticles at different salts, ionic strength, pH, and temperature. Phase behavior study was first conducted. The best system was then tested in parallel coreflood. Then Population Balance equation (PBE) is used to model the growth of aggregates and the interaction between aggregates and porous media. Quadrature method of moments (QMOM) is used to convert the PBE with continuous distribution of nanoparticle size into moment transport equations for efficient computation. Finite volume method is used for discretization of moment transport equation, acid transport equation, continuity equation and Darcy law. Acid diversion in carbonates using nanoparticle-based in situ gelled acid is proven to be more efficient than convectional diversion systems especially for harsh reservoir conditions. The effect of different salts, ionic strength, pH and temperature was studied experimentally. Coreflooding shows that Nanoparticle-based system can create several complete wormholes in both low and high permeability cores. Nanoparticles plugging small pore throats can divert acid into larger pores and reduce acid leakoff. Model presented in this paper gives insight into the aggregation and gelation kinetics. Model displayed the influence of nanoparticle concentration on gelation time. Once the gel forms, shear thinning behavior is used to model the viscosity of the gel. Shear rate could highly reduce the viscosity of the gel and hence affect the efficiency of acid diversion. The model developed in this work accurately simulate aggregation, initiation of gelation of fumed silica and acid diversion in carbonates. The new acid diversion system is highly effective in even distribution of acid between layers of different permeability. The model developed in this study can help in optimization of new nanoparticles-based acid diversion system.

Reservoirs containing very high total dissolved solids and high hardness make the design of a surfactant polymer (SP) flood extremely difficult because surfactant tends to precipitate and separate under these conditions. Beside divalent ions, Ca2+, Mg2+, presence of iron in the brine can be a challenging issue. Different surfactant formulations are evaluated and incorporate cosurfactants and co-solvents which minimize viscous macroemulsions, promote rapid coalescence under Winsor Type III conditions, and stabilize the chemical solution by reducing precipitation and phase separation. The optimal surfactant formulations were further evaluated in one-dimensional sand packs and coreflood tests using Berea sandstone, reservoir oils, and brines at reservoir temperatures. Using similar injection protocols, 3 pore volumes of surfactant-only system, experimental results show the oil recovery ranging from 45 % to 70% of the residual oil (Sor) after water flooding. The level of surfactant loading is less than 0.5 wt%. A single-well test was conducted to confirm laboratory results in situ in the presence of high-salinity formation water containing 102,300 mg/L total dissolved solids (TDS). The aim of ongoing test is to confirm the effectiveness of the high-salinity surfactant-only formulation (0.46 wt% of surfactant). In this effort, we plan to conduct multiple single-well tests at different wells to minimize the design risks involved for the surfactant pilot test. A pilot test at a sandstone reservoir is scheduled to be performed in July of 2013 to further evaluate the effectiveness of surfactant formulation and address technical issues related to scale-up.

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