Suspension, colloidal, and emulsion flow in rocks with particle size-exclusion may have a strong effect on the reservoir and on the well behavior during fines migration and production, drillingfluid invasion into oil-or gas-bearing formations, or injection of seawater or produced water. The stochastic microscale equations for size-exclusion colloidal transport in porous media (PM) are derived. The proposed model includes the following new features: It accounts for the accessible flux in the expression for capture rate, it accounts for the increase of inlet concentration caused by the injected particles entering only the accessible area, and it accounts for the dilution of effluent accessible flux in the overall flux of the produced suspension. Two sets of laboratory tests on short-term injection of monosized suspensions have been carried out in engineered PM. The treatment of the laboratory data for short-term continuous-suspension injection shows good agreement with the modeling results. The proposed model shows a better fit to the experimental data than the previous population-balance model for suspension transport in PM, which validates the proposed modified model. Microscale Modeling for Particle Straining The stochastic modeling of suspension flow in PM, accounting for straining particle capture, is established in this section. The medium is represented by the model of triangular parallel capillaries alternated with mixing chambers. The analytical model for lowretention filtration is derived, and the steady-state solution is obtained.
The formation damage in scaled-up production wells caused by incompatibility of injected and formation waters have long been known. Precipitation of salts results in permeability decline. Among the most onerous of all scaling species is that of sulphates, particularly barium and strontium sulphates. We study effects of porous media on the BaSO4 scaling kinetics. A new methodology for determination of reaction rate coefficient from coreflood tests consists of the sequence of diffusivity reaction free tests, of transient tests with chemical reaction, and of simultaneous injections of both injected and formation waters with quasi steady state concentration profiles for barium and sulphate ions. The diffusivity tests serve for dispersivity coefficient determination. Quasi steady state tests allow determination of the reaction rate coefficient versus velocity. The transient test data as compared with the mathematical modelling data validate the model and the data of steady state test data treatment. An analytical model developed is used for treatment of quasi steady state test data. The transient tests are treated by a numerical model. The main result of the work is proportionality between the reaction rate coefficient and flow velocity for the parameter range studied. Introduction The BaSO4 scaling is a chronicle disaster in waterflood projects with incompatible injected and formation waters. This is usually due to precipitation of barium sulphate from the mixture of both waters and consequent permeability reduction1–3. The rate coefficient for the reaction between incompatible chemical species in injected and formation waters is the main parameter that determines the oilfield scaling intensity in cases where the aqueous solution is far from equilibrium. This rate is highly affected by flow velocity, diffusion/dispersion in porous media, pore space geometry and, therefore, the reaction rate coefficients inside and outside porous media should be different. Nevertheless, presently the reaction rate coefficients used in mathematical modelling are obtained in laboratory reactors without porous media4–8. Usually the solid grains are used during water mixing in reactors in order to induce the precipitation centres, but the pore space structure and the relative fluid-rock flows are not represented. The mathematical models for reactive flow in porous media consist on mass balance equations with the reaction rate sink terms8–10. The rate terms should depend on porous media properties. In order to reliably predict well behaviour during the oilfield scaling, the effect of porous media flow on chemical reaction rate should be studied systematically. The design and results of barium sulphate steady state scaling tests allowing for such study have been presented in the literature11–13. Nevertheless, there were no attempts to determine the reaction rate coefficients from laboratory coreflood tests. The laboratory and mathematical study of scaling formation in porous media has been performed13,14. The sequence of coreflood tests allowing for determination of the reaction rate coefficient for various flow conditions has been proposed:displacement of water by traced water at the absence of reaction in order to determine diffusion coefficient;displacement of Ba-rich formation water by SO4-rich injection water (transient tests);simultaneous injection of Ba-rich formation water and SO4-rich injection water (steady state tests). The diffusive tests allow determining the diffusion coefficient dependency of flow velocity for a given core15. The quasi steady state tests being performed at different velocities determine the reaction rate coefficient versus flow velocity. The transient tests allow comparing experimental results with the data of numerical modelling based on the steady state test data.
TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractInjectivity decline is a chronicle disaster during produced water re-injection (PWRI); the phenomenon has been widely reported in the literature for North Sea, Gulf of Mexico and Campos Basin fields. The damage happens due to solid and liquid particles in the re-injected water. The injectivity decline prediction is important for planning and design of PWRI, of injected water treatment and of well stimulation procedures. The reliable prediction should be based on mathematical modelling using well injectivity index history and laboratory data.The mathematical models for deep bed filtration of particles and for external filter cake formation have been developed and adjusted to coreflood and well data by numerous authors (Sharma, Khatib, Wennberg et. al.). Here we add modelling of external cake erosion during well closing by the growing cake and filling the well by the erosion particles and develop a comprehensive model.The comprehensive model predicts very peculiar injectivity index (II) curve: initial II increase due to displacement of oil by less viscous water, slow II decline due to deep bed filtration, fast II decrease during external filter cake formation, II stabilization due to cake erosion during the rat hole filling by the eroded particles and further II decrease during well column filling by erosion products.The model is implemented in Excel; the software SPIN Simulates and Predicts the INjectivity.We present in details the history matching for three injectors (field X, Campos Basin, Brazil), showing good agreement between modelling and well data. The obtained values of injectivity damage parameters lay in the same rage intervals as those calculated from laboratory corefloods.
Abstrac tSevere fall of injectivity in porous rock occurs from the practice in offshore fields of injecting sea water containing organic and urineral inclusions . In general, injection of a poor quality water in a well curtails its injectivity . The injectivity loss is assumed to be due to particle retention in the porous rock .A model for porous rock damage due to retention in Jeep filtration during injection of water containing solid particles is formulated. The model contains two empirical functions that affect loss of injectivity -filtration coefficient and damage coefficient versus deposited particle concentration.We show how to solve the inverse problem for determining the first function based on effluent particle concentration measurements in coreflood tests .The second inverse problem is the determination of the formation damage coefficient from the pressure drop history on a core . These two methods allow determining from laboratory tests the information necessary for prediction of well impairment .
Severe fall of injectivity happens with the reinjection of produced water which contains oil droplets and solid particles, with the injection of sea water in offshore fields which contains organic and mineral inclusions, and in a general case of injection of a poor quality water. The mathematical model contains two empirical functions - filtration coefficient versus concentration of deposited particles and velocity and formation damage function versus concentration of deposited particles. Two inverse problems for determination of these two functions from the laboratory coreflood test are formulated. The first problem is determination of a filtration coefficient from the concentration history on a core outlet. The algorithm of solution is given, and the laboratory data treatment is presented. The second problem is determination of a formation damage function from the pressure drop history on a core. These two methods allows to determine from laboratory test the information necessary for prediction of well impairment. Introduction Injectivity reduction with the injection of water which contains solid and liquid inclusions takes place to some degree in most waterflooding projects. It becomes an important issue with respect to waterflooding of offshore fields using the sea water which usually contains different organic matters and solids. Facilities for raw sea water treatment are very limited by limitations for operations in sea platforms, so often a poor quality water is used in offshore waterflood projects. Reinjection of produced water which contains oil droplets and solid particles happens in several onshore fields and is often accompanied by injectivity decline. Amongst the advantages of produced water reinjection are that the water quality treatment for produced water is less than that for raw water from other sources; also produced water is usually compatible with the reservoir fluids and do not cause scale problems7,8. Nevertheless, oil droplets and solid particles may be present in the produced water, which often causes severe formation damage. Presently produced water reinjection is under consideration in offshore fields due to the possible environmental impact of the alternative of sea disposal. In designing a waterflood project, the level of water treatment necessary to minimise formation damage must be assessed, particularly whether solids or oil droplets should be removed and by how much. The different water treatment options are to be considered, so it is important to know the performance of an injector as a function of quality of injection water. Therefore, substantial efforts have been done in modelling of injectivity decline with injection of water with solid particles and oil droplets. The flow of solid-containing suspensions have been studied in many engineering branches, including the petroleum one, and was widely exposed in the literature, while there has been little published on the aspect of formation damage resulting from the flow of oily water. The basic mathematical model for deep filtration with particle retention consists on the mass balance equation and the kinetic equation for clogging1–5. The analytical model for diffusion-free flow was developed in the work1 under the assumptions that accumulation of suspended particles can be ignored and that the suspended concentration distribution is steady state. The simplified assumption that filtration coefficient is constant is proposed in other works3,4. In this case the direct problem of prediction of concentation of particles and pressure drop on the core allows for simple analytical solution.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.