Análise da modelagem experimental da perda de injetividade

Injectivity decline, which can be caused by particle retention, generally occurs during water injection or reinjection in oil fields. Several mechanisms, including straining, are responsible for particle retention and pore blocking causing formation damage and injectivity decline. Predicting formation damage and injectivity decline is essential in waterflooding projects. The Classic Model (CM), which incorporates filtration coefficients and formation damage functions, has been widely used to predict injectivity decline. However, various authors have reported significant discrepancies between Classical Model and experimental results, motivating the development of deep bed filtration models considering multiple particle retention mechanisms (Santos & Barros, 2010; SBM). In this dissertation, inverse problem solution was studied and a software for experimental data treatment was developed. Finally, experimental data were fitted using both the CM and SBM. The results showed that, depending on the formation damage function, the predictions for injectivity decline using CM and SBM models can be significantly different

Análise da modelagem experimental da perda de injetividade

Injectivity decline, which can be caused by particle retention, generally occurs during water injection or reinjection in oil fields. Several mechanisms, including straining, are responsible for particle retention and pore blocking causing formation damage and injectivity decline. Predicting formation damage and injectivity decline is essential in waterflooding projects. The Classic Model (CM), which incorporates filtration coefficients and formation damage functions, has been widely used to predict injectivity decline. However, various authors have reported significant discrepancies between Classical Model and experimental results, motivating the development of deep bed filtration models considering multiple particle retention mechanisms (Santos & Barros, 2010; SBM). In this dissertation, inverse problem solution was studied and a software for experimental data treatment was developed. Finally, experimental data were fitted using both the CM and SBM. The results showed that, depending on the formation damage function, the predictions for injectivity decline using CM and SBM models can be significantly different

Modelagem e previsão da perda de injetividade em poços canhoneados

Waterflooding is a technique largely applied in the oil industry. The injected water displaces oil to the producer wells and avoid reservoir pressure decline. However, suspended particles in the injected water may cause plugging of pore throats causing formation damage (permeability reduction) and injectivity decline during waterflooding. When injectivity decline occurs it is necessary to increase the injection pressure in order to maintain water flow injection. Therefore, a reliable prediction of injectivity decline is essential in waterflooding projects. In this dissertation, a simulator based on the traditional porous medium filtration model (including deep bed filtration and external filter cake formation) was developed and applied to predict injectivity decline in perforated wells (this prediction was made from history data). Experimental modeling and injectivity decline in open-hole wells is also discussed. The injectivity of modeling showed good agreement with field data, which can be used to support plan stimulation injection wells

Modelagem matemática e experimental da perda de injetividade em poços canhoneados

Water injection in oil reservoirs is a recovery technique widely used for oil recovery. However, the injected water contains suspended particles that can be trapped, causing formation damage and injectivity decline. In such cases, it is necessary to stimulate the damaged formation looking forward to restore the injectivity of the injection wells. Injectivity decline causes a major negative impact to the economy of oil production, which is why, it is important to foresee the injectivity behavior for a good waterflooding management project. Mathematical models for injectivity losses allow studying the effect of the injected water quality, also the well and formation characteristics. Therefore, a mathematical model of injectivity losses for perforated injection wells was developed. The scientific novelty of this work relates to the modeling and prediction of injectivity decline in perforated injection wells, considering deep filtration and the formation of external cake in spheroidal perforations. The classic modeling for deep filtration was rewritten using spheroidal coordinates. The solution to the concentration of suspended particles was obtained analytically and the concentration of the retained particles, which cause formation damage, was solved numerically. The acquisition of the solution to impedance assumed a constant injection rate and the modified Darcy´s Law, defined as being the inverse of the normalized injectivity by the inverse of the initial injectivity. Finally, classic linear flow injectivity tests were performed within Berea sandstone samples, and within perforated samples. The parameters of the model, filtration and formation damage coefficients, obtained from the data, were used to verify the proposed modeling. The simulations showed a good fit to the experimental data, it was observed that the ratio between the particle size and pore has a large influence on the behavior of injectivity decline.

Modelagem e previsão da perda de injetividade em poços canhoneados

Waterflooding is a technique largely applied in the oil industry. The injected water displaces oil to the producer wells and avoid reservoir pressure decline. However, suspended particles in the injected water may cause plugging of pore throats causing formation damage (permeability reduction) and injectivity decline during waterflooding. When injectivity decline occurs it is necessary to increase the injection pressure in order to maintain water flow injection. Therefore, a reliable prediction of injectivity decline is essential in waterflooding projects. In this dissertation, a simulator based on the traditional porous medium filtration model (including deep bed filtration and external filter cake formation) was developed and applied to predict injectivity decline in perforated wells (this prediction was made from history data). Experimental modeling and injectivity decline in open-hole wells is also discussed. The injectivity of modeling showed good agreement with field data, which can be used to support plan stimulation injection wells

Modelagem analítica e experimental da filtração em meios porosos

Deep bed filtration occurs in several industrial and environmental processes like water filtration and soil contamination. In petroleum industry, deep bed filtration occurs near to injection wells during water injection, causing injectivity reduction. It also takes place during well drilling, sand production control, produced water disposal in aquifers, etc. The particle capture in porous media can be caused by different physical mechanisms (size exclusion, electrical forces, bridging, gravity, etc). A statistical model for filtration in porous media is proposed and analytical solutions for suspended and retained particles are derived. The model, which incorporates particle retention probability, is compared with the classical deep bed filtration model allowing a physical interpretation of the filtration coefficients. Comparison of the obtained analytical solutions for the proposed model with the classical model solutions allows concluding that the larger the particle capture probability, the larger the discrepancy between the proposed and the classical models

Modelagem analítica e experimental da filtração em meios porosos

Deep bed filtration occurs in several industrial and environmental processes like water filtration and soil contamination. In petroleum industry, deep bed filtration occurs near to injection wells during water injection, causing injectivity reduction. It also takes place during well drilling, sand production control, produced water disposal in aquifers, etc. The particle capture in porous media can be caused by different physical mechanisms (size exclusion, electrical forces, bridging, gravity, etc). A statistical model for filtration in porous media is proposed and analytical solutions for suspended and retained particles are derived. The model, which incorporates particle retention probability, is compared with the classical deep bed filtration model allowing a physical interpretation of the filtration coefficients. Comparison of the obtained analytical solutions for the proposed model with the classical model solutions allows concluding that the larger the particle capture probability, the larger the discrepancy between the proposed and the classical models

Simulador de dano à formação, aplicado ao Projeto e à execução da perfuração de poços de petróleo

With the high oil price variability, the petroleum and the reservoir engineers are usually face to face on how they can evaluate the well performance and productivity. They can improve high productivity from the well construction to the secondary recoveries, but they have never tried a measurement in the drilling operations about the lower productivity index. As a rule, frequently the drilling operations hear from the reservoir engineering and geology that, if there is a formation damage, probably some drilling operations practices were not done properly or the good practice in petroleum engineering or mud engineering were not observed. The study in this working search is an attempt of how to measure a formation damage just from the project drilling to the drilling operations, with datum from the fields in Brazilian northeast and putting into practice a Simulator developed from the modeling on the theory offered by different experts and sources in formation damage

Simulador de dano à formação, aplicado ao Projeto e à execução da perfuração de poços de petróleo

With the high oil price variability, the petroleum and the reservoir engineers are usually face to face on how they can evaluate the well performance and productivity. They can improve high productivity from the well construction to the secondary recoveries, but they have never tried a measurement in the drilling operations about the lower productivity index. As a rule, frequently the drilling operations hear from the reservoir engineering and geology that, if there is a formation damage, probably some drilling operations practices were not done properly or the good practice in petroleum engineering or mud engineering were not observed. The study in this working search is an attempt of how to measure a formation damage just from the project drilling to the drilling operations, with datum from the fields in Brazilian northeast and putting into practice a Simulator developed from the modeling on the theory offered by different experts and sources in formation damage

Modelagem matemática para o transporte de partículas sujeitas a múltiplos mecanismos de retenção

Discrepancies between classical model predictions and experimental data for deep bed filtration have been reported by various authors. In order to understand these discrepancies, an analytic continuum model for deep bed filtration is proposed. In this model, a filter coefficient is attributed to each distinct retention mechanism (straining, diffusion, gravity interception, etc.). It was shown that these coefficients generally cannot be merged into an effective filter coefficient, as considered in the classical model. Furthermore, the derived analytic solutions for the proposed model were applied for fitting experimental data, and a very good agreement between experimental data and proposed model predictions were obtained. Comparison of the obtained results with empirical correlations allowed identifying the dominant retention mechanisms. In addition, it was shown that the larger the ratio of particle to pore sizes, the more intensive the straining mechanism and the larger the discrepancies between experimental data and classical model predictions. The classical model and proposed model were compared via statistical analysis. The obtained p values allow concluding that the proposed model should be preferred especially when straining plays an important role. In addition, deep bed filtration with finite retention capacity was studied. This work also involves the study of filtration of particles through porous media with a finite capacity of filtration. It was observed, in this case, that is necessary to consider changes in the boundary conditions through time evolution. It was obtained a solution for such a model using different functions of filtration coefficients. Besides that, it was shown how to build a solution for any filtration coefficient. It was seen that, even considering the same filtration coefficient, the classic model and the one here propposed, show different predictions for the concentration of particles retained in the porous media and for the suspended particles at the exit of the media

Modelagem matemática para o transporte de partículas sujeitas a múltiplos mecanismos de retenção

Discrepancies between classical model predictions and experimental data for deep bed filtration have been reported by various authors. In order to understand these discrepancies, an analytic continuum model for deep bed filtration is proposed. In this model, a filter coefficient is attributed to each distinct retention mechanism (straining, diffusion, gravity interception, etc.). It was shown that these coefficients generally cannot be merged into an effective filter coefficient, as considered in the classical model. Furthermore, the derived analytic solutions for the proposed model were applied for fitting experimental data, and a very good agreement between experimental data and proposed model predictions were obtained. Comparison of the obtained results with empirical correlations allowed identifying the dominant retention mechanisms. In addition, it was shown that the larger the ratio of particle to pore sizes, the more intensive the straining mechanism and the larger the discrepancies between experimental data and classical model predictions. The classical model and proposed model were compared via statistical analysis. The obtained p values allow concluding that the proposed model should be preferred especially when straining plays an important role. In addition, deep bed filtration with finite retention capacity was studied. This work also involves the study of filtration of particles through porous media with a finite capacity of filtration. It was observed, in this case, that is necessary to consider changes in the boundary conditions through time evolution. It was obtained a solution for such a model using different functions of filtration coefficients. Besides that, it was shown how to build a solution for any filtration coefficient. It was seen that, even considering the same filtration coefficient, the classic model and the one here propposed, show different predictions for the concentration of particles retained in the porous media and for the suspended particles at the exit of the media

Modelo Estocástico para bloqueio de poros e redução de permeabilidade

Modeling transport of particulate suspensions in porous media is essential for understanding various processes of industrial and scientific interest. During these processes, particles are retained due to mechanisms like size exclusion (straining), adsorption, sedimentation and diffusion. In this thesis, a mathematical model is proposed and analytical solutions are obtained. The obtained analytic solutions for the proposed model, which takes pore and particle size distributions into account, were applied to predict the particle retention, pore blocking and permeability reduction during dead-end microfiltration in membranes. Various scenarios, considering different particle and pore size distributions were studied. The obtained results showed that pore blocking and permeability reduction are highly influenced by the initial pore and particle size distributions. This feature was observed even when different initial pore and particle size distributions with the same average pore size and injected particle size were considered. Finally, a mathematical model for predicting equivalent permeability in porous media during particle retention (and pore blocking) is proposed and the obtained solutions were applied to study permeability decline in different scenarios

Partículas inteligentes de poli (nisopropilacrilamida), quitosana e poli (ácido acrílico): efeito da temperatura e do pH sobre suas propriedades em suspensões aquosas

The present study describes the stability and rheological behavior of suspensions of poly (N-isopropylacrylamide) (PNIPAM), poly (N-isopropylacrylamide)-chitosan (PNIPAMCS), and poly (N-isopropylacrylamide)-chitosan-poly (acrylic acid) (PNIPAM-CS-PAA) crosslinked particles sensitive to pH and temperature. These dual-sensitive materials were simply obtained by one-pot method, via free-radical precipitation copolymerization with potassium persulfate, using N,N -methylenebisacrylamide (MBA) as a crosslinking agent. Incorporation of the precursor materials into the chemical networks was confirmed by elementary analysis and infrared spectroscopy. The influence of external stimuli such as pH and temperature, or both, on particle behavior was investigated through rheological measurements, visual stability tests and analytical centrifugation. The PNIPAM-CS particles showed higher stability in acid and neutral media, whereas PNIPAM-CS-PAA particles were more stable in neutral and alkaline media, both below and above the LCST of poly (Nisopropylacrylamide) (stability data). This is due to different interparticle interactions, as well as those between the particles and the medium (also evidenced by rheological data), which were also influenced by the pH and temperature of the medium. Based on the results obtained, we found that the introduction of pH-sensitive polymers to crosslinked poly (Nisopropylacrylamide) particles not only produced dual-sensitive materials, but allowed particle stability to be adjusted, making phase separation faster or slower, depending on the desired application. Thus, it is possible to adapt the material to different media