PWRI-Induced Injectivity Decline: New Insights on In-Depth Particle
Deposition Mechanisms

Rousseau, D.; Latifa, Hadi; Nabzar, L.

doi:10.2523/107666-ms

Cited by 3 publications

(4 citation statements)

References 15 publications

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“…Produced water re-injection is an important option in productivity enhancement through a produced water management strategy. It simultaneously allows converting waste to value and preserving the environment [20].…”

Section: Operationsmentioning

confidence: 99%

Qualitative Analysis of Enhanced Oil Recovery: Impacts on Air, Surface Water and Groundwater

2014

International Conference on Chemical, Environment &Amp; Biological Sciences (CEBS-2014) Sept. 17-18, 2014 Kuala Lumpur (Malaysi

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Utilization of Enhanced Oil Recovery (EOR) methods increase the economic value of existing fields through increased oil recovery and field life extension. When EOR chemicals are transported, reserved, and injected into deep wells for oil recovery, they may pose environmental problems. So, in order to avoid environmental disasters, environmental impacts of EOR methods must be considered in planning and executing of such methods. Major environmental impacts associated with EOR are contamination of surface water and groundwater, and excessive air emissions especially from thermal operations. The objective of this review paper is to quantify some of the environmental effects of EOR methods in petroleum industry.

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Section: Operationsmentioning

confidence: 99%

Qualitative Analysis of Enhanced Oil Recovery: Impacts on Air, Surface Water and Groundwater

2014

International Conference on Chemical, Environment &Amp; Biological Sciences (CEBS-2014) Sept. 17-18, 2014 Kuala Lumpur (Malaysi

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“…Also, the particles can flocculate at some values of brine salinities and pH. These processes are ignored in the current work in which the so-called classical deep-bed-filtration model (Pang and Sharma 1997;Chauveteau et al 1998;Herzig et al 1970;Sharma and Yortsos 1987;Rousseau et al 2007;Wennberg and Sharma 1997) is used.…”

Section: Mathematical Model For Deep-bed Filtrationmentioning

confidence: 99%

“…Following previous work (Pang and Sharma 1997;Chauveteau et al 1998;Herzig et al 1970;Sharma and Yortsos 1987;Rousseau et al 2007;Wennberg and Sharma 1997), we briefly describe the mathematical model for flow of suspensions in porous media.…”

Section: Mathematical Model For Deep-bed Filtrationmentioning

confidence: 99%

“…The reliable injectivity-decline prediction-allowing for injector-stimulation planning and for the choice of optimal water-management strategy-is based on mathematical modeling with well-known values of the model coefficients. The classical mathematical model for deep-bed filtration, presented by Herzig et al (1970), Sharma and Yortsos (1987), and Rousseau et al (2007), contains two empirical functions: the filtration coefficient that is equal to particle-capture probability per unit length of its trajectory and the formation-damage coefficient that reflects permeability decrease caused by particle retention (the mathematical model for deep-bed filtration, described further in the text, contains equations for both coefficients); both coefficients are functions of the retained-particle concentration. Knowledge of these two parameters is essential for predicting well-injectivity decline during seawater/produced-water injection.…”

Section: Introductionmentioning

confidence: 99%

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Formation-Damage Evaluation From Nonlinear Skin Growth During Coreflooding

Bedrikovetsky

Vaz

Furtado

et al. 2011

SPE Reservoir Evaluation &Amp; Engineering

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Injectivity decline of oilfield injection wells is a widespread phenomenon during seawater/produced-water injection. The decline may result in significant cost increase of the waterflooding project. Reliable modeling-based prediction of injectivity-index decrease is important for waterflood design as well as for the planning of preventive injected-water treatment. One of the reasons for well injectivity decline is permeability decrease caused by rock plugging by solid/liquid particles suspended in the injected water. The mathematical model for deep-bed filtration contains two empirical functions: the filtration coefficient and the formationdamage coefficient. These empirical coefficients must be determined from laboratory coreflood tests by forcing water with particles to flow through the core samples. A routine laboratory method determines the filtration coefficient from expensive and difficult particle-concentration measurements at the core effluent; then, the formation-damage coefficient is determined from inexpensive and simple pressure-drop measurements. An alternative three-point-pressure method uses pressure data at an intermediate point of the core, supplementing pressure measurements at the core inlet and outlet. The method provides unique and stable values for constant-filtration and formation-damage coefficients. In the current work, we consider a more complex case in which both coefficients are linear functions of retained-particle concentration. In this case, the model is fully determined by four constants. The three-point-pressure method furnishes unique values for the four model parameters. A new semianalytical model for axisymmetric suspension filtration was developed to predict well-injectivity decline from the linear coreflood data with pressure measurements in three core points.

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Modeling of Oil-In-Water Dispersion Injection for Enhancing Displacement Front Uniformity in Water-Flooded Heterogeneous Reservoirs

Alahmed

Fjelde

2023

Day 4 Thu, June 08, 2023

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Due to the maturity of water-flooded oil reservoirs, as a consequence of heterogeneity, fluids move preferentially through the most permeable layers, leaving large volumes of mobile oil remain unswept. Injection of oil-in-water (O/W) dispersions can regulate the permeability contrast between these layers. Droplet size distribution and porous media heterogeneity are the principal features that characterize displacement front uniformity. The intent of this work is therefore to provide a fundamental insight into number of factors may influence the dispersion flow in porous media. The workflow in this study is comprised of three stages. First, O/W dispersions with low oil concentrations were prepared and characterized. Second, a series of O/W dispersion injection experiments was conducted. The objective of this stage was to evaluate the distribution of retained oil droplets, pressure drop and permeability reduction in different sandstone core-plugs. Finally, a mathematical model based on the experimental setup was developed to describe the dynamics of O/W dispersion flow. Finite element method (FEM) was employed to numerically solve the governing equations. The experimental results revealed that the number and size of retained oil droplets decay with the core depth and correspondingly in the effluent. Verification of the numerical model was performed by comparing the pressure drop and permeability reduction to the results of analytical solutions. The model showed good validation with the experimental data. The numerical results were closely match those of the analytical solutions. The current work presents a potentially efficient method of modelling to describe the dispersion flow in porous media. However, for field applications, further improvement to the model complexity is required.

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PWRI-Induced Injectivity Decline: New Insights on In-Depth Particle Deposition Mechanisms

Abstract: fax 01-972-952-9435. geom C C Peg Peg > for larger particles.

Cited by 3 publications

References 15 publications

Qualitative Analysis of Enhanced Oil Recovery: Impacts on Air, Surface Water and Groundwater

Qualitative Analysis of Enhanced Oil Recovery: Impacts on Air, Surface Water and Groundwater

Formation-Damage Evaluation From Nonlinear Skin Growth During Coreflooding

Modeling of Oil-In-Water Dispersion Injection for Enhancing Displacement Front Uniformity in Water-Flooded Heterogeneous Reservoirs

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